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1

On Extracting Evolutions from Satellite Image Time Series  

Microsoft Academic Search

Due to the increase in size, in resolution, in spectral channel numbers and in acquisition frequency of remote sensing images, there is a need for processing huge volumes of observation data for a same geographical zone at different dates. This kind of data is termed as Satellite Image Times-Series (STIS) (1). In this paper, we propose to extract pixel-based evolutions

Andreea Julea; Nicolas Méger; Emmanuel Trouvé; Philippe Bolon

2008-01-01

2

Change detection in time series of high resolution SAR satellite images  

NASA Astrophysics Data System (ADS)

In the last few years, change detection based on remote sensing data has become a highly frequented field of research with multiple applications for practical use. To detect changes between temporarily different satellite images is of interest for example in terms of urban monitoring and disaster management. The approach presented in this paper allows the fully automatic detection of small-scaled changes (e.g. vehicles or construction sites) in time series of SAR amplitude image data. To create a robust method, only one single parameter encoding the size of the detected changes has to be set by the operator. Furthermore, first steps concerning the categorization of the detected changes are presented. As dataset, a time series of high resolution SAR images acquired by the German satellite TerraSAR-X was used. The time span of this time series, acquired in ascending and descending orbit, is about half a year.

Boldt, Markus; Schulz, Karsten

2012-10-01

3

Unsupervised Spatiotemporal Mining of Satellite Image Time Series Using Grouped Frequent Sequential Patterns  

Microsoft Academic Search

An important aspect of satellite image time series is the simultaneous access to spatial and temporal information. Various tools allow end users to interpret these data without having to browse the whole data set. In this paper, we intend to extract, in an unsupervised way, temporal evolutions at the pixel level and select those covering at least a minimum surface

Andreea Julea; Nicolas Meger; Philippe Bolon; Christophe Rigotti; Marie-Pierre Doin; Cécile Lasserre; Emmanuel Trouve; Vasile N. Lazarescu

2011-01-01

4

Polsar RADARSAT-2 Satellite Image Time Series mining over the Chamonix Mont-Blanc test site  

Microsoft Academic Search

This paper presents a data mining approach for describing Satellite Image Time Series (SITS) spatially and temporally. It relies on pixel-based evolution and sub-evolution extraction. These evolutions, namely the {frequent grouped sequential patterns}, are required to cover a minimum surface and to affect pixels that are sufficiently connected. These spatial constraints are actively used to face large data volumes and

A. Julea; F. Ledo; N. Meger; E. Trouve; Ph. Bolon; C. Rigotti; R. Fallourd; J.-M. Nicolas; G. Vasile; M. Gay; O. Harant; L. Ferro-Famil; F. Lodge

2011-01-01

5

Extraction of frequent grouped sequential patterns from Satellite Image Time Series  

Microsoft Academic Search

This paper presents an original data mining approach for extracting pixel evolutions and sub-evolutions from Satellite Image Time Series. These patterns, called frequent grouped sequential patterns, represent the (sub-)evolutions of pixels over time, and have to satisfy two constraints: firstly to correspond to at least a given minimum surface and secondly to be shared by pixels that are sufficiently connected.

Andreea Julea; Nicolas Méger; Christophe Rigotti; Marie-Pierre Doin; Cécile Lasserre; Emmanuel Trouvé; Philippe Bolon; Vasile Lazarescu

2010-01-01

6

Change Detection Analysis on Time Series of Satellite Images with Variable Illumination Conditions and Spatial Resolution  

Microsoft Academic Search

Very recently satellite systems for remote sensing are required to provide images with a spatial and temporal resolution suitable to be applied for disaster management. High resolution (HR) satellite imagery can provide a good insight into the magnitude of a disaster and a detailed assessment of the damage. To meet these objectives, HR imagery has to be collected immediately after

G. Laneve; E. G. Cadau; D. De Rosa

2007-01-01

7

Landslide activity peak of late 1980's in Central Yamal, Russia, observed from satellite image time series  

NASA Astrophysics Data System (ADS)

A large set of cryogenic landslides occurred in Bovanenkovo region in Central Yamal peninsula, Arctic Russia in late 1980's. Database of satellite images was collected to follow landslide activity 1969-2011. Imagery used were CORONA, Landsat MSS/TM/ETM7, SPOT, Terra ASTER VNIR and Quickbird-2 images from years 1969, 1988, 1993, 1998, 2001, 2004 and 2011. Field data was collected from several years and sites. Earliest data was collected in 1993. More recent data was collected in 2004 and 2005. Main field data was collected in 2011 from Mordy-Jaha landslide field. CORONA image from 1969 is used as a starting date of analysis. Landsat TM image dated from 1988 just before the main landslide event in 1989. This image was compared to SPOT (1993,1998), Landsat ETM+ (1999, 2001), Landsat TM (2011) and Terra ASTER VNIR (2001) images to detect occurred landslides. Quickbird-2 (2004) (QB) images were used to help the interpretation of the SPOT and Landsat images and to detect small scale landslides (< 1 ha). All identified landslides were saved into a GIS database as points and the boundaries of the landslides were digitized. From SPOT, Landsat, ASTER and Quickbird-2 images bare soil were classified both with unsupervised and supervised methods. Characteristic spectral reflectance of landslides was estimated and images were reclassified. Change detection using NDVI verified well larger scale landslides, but was not generally reliable enough alone to estimate the occurrance and areas of the landslides. Errors caused by nearby Bovanenkovo gas fields anthropogenic disturbances like roads, quarriers and other infrastructure around the gas field were masked out with buffers. In data analysis we used ERDAS Imagine 2011 and ArcGIS 10. Final estimation of landslide occurrence was made with combined visual interpretations, change detection (NDVI), image classifications. Totally in the study area there were about 600 landslides.

Kumpula, Timo; Mikhaylova, Tatiana; Ukraintseva, Natalia; Forbes, Bruce

2013-04-01

8

IDP camp evolvement analysis in Darfur using VHSR optical satellite image time series and scientific visualization on virtual globes  

NASA Astrophysics Data System (ADS)

In this paper we focus on the application of transferable, object-based image analysis algorithms for dwelling extraction in a camp for internally displaced people (IDP) in Darfur, Sudan along with innovative means for scientific visualisation of the results. Three very high spatial resolution satellite images (QuickBird: 2002, 2004, 2008) were used for: (1) extracting different types of dwellings and (2) calculating and visualizing added-value products such as dwelling density and camp structure. The results were visualized on virtual globes (Google Earth and ArcGIS Explorer) revealing the analysis results (analytical 3D views,) transformed into the third dimension (z-value). Data formats depend on virtual globe software including KML/KMZ (keyhole mark-up language) and ESRI 3D shapefiles streamed as ArcGIS Server-based globe service. In addition, means for improving overall performance of automated dwelling structures using grid computing techniques are discussed using examples from a similar study.

Tiede, Dirk; Lang, Stefan

2009-09-01

9

A radar image time series  

Microsoft Academic Search

A set of side-looking radar images has been collected over an area in the Sierrita Pediment, Arizona, U.S.A. The dates of image acquisition vary from 1965-1979 and the images are taken at various look angles, frequencies, flight directions and polarizations. The objective of the study is to demonstrate the photogrammetric orthophoto technique applied to radar images and at the same

F. Leberl; H. Fuchs; J. P. Ford

1981-01-01

10

Using Time-Series Satellite Imaging Radar Data to Monitor Inundation Patterns and Hydroperiod in Herbaceous Wetlands of Southern Florida  

NASA Astrophysics Data System (ADS)

Knowledge of the components of the hydrologic cycle, including spatial and temporal distribution of water, is critical for regional hydrologic applications. However, at a regional scale, the variations of hydrologic condition are often too great to be easily quantified with ground-based observations alone. We developed methods to use satellite imaging radar data to monitor changes in hydrologic condition of regional scale wetland ecosystems in south Florida. Satellite imaging radar data have been shown to be sensitive to soil moisture variations and to flood conditions in a variety of wetland ecosystems. Initial observations of south Florida imagery from the European Space Agency's C-band microwave sensor onboard the European Remote Sensing Satellite (ERS) showed dynamic variations in backscatter between wet and dry seasons. Further studies revealed how fluctuations in water level influenced ERS radar backscatter for several different herbaceous vegetation cover types. Unfortunately, the C-band wavelength is incapable of penetrating dense forested canopies, thus, our research was focused on the vast herbaceous wetland ecosystems of southern Florida. The ERS synthetic aperture radar (SAR) sensor is a C-band, 5.7 cm wavelength imaging radar with vertical transmit and receive polarization (C-VV). The ERS sensor has a resolution of 30 m and a footprint of 100 by 100 km. SARs have the unique capability to collect data independent of cloud cover and solar illumination. This provides an advantage in areas typically covered by clouds such as tropical and sub-tropical regions like south Florida. In this study, several techniques were developed to utilize SAR data to detect, monitor, and map spatial and temporal changes in wetland hydrology. This study shows that radar imagery can be used to create innundation maps of relative soil moisture and flooding in herbaceous wetlands. Using C-band SAR imagery collected between 1997 and 1999, hydropattern maps were created at approximately bi-monthly periods for the south Florida region. In addition, a methodology for creating hydroperiod (the time period of flooding) maps was developed and examples from wet and dry years are presented. Principal component Analysis (PCA) was the basis of our hydroperiod maps and was linked to rainfall patterns of the south Florida region. Validation of the maps was conducted with in situ data and review by experts in the region.

Bourgeau-Chavez, L. L.; Kasischke, E.

2002-05-01

11

Segmentation of Signals, Time Series, and Images.  

National Technical Information Service (NTIS)

Signals and time series often are not homogeneous but rather are generated by mechanisms or processes with various phases. Similarly, images are not homogeneous but contain various objects. 'Segmentation' is a process of attempting to recover automaticall...

S. L. Sclove

1985-01-01

12

Assessing land-use and carbon stock in slash-and-burn ecosystems in tropical mountain of Laos based on time-series satellite images  

NASA Astrophysics Data System (ADS)

In the tropical mountains of Southeast Asia, slash-and-burn (S/B) agriculture is a widely practiced and important food production system. The ecosystem carbon stock in this land-use is linked not only to the carbon exchange with the atmosphere but also with food and resource security. The objective of this study was to provide quantitative information on the land-use and ecosystem carbon stock in the region as well as to infer the impacts of alternative land-use and ecosystem management scenarios on the carbon sequestration potential at a regional scale. The study area was selected in a typical slash-and-burn region in the northern part of Laos. The chrono-sequential changes of land-use such as the relative areas of community age and cropping (C) + fallow (F) patterns were derived from the analysis of time-series satellite images. The chrono-sequential analysis showed that a consistent increase of S/B area during the past three decades and a rapid increase after 1990. Approximately 37% of the whole area was with the community age of 1-5 years, whereas 10% for 6-10 years in 2004. The ecosystem carbon stock at a regional scale was estimated by synthesizing the land-use patterns and semi-empirical carbon stock model derived from in situ measurements where the community age was used as a clue to the linkage. The ecosystem carbon stock in the region was strongly affected by the land-use patterns; the temporal average of carbon stock in 1C + 10F cycles, for example, was greater by 33 MgC ha -1 compared to that in 1C + 2F land-use pattern. The amount of carbon lost from the regional ecosystems during 1990-2004 periods was estimated to be 42 MgC ha -1. The study approach proved to be useful especially in such regions with low data-availability and accessibility. This study revealed the dynamic change of land-use and ecosystem carbon stock in the tropical mountain of Laos as affected by land-use. Results suggest the significant potential of carbon sequestration through changing land-use and ecosystem management scenarios. These quantitative estimates would be useful to better understand and manage the land-use and ecosystem carbon stock towards higher sustainability and food security in similar ecosystems.

Inoue, Yoshio; Kiyono, Yoshiyuki; Asai, Hidetoshi; Ochiai, Yukihito; Qi, Jiaguo; Olioso, Albert; Shiraiwa, Tatsuhiko; Horie, Takeshi; Saito, Kazuki; Dounagsavanh, Linkham

2010-08-01

13

The impact of the 2011 T¯o hoku-oki tsunami in the Sendai area: interpretations of time series satellite images and videos.  

NASA Astrophysics Data System (ADS)

The Tohoku-oki tsunami of March 11th 2011 was the most devastating tsunami to strike Japan in recorded history. Approximately 20,000 people died and 100's of square kms of the coast were inundated. Runup heights (local tsunami height above sea level) were at a maximum of 40 m along the northern Honshu coast. Farther south, on the Sendai coastal plain, tsunami runup heights were lower, with a maximum of 20 m recorded. The tsunami inundated up to 5 km inland across the Sendai Plain, which remained partly flooded for several weeks after the event. For the first time after a major natural disaster, post-event satellite imagery of the affected areas was immediately released. Numerous helicopter videos were also acquired. This contribution presents on pre- and post-tsunami satellite time-series data and video imagery to show the impact of the tsunami along a 15 km stretch of coastline of the Sendai Plain between Yuriagi and Iwanuma. The video and satellite data, in association with other data from tide gauges, ocean buoys, survivor observations and fieldwork, are used to identify the tsunami inundation path, tsunami timing, inundation limits and impact on the coastal areas.

Tappin, D.

2012-04-01

14

Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach  

NASA Astrophysics Data System (ADS)

We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and K?lauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth’s volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.

Koeppen, W. C.; Pilger, E.; Wright, R.

2010-12-01

15

Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach  

NASA Astrophysics Data System (ADS)

We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and K?lauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth's volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.

Koeppen, W. C.; Pilger, E.; Wright, R.

2011-07-01

16

On Fire regime modelling using satellite TM time series  

NASA Astrophysics Data System (ADS)

Wildfires can cause an environment deterioration modifying vegetation dynamics because they have the capacity of changing vegetation diversity and physiognomy. In semiarid regions, like the northwestern Patagonia, fire disturbance is also important because it could impact on the potential productivity of the ecosystem. There is reduction plant biomass and with that reducing the animal carrying capacity and/or the forest site quality with negative economics implications. Therefore knowledge of the fires regime in a region is of great importance to understand and predict the responses of vegetation and its possible effect on the regional economy. Studies of this type at a landscape level can be addressed using GIS tools. Satellite imagery allows detect burned areas and through a temporary analysis can be determined to fire regime and detecting changes at landscape scale. The study area of work is located on the east of the city of Bariloche including the San Ramon Ranch (22,000 ha) and its environs in the ecotone formed by the sub Antarctic forest and the patagonian steppe. We worked with multiespectral Landsat TM images and Landsat ETM + 30m spatial resolution obtained at different times. For the spatial analysis we used the software Erdas Imagine 9.0 and ArcView 3.3. A discrimination of vegetation types has made and was determined areas affected by fires in different years. We determined the level of change on vegetation induced by fire. In the future the use of high spatial resolution images combined with higher spectral resolution will allows distinguish burned areas with greater precision on study area. Also the use of digital terrain models derived from satellite imagery associated with climatic variables will allows model the relationship between them and the dynamics of vegetation.

Oddi, F.; . Ghermandi, L.; Lanorte, A.; Lasaponara, R.

2009-04-01

17

Time series of Essential Climate Variables from Satellite Data  

NASA Astrophysics Data System (ADS)

Climate change is a fact. We need to know how the climate system will develop in future and how this will affect workaday life. To do this we need climate models for prediction of the future on all time scales, and models to assess the impact of the prediction results to the various sectors of social and economic life. With this knowledge we can take measures to mitigate the causes and adapt to changes. Prerequisite for this is a careful and thorough monitoring of the climate systems. Satellite data are an increasing & valuable source of information to observe the climate system. For many decades now satellite data are available to derive information about our planet earth. EUMETSAT is the European Organisation in charge of the exploitation of satellite data for meteorology and (since the year 2000) climatology. Within the EUMETSAT Satellite Application Facility (SAF) Network, comprising 8 initiatives to derive geophysical parameters from satellite, the Satellite Application Facility on Climate Monitoring (CM SAF) is especially dedicated to provide climate relevant information from satellite data. Many products as e.g. water vapour, radiation at surface and top of atmosphere, cloud properties are available, some of these for more then 2 decades. Just recently the European Space Agency (ESA) launched the Climate Change Initiative (CCI) to derive Essential Climate Variables (ECVs) from satellite data, including e.g. cloud properties, aerosol, ozone, sea surface temperature etc.. The presentation will give an overview on some relevant European activities to derive Essential Climate Variables from satellite data and the links to Global Climate Observing System (GCOS), the Global Satellite Intercalibration System (GSICS) as well as the Sustained Co-ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE CM).

Werscheck, M.

2010-09-01

18

Uncertainty in satellite rainfall estimates: time series comparison  

Microsoft Academic Search

We examined nine satellite rainfall algorithms and compared the rain fields produced from these algorithms for the period of August 1987 to December 1988. Preliminary results show algorithms which use the same satellite sensor data tend to be similar, suggesting the importance of sampling. Oceanic global mean rainfall ranges from 2.7 to 3.6 mm\\/d. The variability in zonal mean rain

Alfred T. C. Chang; Long S. Chiu

1997-01-01

19

Uncertainty in satellite rainfall estimates: Time series comparison  

Microsoft Academic Search

We examined nine satellite rainfall algorithms and compared the rain fields produced from these algorithms for the period of August 1987 to December 1988. Preliminary results show algorithms which use the same satellite sensor data tend to be similar, suggesting the importance of sampling. Oceanic global mean rainfall ranges from 2.7 to 3.6 mm\\/d. The variability in zonal mean rain

Alfred T. C. Chang; Long S. Chiu

1997-01-01

20

Drought Monitoring by Time Series Analysis of Satellite Land Surface Temperature  

Microsoft Academic Search

With the development of remote sensing in the last thirty years massive satellite data have been accumulated by different satellite sensors. These continuous satellite data record the information on changes in land surface conditions. The research on the information retrieving from satellite time series data is of great significance, including applications to climate change research, identification of phenology, hydrological modeling,

J. Li; L. Jia

2009-01-01

21

De-noising of microwave satellite soil moisture time series  

NASA Astrophysics Data System (ADS)

The use of satellite soil moisture data for scientific and operational hydrologic, meteorological and climatological applications is advancing rapidly due to increasing capability and temporal coverage of current and future missions. However evaluation studies of various existing remotely-sensed soil moisture products from these space-borne microwave sensors, which include AMSR-E (Advanced Microwave Scanning Radiometer) on Aqua satellite, SMOS (Soil Moisture and Ocean Salinity) mission and ASCAT (Advanced Scatterometer) on MetOp-A satellite, found them to be significantly different from in-situ observations, showing large biases and different dynamic ranges and temporal patterns (e.g., Albergel et al., 2012; Su et al., 2012). Moreover they can have different error profiles in terms of bias, variance and correlations and their performance varies with land surface characteristics (Su et al., 2012). These severely impede the effort to use soil moisture retrievals from multiple sensors concurrently in land surface modelling, cross-validation and multi-satellite blending. The issue of systematic errors present in data sets should be addressed prior to renormalisation of the data for blending and data assimilation. Triple collocation estimation technique has successfully yielded realistic error estimates (Scipal et al., 2008), but this method relies on availability of large number of coincident data from multiple independent satellite data sets. In this work, we propose, i) a conceptual framework for distinguishing systematic periodic errors in the form of false spectral resonances from non-systematic errors (stochastic noise) in remotely-sensed soil moisture data in the frequency domain; and ii) the use of digital filters to reduce the variance- and correlation-related errors in satellite data. In this work, we focus on the VUA-NASA (Vrije Universiteit Amsterdam with NASA) AMSR-E, CATDS (Centre National d'Etudes Spatiales, CNES) SMOS and TUWIEN (Vienna University of Technology) ASCAT data sets to identify two types of errors that are spectrally distinct. Based on a semi-empirical model of soil moisture dynamics, we consider possible digital filter designs to improve the accuracy of their soil moisture products by reducing systematic periodic errors and stochastic noise. We describe a methodology to design bandstop filters to remove artificial resonances, and a Wiener filter to remove stochastic white noise present in the satellite data. Utility of these filters is demonstrated by comparing de-noised data against in-situ observations from ground monitoring stations in the Murrumbidgee Catchment (Smith et al., 2012), southeast Australia. Albergel, C., de Rosnay, P., Gruhier, C., Muñoz Sabater, J., Hasenauer, S., Isaksen, L., Kerr, Y. H., & Wagner, W. (2012). Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment, 118, 215-226. Scipal, K., Holmes, T., de Jeu, R., Naeimi, V., & Wagner, W. (2008), A possible solution for the problem of estimating the error structure of global soil moisture data sets. Geophysical Research Letters, 35, L24403. Smith, A. B., Walker, J. P., Western, A. W., Young, R. I., Ellett, K. M., Pipunic, R. C., Grayson, R. B., Siriwardena, L., Chiew, F. H. S., & Richter, H. (2012). The Murrumbidgee soil moisture network data set. Water Resources Research, 48, W07701. Su, C.-H., Ryu, D., Young, R., Western, A. W., & Wagner, W. (2012). Inter-comparison of microwave satellite soil moisture retrievals over Australia. Submitted to Remote Sensing of Environment.

Su, Chun-Hsu; Ryu, Dongryeol; Western, Andrew; Wagner, Wolfgang

2013-04-01

22

Satellite imagery time series for the detection of looting activities at archaeological sites  

NASA Astrophysics Data System (ADS)

Clandestine excavations is one of the biggest man-made risks which affect the archaeological heritage, especially in some countries of Southern America, Asia and Middle East. To contrast and limit this phenomenon a systematic monitoring is required. The protection of archaeological heritage from clandestine excavations is generally based on a direct surveillance, but it is time consuming and expensive for remote archaeological sites and non practicable in several countries due to military or political restrictions. In such conditions, Very high resolution (VHR) satellite imagery offer a suitable chance thanks to their global coverage and frequent revisitation times. This paper is focused on the results we obtained from ongoing research focused on the use of VHR satellite images for the identification and monitoring of looting. A time series of satellite images (QuickBird-2 and World-View-1) has been exploited to analyze and monitor archaeological looting in the Nasca Ceremonial Centre of Cahuachi (Peru) dating back between the 4th centurt B.C. and the 4th century A.D. The Cahuachi study case herein presented put in evidence the limits of VHR satellite imagery in detecting features linked to looting activity. This suggested to experience local spatial autocorrelation statistics which allowed us to improve the reliability of satellite in mapping looted area.

Coluzzi, Rosa; Lasaponara, Rosa; Masini, Nicola

2010-05-01

23

Estimation of vegetation cover resilience from satellite time series  

NASA Astrophysics Data System (ADS)

Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation activity. In order to characterize resilience, we analyzed the time series 1982 2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. Persistence probability of negative and positive trends was estimated according to the vegetation cover class, altitude, and climate. Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. Some signatures of inefficient resilience were found in high-level mountainous areas and in the Mediterranean sub-tropical ones. This analysis was refined by aggregating pixels according to phenology. This multitemporal clustering synthesized information on vegetation cover, climate, and orography rather well. The consequent persistence estimations confirmed and detailed hints obtained from the previous analyses. Under the same climatic regime, different vegetation resilience levels were found. In particular, within the Mediterranean sub-tropical climate, clustering was able to identify features with different persistence levels in areas that are liable to different levels of anthropic pressure. Moreover, it was capable of enhancing reduced vegetation resilience also in the southern areas under Warm Temperate sub-continental climate. The general consistency of the obtained results showed that, with the help of suited analysis methodologies, 8 km AVHRR-NDVI data could be useful for capturing details on vegetation cover activity at local scale even in complex territories such as that of the Italian peninsula.

Simoniello, T.; Lanfredi, M.; Liberti, M.; Coppola, R.; Macchiato, M.

2008-07-01

24

Measuring vertical deformation in the Seattle, WA urban corridor with satellite radar interferometry time series analysis  

Microsoft Academic Search

Satellite radar interferometry (InSAR) time series analysis (e.g., Lundgren et al., 2001) can reveal rich patterns of deformation in both time and space. As the technique is sensitive to mm-scale vertical deformation over large and spatially extensive regions, it provides a useful geodetic tool where satellite coverage and radar phase coherence permit. Here we apply InSAR time series techniques based

N. J. Finnegan; M. E. Pritchard; R. Lohman; P. R. Lundgren

2007-01-01

25

Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach  

Microsoft Academic Search

We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify\\u000a the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed\\u000a MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust\\u000a Satellite Techniques (RST)

W. C. Koeppen; E. Pilger; R. Wright

2011-01-01

26

Volcanic SO2 flux time series from MSG-SEVIRI satellite measurements.  

NASA Astrophysics Data System (ADS)

Quantitative retrieval maps of SO2 and ash columnar abundances retrieved from thermal infrared (TIR) satellite images of volcanic plumes can be converted into flux time series if the wind field is known. In a recently published work we showed how to reconstruct SO2 and ash fluxes from a single TIR MODIS image instrument aboard TERRA and AQUA polar satellites. The results obtained were then successfully compared with the SO2 flux measured with the FLAME ground-based network of DOAS instruments in a case study of the December, 2006 Mt. Etna (Sicily, Italy) eruption. The key point of this work was that a single multispectral image framing a volcanic cloud can be regarded as the evolution in time of physical and volcanological parameters, and effectively records many hours of volcanic activity. We highlight that the flux reconstruction obtained from satellite data with this technique offers new perspectives that are particularly valuable for the monitoring of remote volcanoes and allows some insights on the volcanic processes driving the eruptions. Here we show how this promising approach can be easily extended to a collection of TIR MSG-SEVIRI images exploiting the high acquisition frequency achieved by an instrument on board on a geostationary platform.

Merucci, L.; Corradini, S.

2012-04-01

27

Reconstruction of cloud-free time series satellite observation of land surface temperature  

NASA Astrophysics Data System (ADS)

Time series satellite observations of land surface properties, like Land Surface Temperature (LST), often feature missing data or data with anomalous values due to cloud coverage, malfunction of sensor, atmospheric aerosols, defective cloud masking and retrieval algorithms. Preprocessing procedures are needed to identify anomalous observations resulting the gaps and outliers and then reconstruct the time series by filling the gaps. Hourly LST parameters, estimated from data acquired by the Single channel Visible and Infrared Spin Scan Radiometer (S-VISSR) sensor onboard the Fengyun-2C (FY-2C) Chinese geostationary satellite have been used in this study which cover the whole Tibetan Plateau from 2008 through 2010 with a 5×5Km spatial resolution. Multi-channel Singular Spectrum Analysis (M-SSA), an advanced methodology of time series analysis, has been utilized to reconstruct LST time series. The results show that this methodology has the ability to fill the gaps and also remove the outliers (both positive and negative). To validate the methodology, we employed LST ground measurements and created artificial gaps. The results indicated with 63% of hourly gaps in the time series, the Mean Absolute Error (MAE) reached to 2.25 Kelvin (K) with R2 = 0.83 This study shows the ability of M-SSA that uses temporal and spatio-temporal correlation to fill the gaps to reconstruct LST time series.

Ghafarian, Hamid; Menenti, Massimo; Jia, Li; den Ouden, Hendrik

2013-04-01

28

Spatial filter velocimetry based on time-series particle images  

NASA Astrophysics Data System (ADS)

High accuracy and high spatial resolution are required in measurements of fluid velocity for detailed flow diagnostics. In this study, we proposed spatial filter velocimetry (SFV) based on a frequency analysis of time-series spatially filtered particle images. Since this method can measure velocity from one particle in a measurement region, it enables us to measure the velocity with high accuracy and high spatial resolution. We developed a SFV system and applied it to laminar and turbulent flows in a duct to examine its performance. Comparisons between the velocities measured by SFV and LDV confirmed that SFV accurately measures the mean velocity and turbulent intensity with spatial and temporal resolutions as high as LDV.

Hosokawa, Shigeo; Tomiyama, Akio

2012-06-01

29

Spatial and temporal Amazon vegetation dynamics and phenology using time series satellite data  

NASA Astrophysics Data System (ADS)

Improved knowledge of landscape seasonal variations and phenology at the regional scale is needed for carbon and water flux studies, and biogeochemical, hydrological, and climate models. Amazon vegetation mechanisms and dynamics controlling biosphere-atmosphere interactions are not entirely understood. To better understand these processes, vegetation photosynthetic activity and canopy water and temperature dynamics were analyzed over various types of vegetation in Amazon using satellite data from the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS). The objectives of this dissertation were to (1) assess the spatial and temporal variations of satellite data over the Amazon as a function of vegetation physiognomies for monitoring and discrimination, (2) investigate seasonal vegetation photosynthetic activity and phenology across the forest-cerrado ecotone and conversion areas, and (3) investigate seasonal variations of satellite-based canopy water and land surface temperature in relation to photosynthetic activity over the Amazon basin. The results of this study showed the highly diverse and complex cerrado biome and associated cerrado conversions could be monitored and analyzed with MODIS vegetation index (VI) time series data. The MODIS enhanced vegetation index (EVI) seasonal profiles were found useful in characterizing the spatial and temporal variability in landscape phenology across a climatic gradient of rainfall and sunlight conditions through the rainforest-cerrado ecotone. Significant trends in landscape phenology were observed across the different biomes with strong seasonal shifts resulting from differences in vegetation physiognomic responses to rainfall and sunlight. We also found unique seasonal and temporal patterns of the land surface water index (LSWI) and land surface temperature (LST), which in combination with the EVI provided improved information for monitoring the seasonal ecosystem dynamics of the Amazon rainforest, cerrado, ecotone, and conversion areas. In conclusion, satellite-based, regional scale studies were found to aid in understanding land surface processes and mechanisms at the ecosystem level, providing a "big picture" of landscape dynamics. Coupling this with ground, in-situ measurements, such as from flux towers, can greatly improve the estimation of carbon and water fluxes, and our understanding of the biogeochemistry and climate in very dynamic and changing landscapes.

Ratana, Piyachat

30

Analysis of the Greenland ice sheet elevation time series from satellite altimetry  

NASA Astrophysics Data System (ADS)

Change in surface elevation is an important characteristic of the ice sheet behavior, which is used in mass balance studies. Greenland ice sheet elevation changes were analysed using 20-years (1992-2012) time series derived from ERS-1, ERS-2 and Envisat satellite radar altimeter measurements by crossover method. The methods that allowed improving estimation of the ice sheet elevation changes from satellite radar altimeters were developed and applied. Altimeter measurements from different satellites were merged through determining of spatially variable inter-satellite biases in order to create continuous and consistent time series. Inter-satellite biases of elevation and altimeter waveform parameters have shown to be significantly affected by the bias between measurements in ascending and descending orbits. Distribution of the biases reveals remarkable spatial variability, so their detailed determination is required. Analysis of elevation and backscatter parameter time series indicated significant temporal changes in their sensitivity gradient, which is used for estimation of backscatter correction and correcting of the measured elevation changes to account for penetration of radar altimeter signal in snow. Taking these gradient changes into account results in better correction of seasonal and inter-annual elevation variations. Over whole time period considered elevation increases in the interior of the Greenland ice sheet and significantly decreases over low-elevation areas. At the same time spatio-temporal analysis shows large inter-annual elevation variability over western and south-eastern regions of the ice sheet. In particular, increases in surface elevation from 1995 were followed by an elevation decrease from 2006 caused primarily by the changes over western flank of the ice sheet. Over low-elevation areas below 1500 considerable elevation decrease started from 2000 has continued. Comparison of elevation time series derived using temporally consistent altimeter measurements from Envisat and ICESat satellites provided an assessment of uncertainty of elevation change estimation. Although elevation changes derived from these two satellites are in a reasonable agreement over most part of the Greenland ice sheet, there are large discrepancies in some areas indicating existence of the bias between the results. Both - positive and negative - biases are observed in different areas, and may be resulted either from Envisat measurements due to inaccurate estimation of backscatter correction and slope-induced errors caused by large footprint or from ICESat measurements due to low spatio-temporal data coverage.

Khvorostovsky, Kirill

2013-04-01

31

Consistent Long-Time Series of GPS Satellite Antenna Phase Center Corrections  

NASA Astrophysics Data System (ADS)

The current IGS processing strategy disregards satellite antenna phase center variations (pcvs) depending on the nadir angle and applies block-specific phase center offsets only. However, the transition from relative to absolute receiver antenna corrections presently under discussion necessitates the consideration of satellite antenna pcvs. Moreover, studies of several groups have shown that the offsets are not homogeneous within a satellite block. Manufacturer specifications seem to confirm this assumption. In order to get best possible antenna corrections, consistent ten-year time series (1994-2004) of satellite-specific pcvs and offsets were generated. This challenging effort became possible as part of the reprocessing of a global GPS network currently performed by the Technical Universities of Munich and Dresden. The data of about 160 stations since the official start of the IGS in 1994 have been reprocessed, as today's GPS time series are mostly inhomogeneous and inconsistent due to continuous improvements in the processing strategies and modeling of global GPS solutions. An analysis of the signals contained in the time series of the phase center offsets demonstrates amplitudes on the decimeter level, at least one order of magnitude worse than the desired accuracy. The periods partly arise from the GPS orbit configuration, as the orientation of the orbit planes with regard to the inertial system repeats after about 350 days due to the rotation of the ascending nodes. In addition, the rms values of the X- and Y-offsets show a high correlation with the angle between the orbit plane and the direction to the sun. The time series of the pcvs mainly point at the correlation with the global terrestrial scale. Solutions with relative and absolute phase center corrections, with block- and satellite-specific satellite antenna corrections demonstrate the effect of this parameter group on other global GPS parameters such as the terrestrial scale, station velocities, the geocenter position or the tropospheric delays. Thus, deeper insight into the so-called `Bermuda triangle' of several highly correlated parameters is given.

Steigenberger, P.; Schmid, R.; Rothacher, M.

2004-12-01

32

Measuring vertical deformation in the Seattle, WA urban corridor with satellite radar interferometry time series analysis  

NASA Astrophysics Data System (ADS)

Satellite radar interferometry (InSAR) time series analysis (e.g., Lundgren et al., 2001) can reveal rich patterns of deformation in both time and space. As the technique is sensitive to mm-scale vertical deformation over large and spatially extensive regions, it provides a useful geodetic tool where satellite coverage and radar phase coherence permit. Here we apply InSAR time series techniques based on the Small BAseline Subset Algorithm (SBAS) (Berardino et al., 2002) using data from three satellites (ERS 1, ERS2, and RADARSAT) to the urban corridor between Tacoma, Seattle and Everett, WA, over the time period 1992 - 2007. The target of our work is to better characterize the nature of active faulting and deep-seated landsliding within the densely populated study area. Additionally, we seek to independently quantify how localized short-wavelength deformation is contaminating data collected from the ~ 12 GPS stations in the eastern Puget Sound region. Comparisons of InSAR time series inversions to data from 4 GPS stations temporally and spatially overlapping the available InSAR observations reveal that surface displacement computed from InSAR matches the GPS deformation within the range of error reported for vertical GPS data (~ 4mm). Contemporaneous surface velocity maps generated via linear regression to two independent time series inversions from overlapping ERS satellite tracks 428 and 156 show striking agreement in the pattern of surface velocity, and effectively resolve rates as low as 1 mm/yr. Based on the results of our velocity mapping, we provide new constraints on surface deformation in the Seattle metro region. First, between 1992 and 2007 we document subsidence (~ 1-3 mm/yr) over much of the region characterized by Holocene infilling of the Puget Sound by lahar and floodplain sedimentation. This deformation is consistent with subsidence due to sediment compaction and de-watering. Second, between 1992 and 2007 we document no slow landslide deformation on any of the numerous mapped slide complexes within Seattle. Regions of known active landsliding, such as along Perkins Lane in Seattle, exhibit radar phase de- correlation. These observations are therefore consistent with relatively infrequent and rapid landslide deformation within Seattle. Finally, we note a NW-SE striking, sharp linear gradient in deformation near Federal Way, WA. As this feature is located just north of the Tacoma Fault Zone, it may mark the location of a previously unmapped fault splay that is serving as a barrier to local groundwater flow.

Finnegan, N. J.; Pritchard, M. E.; Lohman, R.; Lundgren, P. R.

2007-12-01

33

MODVOLC2: A Hybrid Time Series Analysis for Detecting Thermal Anomalies Applied to Thermal Infrared Satellite Data  

NASA Astrophysics Data System (ADS)

We developed and tested a new, automated algorithm, MODVOLC2, which analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes, fires, and gas flares. MODVOLC2 combines two previously developed algorithms, a simple point operation algorithm (MODVOLC) and a more complex time series analysis (Robust AVHRR Techniques, or RAT) to overcome the limitations of using each approach alone. MODVOLC2 has four main steps: (1) it uses the original MODVOLC algorithm to process the satellite data on a pixel-by-pixel basis and remove thermal outliers, (2) it uses the remaining data to calculate reference and variability images for each calendar month, (3) it compares the original satellite data and any newly acquired data to the reference images normalized by their variability, and it detects pixels that fall outside the envelope of normal thermal behavior, (4) it adds any pixels detected by MODVOLC to those detected in the time series analysis. Using test sites at Anatahan and Kilauea volcanoes, we show that MODVOLC2 was able to detect ~15% more thermal anomalies than using MODVOLC alone, with very few, if any, known false detections. Using gas flares from the Cantarell oil field in the Gulf of Mexico, we show that MODVOLC2 provided results that were unattainable using a time series-only approach. Some thermal anomalies (e.g., Cantarell oil field flares) are so persistent that an additional, semi-automated 12-µm correction must be applied in order to correctly estimate both the number of anomalies and the total excess radiance being emitted by them. Although all available data should be included to make the best possible reference and variability images necessary for the MODVOLC2, we estimate that at least 80 images per calendar month are required to generate relatively good statistics from which to run MODVOLC2, a condition now globally met by a decade of MODIS observations. We also found that MODVOLC2 achieved good results on multiple sensors (MODIS and GOES), which provides confidence that MODVOLC2 can be run on future instruments regardless of their spatial and temporal resolutions. The improved performance of MODVOLC2 over MODVOLC makes possible the detection of lower temperature thermal anomalies that will be useful in improving our ability to document Earth’s volcanic eruptions as well as detect possible low temperature thermal precursors to larger eruptions.

Koeppen, W. C.; Wright, R.; Pilger, E.

2009-12-01

34

Assessment and surveillance of active seismic regions through time series satellite data  

NASA Astrophysics Data System (ADS)

Satellite time-series data, coupled with ground based observations where available, can enable scientists to survey pre-earthquake signals in the areas of strong tectonic activity. Cumulative stress energy in seismic active regions under operating tectonic force manifests various earthquakes' precursors. Space-time anomalies of Earth's emitted radiation (radon in underground water and soil, thermal infrared in spectral range measured from satellite months to weeks before the occurrence of earthquakes etc.), and electromagnetic anomalies are considered as pre-seismic signals. This energy transformation may result in enhanced transient thermal infrared (TIR) emission, which can be detected through satellites equipped with thermal sensors like AVHRR (NOAA), MODIS (Terra/Aqua). This paper presents observations made using time series NOAA-AVHRR and MODIS satellite data-derived land surface temperature (LST) and outgoing longwave radiation (OLR) values in case of 27th 2004 earthquake recorded in seismic Vrancea region, Romania, using anomalous TIR signals as reflected in LST rise and high OLR values which followed similar growth pattern spatially and temporally. In all analyzed cases, starting with almost one week prior to a moderate or strong earthquake a transient thermal infrared rise in LST of several Celsius degrees (°C) and the increased OLR values higher than the normal have been recorded around epicentral areas, function of the magnitude and focal depth, which disappeared after the main shock. As Vrancea area has a significant regional tectonic activity in Romania and Europe, the joint analysis of geospatial and in-situ geophysical information is revealing new insights in the field of hazard assessment.

Zoran, M. A.; Savastru, R. S.; Savastru, D. M.

2013-08-01

35

MODVOLC2: A Hybrid Time Series Analysis for Detecting Thermal Anomalies Applied to Thermal Infrared Satellite Data  

Microsoft Academic Search

We developed and tested a new, automated algorithm, MODVOLC2, which analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes, fires, and gas flares. MODVOLC2 combines two previously developed algorithms, a simple point operation algorithm (MODVOLC) and a more complex time series analysis (Robust AVHRR Techniques, or RAT)

W. C. Koeppen; R. Wright; E. Pilger

2009-01-01

36

Comparison analysis in growth process in Asian cities by using tandem time series remote sensing of different satellite  

NASA Astrophysics Data System (ADS)

The growth of major cities in Asia, as a consequence of economic development, is feared to have adverse influences on the natural environment of the surrounding areas. Comparison of land cover changes in major cities from the viewpoints of both spatial and time series is necessary to fully understand the characteristics of urban development in Asia. To accomplish this, multiple satellite remote sensing data were analyzed across a wide range and over a long term in this study. The process of transition of a major Asian city in Tokyo, Osaka, Beijing, Shanghai, and Hong Kong was analyzed from the characteristic changes of the vegetation index value and the land cover over about 40 years, from 1972 to 2010. Image data for LANDSAT/MSS, LAND-SAT/TM, ALOS/AVNIR-2, and ALOS/PRISM were obtained using a tandem time series. The ratio and state of detailed distribution of land cover were clarified by the classification processing. The time series clearly showed different change characteristics for each city and its surrounding natural environment of vegetation and forest etc. as a result of development processes.

Hashiba, Hideki; Nakayama, Yasunori; Sugimura, Toshiro

37

MOBY Normalized Water-Leaving Radiance Time-series Uncertainty Reduction for Improved Multi-platform Satellite Sensor Vicarious Calibration  

NASA Astrophysics Data System (ADS)

The Marine Optical Buoy (MOBY), a radiometric buoy stationed in the waters off Lanai, Hawaii, is the primary ocean observatory for vicarious calibration of satellite ocean color sensors. Since late 1996, MOBY has been the primary basis for the on-orbit vicarious calibrations of the USA Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Japanese Ocean Color and Temperature Sensor (OCTS) and Global Imager (GLI), the French Polarization Detection Environmental Radiometer (POLDER), the USA Moderate Resolution Imaging Spectrometers (MODIS, Terra and Aqua), the Japanese Global Imager (GLI), and the European Medium Resolution Imaging Spectrometer (MERIS). The MOBY vicarious calibration of these sensors supports the international effort to develop a global, multi-year time series of consistently calibrated ocean color data products. A longstanding goal of the Ocean Color Science Teams is to determine satellite-derived normalized water-leaving radiance (LWN) with a combined standard uncertainty of 5 percent. A critical component of this approach is to reduce uncertainties in MOBY in situ LWN data. As has been the case since the first MOBY deployment, these improvements are achieved incrementally and from a variety of system aspects. We will discuss these efforts and present results relating to the radiometric calibration, instrument stability during deployments, sensitivity to temperature, stray light corrections, data acquisition protocols, and instrument self shading.

Flora, S.; Brown, S.; Clark, D.; Feinholz, M.; Houlihan, T.; Johnson, C.; Kinkade, K.; Kim, Y.; Koval, L.; Murphy, M.; Ondrusek, O.; Peters, D.; Stengel, E.; Voss, K.; Yarbrough, M.

2007-05-01

38

Space Monitoring of air pollution using satellite time series: from a global view down to local scale  

NASA Astrophysics Data System (ADS)

Assessment of air pollution has been performed by different means over the years and, recently, the use of satellite data for detecting and monitoring atmospheric pollution has received considerable attention especially for application in industrial and urban areas. Methods based on satellite data (such as Landsat TM, SPOT MODIS images) are focused on the estimation of aerosol optical thickness (AOT) that is a measure of aerosol loading in the atmosphere, and therefore, it is considered as the main significant parameter of the presence/absence of atmospheric pollutants. A higher AOT value expresses the degree to which aerosols prevent the transmission of light, therefore, higher columnar of aerosol loading means lower visibility and higher aerosol concentration Several state-of-art aerosol retrieval techniques provide aerosol properties in global scale, as for example products from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Earth Observing System (EOS) Terra and Aqua satellites. The current aerosol optical thickness (AOT) products from MODIS (available free of charge by the NASA web site) is 10 km. This product is suitable for global research, but it faces difficulty in local area research, especially in urban areas However, new aerosol retrieval algorithm for the (MODIS) 500m resolution data have been developed to retrieve aerosol properties over land, which helps on addressing the aerosol climatic issues in local/urban scale. Over the years, several algorithms for determining the aerosol optical thickness have been developed using several approaches and satellite sensors including medium (Landsat; ASTER) and high resolution imagery (IKONOS and Quickbird). A comparison of results from these methods and independent data sets has been performed in the Basilicata region in the framework of the MITRA project (ref). This research activity was conducted in order to analyze their temporal dynamics and reliability for systematically using them in operative applications. Next step of the project is oriented towards the identification, on the basis of satellite time series, of critical levels of the major atmospheric pollutants

Lanorte, Antonio; Aromando, Angelo; Desantis, Fortunato; Lasaponara, Rosa

2013-04-01

39

Circulation in Drake Passage revisited using new current time series and satellite altimetry  

NASA Astrophysics Data System (ADS)

The Drake Passage circulation was examined using in situ velocity time series gathered at five mooring sites across the Yaghan Basin (from January 2006 to March 2009), and at four mooring sites across Ona Basin (from February 2006 to April 2008). The moorings were located under the Jason satellite ground-track #104, allowing precise comparisons with various altimetry products. The mooring data suggested the existence of a permanent strong deep cyclonic circulation in the northeastern part of the Yaghan Basin and in the Ona Basin. The mean velocity vectors were observed to rotate with depth. Rotations of the mean velocity vector with depth indicated consistent downwelling except at the mooring located at 59°S, in the center of the Ona Basin. Temporal scales of variability observed from the mooring data were analyzed and leading modes of variability were discussed. The in situ data provided the first opportunity to compare altimetry-derived velocities with high temporal resolution near-surface current meter velocities in a large eddy kinetic energy environment at high latitudes. Globally, altimetry-derived velocities compared rather well with the in situ velocities at 500 m depth both in strength and direction. Correlations were high between the in situ velocities and the surface velocities derived from satellite altimetric data. The quality of the altimetric surface geostrophic velocities being assessed, altimetry was used to further interpret observations at isolated mooring sites and to put them in context of the 18-year-long altimetric time series. In Yaghan Basin, during the in situ measurement period, the spatial structure of the dominant mode of Mean Sea Level Anomaly was associated to the presence of a strong southward meander of the Subantarctic Front upstream of the mooring section. The 18-year-long altimetry time series revealed that this pattern is robust, dominant and had a strong semi-annual component. Map of Absolute Dynamic Topography-derived velocity across the crest of the Shackleton Ridge, at the western entrance to the Ona Basin, showed that deep gaps in the ridge control the mean location of the Antarctic Circumpolar Current frontal branches. In the complex area where the Shackleton Fracture Zone intersects the West Scotia Ridge, the Map of Absolute Dynamic Topography maps provided an accurate documentation of the meandering of the Polar Front branches around the seamounts, in remarkable agreement with the current meter data. The altimetry helped to put the mooring period into perspective and in particular to show that some of the events sampled during the mooring period were exceptional, such as the invasions of water from south of the southern boundary of the ACC over a large part of the Ona Basin. An active ventilation of the Circumpolar Deep Water by water from the south of the southern boundary of the ACC was shown to be associated with cyclonic eddies and their filaments [Provost et al., 2011].

Ferrari, Ramiro; Prvost, Christine; Sennéchael, Nathalie; Park, Young-Hyang; Lee, Jae Hak

2013-04-01

40

Using satellite time series for remote sensing based investigations of ancient acqueduct systems: the case of the Nasca puquios  

NASA Astrophysics Data System (ADS)

Satellite time series can provide valuable information to reconstruct ancient environmental changes, still fossilized in the present landscape. In particular, satellite derived moisture content and moisture patter variations over the seasons and years may facilitate the identification of areas involved in early environmental manipulation. Up to now, only a few number of archaeological studies on spatial patterns of moisture have been carried out through the world using satellite optical data. We focus on Landsat and ASTER multitemporal data acquired for some areas near Nasca basin (Peru) to extract information on ancient irrigation systems and artificial wet agro-ecosystems. The study area is particularly interesting mainly because it was populated since millennia ago despite its drought and critical environment conditions presented serious obstacles to human occupation. Considering this extreme drought, which characterizes this area today as several centuries ago, ancient populations of the Nasca River valley devised an efficient system for retrieval water and to face the drought conditions. This system was based on underground aqueducts called puquios, which in part are still used today. Archaeological record put in evidence that during the Nasca flourishing period, the number and spatial distribution of puquios were larger than today. On the basis of satellite multitemporal moisture maps, Unknown puquios were identified and confirmed by ground survey. This information can be a basic The successful results achieved in the Nasca Basin area may be also rejoined in similar environmental conditions (in Meso-America, Middle East, North Africa, Asia) where ancient populations devised aqueducts to face drought and retrieve water for domestic, ritual and agricultural needs. Reference Lasaponara R., Masini N., Following the Ancient Nasca Puquios from Space, in Lasaponara R. and Masini N. (Eds), Satellite Remote Sensing: A New Tool for Archaeology (Remote Sensing and Digital Image Processing), Springer, ISBN: 9048188008, pp. 269-290.

Lasaponara, R.; Masini, N.

2012-04-01

41

Development of satellite green vegetation fraction time series for use in mesoscale modeling: application to the European heat wave 2006  

NASA Astrophysics Data System (ADS)

A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution of vegetation. Several high-resolution GVF products, derived from high-quality satellite retrievals from Moderate Resolution Imaging Spectroradiometer images, were produced and their performance was evaluated in long-term WRF simulations. The atmospheric conditions during the 2006 heat wave year over Europe were simulated since significant interannual variability in vegetation seasonality was found. Such interannual variability is expected to increase in the coming decades due to climatic changes. The simulation using a quadratic normalized difference vegetation index to GVF relationship resulted in consistent improvements of modeled temperatures. The model mean temperature cold bias was reduced by 10 % for the whole domain and by 20-45 % in areas affected by the heat wave. The study shows that WRF simulations during heat waves and droughts, when vegetation conditions deviate from the climatology, require concurrent land surface properties in order to produce accurate results.

Refslund, Joakim; Dellwik, Ebba; Hahmann, Andrea N.; Barlage, Michael J.; Boegh, Eva

2013-09-01

42

A snow extent time series assimilation using MODIS images and temperature data, case study Koohrang, Iran  

NASA Astrophysics Data System (ADS)

A unique advantage of satellite data is the possibility for delineation of snow line and calculation of snow cover area. Recent availability of remote sensing data offers promise for better performance of hydrological models, which contain a snow component. The near-daily coverage of Moderate Resolution Imaging Spectrometer (MODIS) data and its moderate resolution provide a powerful capability for time series analysis of snow cover area. However, because of several reasons like cloud cover, technical problems, etc., images are not available or usable. This paper suggests a regional solution to fill the gap of missing data for purpose of snow cover assessment. In this study 27 images of MODIS from NASA have been used to calculate basin scale snow cover area by applying NDSI technique. Also a temperature dataset was collected from the Koohrang station, which was measured by the Iranian meteorological organization for the period 2004-2008. The elevation of the Koohrang station is 2285 m above sea level and geographically it is located at latitude 32 26' and longitude 50 07'. The study considered snow cover derived from satellite imagery as dependent variable and temperature as independent variable. To find a relationship between snow extent and temperature we used the CURVEEXPERT 1.4 package. This program uses the Levenberg-Marquardt algorithm to solve nonlinear regressions by combination of steepest-descent method and a Taylor series technique. Our methodology is applied each time when snow extent is not available and it estimates snow extend based on the remaining data. A wide range of built in models were tested for this purpose but finally a Logistic, Exponential, Richards, Gompertz, Linear Fit and Exponential model were adopted because of high correlation relationship and low variance.

Abdollahi, K.; Batelaan, O.

2012-04-01

43

Time series modeling for an adaptive visibility improvement of the outdoor image sequences in wavelet domain  

Microsoft Academic Search

Under a complex atmosphere, the visibility of images captured by a moving camera needs to be enhanced so as to overcome various atmospheric perturbations. To achieve a stable and robust performance, in this paper, we propose to build a time series based model in wavelet domain by employing both spatial and temporal information of the sequential images. First, we set

Haoting Liu; Hanqing Lu; Fenggang Xu

2009-01-01

44

Selective logging changes forest phenology in the Brazilian Amazon: Evidence from MODIS image time series analysis  

Microsoft Academic Search

We present a large-scale study of the relationships between selective logging and forest phenology in the Brazilian Amazon. Time-series analysis of MODIS satellite data of selectively logged forests in Mato Grosso, Brazil, shows that relatively low levels (5–10%) of canopy damage cause significant and long-lasting (more than 3 years) changes in forest phenology. Partial clearing slows forest green-up in the dry

Alexander Koltunov; Susan L. Ustin; Gregory P. Asner; Inez Fung

2009-01-01

45

Mapping the extent of abandoned farmland in Central and Eastern Europe using MODIS time series satellite data  

NASA Astrophysics Data System (ADS)

The demand for agricultural products continues to grow rapidly, but further agricultural expansion entails substantial environmental costs, making recultivating currently unused farmland an interesting alternative. The collapse of the Soviet Union in 1991 led to widespread abandonment of agricultural lands, but the extent and spatial patterns of abandonment are unclear. We quantified the extent of abandoned farmland, both croplands and pastures, across the region using MODIS NDVI satellite image time series from 2004 to 2006 and support vector machine classifications. Abandoned farmland was widespread, totaling 52.5 Mha, particularly in temperate European Russia (32 Mha), northern and western Ukraine, and Belarus. Differences in abandonment rates among countries were striking, suggesting that institutional and socio-economic factors were more important in determining the amount of abandonment than biophysical conditions. Indeed, much abandoned farmland occurred in areas without major constraints for agriculture. Our map provides a basis for assessing the potential of Central and Eastern Europe’s abandoned agricultural lands to contribute to food or bioenergy production, or carbon storage, as well as the environmental trade-offs and social constraints of recultivation.

Alcantara, Camilo; Kuemmerle, Tobias; Baumann, Matthias; Bragina, Eugenia V.; Griffiths, Patrick; Hostert, Patrick; Knorn, Jan; Müller, Daniel; Prishchepov, Alexander V.; Schierhorn, Florian; Sieber, Anika; Radeloff, Volker C.

2013-09-01

46

Using satellite time-series data sets to analyze fire disturbance and forest recovery across Canada  

Microsoft Academic Search

The boreal forest biome is one of the largest on Earth, covering more than 14% of the total land surface. Fire disturbance plays a dominant role in boreal ecosystems, altering forest succession, biogeochemical cycling, and carbon sequestration. We used two time-series data sets of Advanced Very High Resolution Radiometer (AVHRR) Normalized Differenced Vegetation Index (NDVI) imagery for North America to

Scott J. Goetz; Gregory J. Fiske; Andrew G. Bunn

2006-01-01

47

Consistent Long-Time Series of GPS Satellite Antenna Phase Center Corrections  

Microsoft Academic Search

The current IGS processing strategy disregards satellite antenna phase center variations (pcvs) depending on the nadir angle and applies block-specific phase center offsets only. However, the transition from relative to absolute receiver antenna corrections presently under discussion necessitates the consideration of satellite antenna pcvs. Moreover, studies of several groups have shown that the offsets are not homogeneous within a satellite

P. Steigenberger; R. Schmid; M. Rothacher

2004-01-01

48

On the use of satellite VEGETATION time series for monitoring post fire vegetation recovery  

NASA Astrophysics Data System (ADS)

Fire is one of the most critical factors of disturbance in worldwide ecosystems. The effects of fires on soil, plants, landscape and ecosystems depend on many factors, among them fire frequency, fire severity and plant resistance. The characterization of vegetation post-fire behaviour is a fundamental issue to model and evaluate the fire resilience, which the ability of vegetation to recover after fire. Recent changes in fire regime, due to abandonment of local land use practice and climate change, can induce significant variations in vegetation fire resilience. In the Mediterranean-type communities, post fire vegetation trends have been analysed in a wide range of habitats, although pre- and post-fire investigation has been widely performed at stand level. But, factors controlling regeneration at the landscape scale are less well known. In this study, a time series of normalized difference vegetation index (NDVI) data derived from SPOT-VEGETATION was used to examine the recovery characteristics of fire affected vegetation in some test areas of the Mediterranean ecosystems of Southern Italy. The vegetation indices operate by contrasting intense chlorophyll pigment absorption in the red against the high reflectance of leaf mesophyll in the near infrared. SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) data from 1998 to 2005 were analyzed in order to evaluate the resilient effects in a some significant test sites of southern Italy. In particular, we considered: (i) one stable area site, one site affected by one fire during the investigated time window, (iii) one site affected by two consecutive fires during the investigated time window. In order to eliminate the phenological fluctuations, for each decadal composition of each pixel, we focused on the departure NDVId = [NDVI - ]/?, where is the decadal mean and ? is the decadal standard deviation. The decadal mean and the standard deviation were calculated for each decade, e.g. 1st decade of January, by averaging over all years in the record. We analyzed both: 1) Time variation of NDVI from 1998 to 2005 of pixels for the fire affected and fire unaffected areas. 2) Post-fire NDVI spatial patterns on each image date were compared to the pre-fire pattern to determine the extent to which the pre-fire pattern was re-established, and the rate of this recovery. Results show the ability of vegetation to recovery after a single fire. Nevertheless, such ability can be strongly reduced by successive fires. The recursive fire occurrence can significantly diminish the green biomass especially when disturbances occur at short intervals of time.

de Santis, F.; Didonna, I.

2009-04-01

49

Constraints on surface deformation in the Seattle, WA, urban corridor from satellite radar interferometry time-series analysis  

Microsoft Academic Search

We apply differential InSAR (DInSAR) time-series techniques to the urban corridor between Tacoma, Seattle and Everett, WA, using 93 interferograms from three satellites (ERS 1, ERS 2 and RADARSAT-1) between 1992 and 2007. Our goal is to study local tectonic, geomorphic and groundwater processes. Consequently, we remove long-wavelength (>50-100 km) deformation signals from unwrapped interferograms. By comparing surface velocities generated

Noah J. Finnegan; Mathew E. Pritchard; Rowena B. Lohman; Paul R. Lundgren

2008-01-01

50

De-noising of passive and active microwave satellite soil moisture time series  

NASA Astrophysics Data System (ADS)

Satellite microwave retrievals and in situ measurements of surface soil moisture are usually compared in the time domain. This paper examines their differences in the conjugate frequency domain to develop a spectral description of the satellite data, suggesting the presence of stochastic random and systematic periodic errors. Based on a semiempirical model of the observed power spectral density, we describe systematic designs of causal and noncausal filters to remove these erroneous signals. The filters are applied to the retrievals from active and passive satellite sensors and evaluated against field data from the Murrumbidgee Basin, southeast Australia, to show substantive increase in linear correlations.

Su, Chun-Hsu; Ryu, Dongryeol; Western, Andrew W.; Wagner, Wolfgang

2013-07-01

51

Nonlinear denoising of functional magnetic resonance imaging time series with wavelets  

Microsoft Academic Search

In functional magnetic resonance imaging (fMRI) the blood oxygenation level dependent (BOLD) effect is used to identify and delineate neuronal activity. The sensitivity of a fMRI-based detection of neuronal activation, however, strongly depends on the relative levels of signal and noise in the time series data, and a large number of different artifact and noise sources interfere with the weak

Sven Stausberg; Klaus Lehnertz

2009-01-01

52

Satellite Imaging Corporation: IKONOS Satellite Images  

NSDL National Science Digital Library

Satellite Imaging Corporation (SIC) acquires and processes imagery from the IKONOS satellite as well as others and makes the products available through their website. The images in the gallery are arranged in several categories based on what applications the images might be useful for, such as Agriculture, Coastal Management, or Sports and Tourism.

Corporation, Satellite I.

53

Towards an identification of tumor growth parameters from time series of images.  

PubMed

In cancer treatment, understanding the aggressiveness of the tumor is essential in therapy planning and patient follow-up. In this article, we present a novel method for quantifying the speed of invasion of gliomas in white and grey matter from time series of magnetic resonance (MR) images. The proposed approach is based on mathematical tumor growth models using the reaction-diffusion formalism. The quantification process is formulated by an inverse problem and solved using anisotropic fast marching method yielding an efficient algorithm. It is tested on a few images to get a first proof of concept with promising new results. PMID:18051102

Konukoglu, Ender; Clatz, Olivier; Bondiau, Pierre-Yves; Sermesant, Maxime; Delingette, Hervé; Ayache, Nicholas

2007-01-01

54

Acoustic Imaging Time Series of Plume Behavior at Grotto Vent, Endeavour Observatory, Juan de Fuca Ridge  

NASA Astrophysics Data System (ADS)

A time series (24 hours) of acoustic images record the behavior of the principal buoyant plume (height interval 0-40 m above seafloor) discharging from black smoker chimneys on the north tower of the Grotto Vent sulfide edifice in the Main Endeavour Vent Field. The plume imaging was performed using the Simrad SM2000 sonar system (frequency 200 kHz) mounted on ROV Jason from a fixed position on the seafloor with a nearly horizontal slant range to the vent of about 20 m at a water depth of about 2190 m. The acoustic imaging is based on Rayleigh backscattering from mineral particles suspended in the plume that are small (microns) relative to the wavelength of the acoustic pulse (centimeter) such that intensity of backscatter is proportional to particle load. The acoustic time series data were acquired on 26-27 July 2000 as part of the VIP (Vent Imaging Pacific) 2000 cruise. We applied our computer visualization and quantification methods to reconstruct the plume 3D volume object and to measure dimensions and orientation. Plume expansion with height corresponds to model prediction (diameter 2 to 20 meters). Particle load decreases with height following model predications. The plume centerline constructed by joining the local center of mass of successive horizontal slices with height through the buoyant plume alternately bends between 0 and 30 degrees to the northeast and southwest in a complex cycle. The plume bending appears to correspond to the regional mixed semidiurnal tidal cycle (H. Mofjeld, personal communication), with a component related to a prevailing northeasterly current (R. Thomson, personal communication). The effectiveness of tracking plume behavior for this short time series shows the potential of the acoustic method for long-term monitoring of the activity and interactions of plumes in seafloor hydrothermal fields.

Rona, P. A.; Bemis, K. G.; Jackson, D. R.; Jones, C. D.; Mitsuzawa, K.; Palmer, D. R.; Silver, D.

2001-12-01

55

Removing Noise From Satellite Time Series Data Significantly Improves Terrestrial Carbon Cycle Model Performance  

NASA Astrophysics Data System (ADS)

Changes in leaf area that occur over time periods of days have large effects on terrestrial ecosystem carbon cycle model estimates of regional carbon exchange. High frequency changes in leaf area index (LAI) over large regions are obtained by MODIS satellite observations. Currently available MODIS LAI observations contain significant amounts of gaps and noise due to less than optimal atmospheric conditions for making measurements. Carbon cycle model simulations using the LoTEC model at several AmeriFlux sites show sensitivity to this noise that affects the amount of growth respiration and results in poor seasonal representation of measure net ecosystem CO2 exchange (NEE). Spatially gap-filled smoothed LAI data were processed with two steps. First, TIMESAT Asymmetric Gauss (AG) approach was used to generate smoothed LAI data and phenology parameters from standard MODIS LAI product (8-day composite in 1-km resolution). Second, spatial gaps were filled by adjusting temporal curve of high quality neighbor pixel of same land cover type from MODIS land cover products using high quality LAI values from current pixel. Use of this spatially gap-filled smoothed LAI greatly improved LoTEC carbon cycle model representation of carbon NEE at selected AmeriFlux sites.

Post, W. M.; Gao, F.; Wolfe, R. E.; Morisette, J. T.; King, A. W.

2006-12-01

56

Towards comprehensive quality controlled time series of in situ SSTs for calibration and validation of satellite retrievals  

NASA Astrophysics Data System (ADS)

In situ measurements of bulk sea surface temperatures (SST) have been historically made from the drifting and moored buoys and ships. In recent decades, a number of successful remotely sensed SST products have been introduced. Customarily, the in situ bulk SST is considered a standard to calibrate and validate the satellite SST retrievals. The volume of in situ SST measurements has dramatically increased since the onset of satellite SST era, and their coverage and quality have improved. The remote sensing techniques have also quickly evolved to a number of matured and accurate SST products with accuracies approaching or even exceeding that of buoy and ship SST. It is imperative that the available records of in situ bulk SSTs are systematized and quality controlled (QC) for use in the satellite SST analyses. The accuracies and information content of the in situ SSTs should be quantified and stratified by data source (drifting vs. moored buoys, ships), country of origin, types of sensors used, etc. The objective is to generate long-term time series of QCed in situ SSTs to be used in conjunction with the operational retrievals and historical reprocessing of the satellite SSTs. This study explores the available ground-based SST data in the satellite era (ca. 1970-on). The emphasis is on their long-term consistency and improved QC through comparison with SST climatologies and exploring spatial and temporal context (in particular, an attempt is made to separate the diurnal signal from noise). Addressing these science issues will contribute towards improved calibration and validation of the current, historical and future SST environmental and climate data records.

Ignatov, A.; Ivanova, D.; Kihai, Y.

2006-05-01

57

Utilizing a Multi-sensor Satellite Time Series in Real-time Drought Monitoring Across the United States  

NASA Astrophysics Data System (ADS)

Drought events frequently occur in the United States and result in billions of dollars of damage, often exceeding the costs of other weather-related hazards. Monitoring drought conditions is a necessary function of government agencies at State, Federal, and local levels as part of decision support for planning, risk management, and hazard mitigation activities. In partnership with the National Drought Mitigation Center, the National Aeronautics and Space Administration, the U.S. Department of Agriculture Risk Management Agency, and the High Plains Regional Climate Center, the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center is developing an operational drought decision support tool with relatively higher spatial resolution (1 km2) than traditional drought monitoring maps. The Vegetation Drought Response Index (VegDRI) is a geospatial model that integrates in-situ climate, satellite, and biophysical data, providing an indicator of canopy vegetation condition (or stress). The satellite data ingested into VegDRI are collected from daily polar-orbiting earth observing systems including the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS). These instruments provide regular synoptic measurements of land surface conditions in near-real time. In VegDRI, remote sensing data provide proxy information about the vegetation status (or health) related to climate-induced changes and are integrated with traditional drought indices based on in-situ climate observations. When merged, the two complementary sources of drought-related data provide a comprehensive and detailed picture of drought impacts across the landscape. A 20-year history of AVHRR time-series data produced over the U.S. at a 1 km2 resolution provides a historical context for monitoring drought conditions. However, the MODIS instrument has improved sensor characteristics designed for land surface monitoring. To seamlessly extend the multi-sensor NDVI data record, inter-sensor NDVI continuity/compatibility has been examined and appropriate adjustments, or multi- sensor translations, have been made to datasets by means of cross-calibration. The data translation equations were derived from an overlapping period of observations with geometric mean regressions to treat variations in both AVHRR and MODIS datasets equally. Since standard MODIS products are often not delivered quickly enough to aid operational decisions, USGS has designed a system based on a direct broadcast model called eMODIS. The eMODIS system at EROS provides the near-real time MODIS vegetation index data needed to supply VegDRI products on a schedule that meets the needs of the U.S. drought monitoring community, largely driven by the U.S. Drought Monitor and the National Integrated Drought Information System. The requirements of the community include providing synoptic indicators in a timely fashion and in an easy-to-interpret format for incorporation into the weekly U.S. Drought Monitor map process.

Brown, J. F.; Miura, T.; Gu, Y.; Jenkerson, C.; Wardlow, B.

2009-05-01

58

Constraints on surface deformation in the Seattle, WA, urban corridor from satellite radar interferometry time-series analysis  

NASA Astrophysics Data System (ADS)

We apply differential InSAR (DInSAR) time-series techniques to the urban corridor between Tacoma, Seattle and Everett, WA, using 93 interferograms from three satellites (ERS 1, ERS 2 and RADARSAT-1) between 1992 and 2007. Our goal is to study local tectonic, geomorphic and groundwater processes. Consequently, we remove long-wavelength (>50-100 km) deformation signals from unwrapped interferograms. By comparing surface velocities generated via the time-series technique at more than two million points within the overlapping region between two independent ERS tracks, we estimate the uncertainty of relative surface velocity measurements to be ~0.5 mm yr-1 in the vertical. We estimate the uncertainty of relative displacement measurements to be ~5.4 mm, given our comparisons of DInSAR-derived time-series to GPS data, a result that is consistent both with previous DInSAR time-series analysis and with the uncertainty expected from GPS displacements projected onto the radar line-of-sight. Active tectonic deformation at shallow depths on the region's numerous east-west structures is absent over the ~11.5 yr of SAR data examined. Assuming that the south-dipping thrust beneath Seattle and Tacoma takes up 3 mm yr-1 of north-south shortening, our data indicate that the fault must be currently locked to a depth of greater than 10 km. We also document extensive groundwater-related deformation throughout much of the study region. Most notably, we identify sharp, linear deformation gradients near Federal Way, WA, and running between Sumner, WA, and Steilacoom, WA. These features may mark the locations of previously unmapped fault splays that locally control groundwater movement. We find no slow landslide deformation on any of the numerous mapped slide complexes within Seattle, although regions of known active landsliding, such as along Perkins Lane in Seattle, exhibit radar phase de-correlation. These observations are consistent with relatively infrequent and rapid landslide deformation within Seattle.

Finnegan, Noah J.; Pritchard, Mathew E.; Lohman, Rowena B.; Lundgren, Paul R.

2008-07-01

59

Comparison of absolute and relative radiometric normalization use Landsat time series images  

NASA Astrophysics Data System (ADS)

For most remote sense image applications, variations in solar illumination conditions, atmospheric scattering and absorption, and detector performance need to be normalized, especially in time series analysis such as change detection. For the purpose of radiometric correction, two levels of radiometric correction, absolute and relative, have been developed for remote sense imagery. In this paper, we select the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm as the Atmospheric correction method, and compare it with an automatic method for relative radiometric normalization based on a linear scale invariance of the multivariate alteration detection (MAD) transformation. The performances of both methods are compared using a landsat TM image pairs, the results from the two techniques have been compared both visually and using a measure of the fit based on standard error statistic.

Hu, Yong; Liu, Liangyun; Liu, Lingling; Jiao, Quanjun

2011-11-01

60

Circulation in Drake Passage revisited using new current time series and satellite altimetry: 2. The Ona Basin  

NASA Astrophysics Data System (ADS)

Abstract<span class="hlt">Time</span> <span class="hlt">series</span> of horizontal velocities were obtained at four mooring sites across the Ona Basin, southern Drake Passage, during 26 months (February 2006 to April 2008). The moorings were located under the Jason <span class="hlt">satellite</span> ground-track #104, allowing precise comparisons with various other altimetry products. Velocities as high as 0.5 m s-1 at 500 m depth were observed during current pulses. Mean velocity amplitudes at 500 m reached 0.22 m s-1 at 58.5°S and 0.15 m s-1 at 60°S, but were smaller at 59°S and 60.5°S. Mean velocities at 2500 m depth varied between 0.05 and 0.10 m s-1 and were westward on two of the moorings, suggesting recirculation in the center of the basin. Mean velocities were consistent with a general cyclonic circulation in the Ona Basin. The mean velocity vectors were observed to rotate with depth, the sense of rotation depending upon mooring sites. Standard deviation ellipses were close to circular except on the continental slope (60.5°S) where they were stretched in the direction of isobaths. The southernmost mooring was under sea ice in winter, and velocity variations were reduced in amplitude during that period. The horizontal velocities were highly coherent in the vertical. Altimetrically derived surface geostrophic velocities compared well with the in situ velocities and were used to investigate further the flow over the West Scotia Ridge and in the center of the Ona Basin to the East of the highest part of the Shackleton Ridge, which provides some shelter from the eastward flowing Antarctic Circumpolar Current.</p> <div class="credits"> <p class="dwt_author">Ferrari, Ramiro; Provost, Christine; SennéChael, Nathalie; Lee, Jae-Hak</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" 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onClick='return showDiv("page_22");' href="#">22</a> <a onClick='return showDiv("page_23");' href="#">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_5");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">61</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1615012"> <span id="translatedtitle">Description of shapes in CT <span class="hlt">images</span>. The usefulness of <span class="hlt">time-series</span> modeling techniques for identifying organs</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The usefulness of two <span class="hlt">time-series</span> modeling techniques (autoregressive (AR) modeling and complex autoregressive (CAR) modeling) are investigated for shape description of substructures in CT <span class="hlt">images</span>. For this purpose, the organ to be identified is separated from the section of a CT <span class="hlt">image</span> by applying edge detection followed by edge linking, and the boundary of the substructure is extracted in terms</p> <div class="credits"> <p class="dwt_author">A. H. Mir; M. Hanmandlu; S. N. Tandon</p> <p class="dwt_publisher"></p> <p class="publishDate">1999-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">62</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50090040"> <span id="translatedtitle">An iterative technique to determine the near surface current velocity from <span class="hlt">time</span> <span class="hlt">series</span> of sea surface <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> of spatial wave <span class="hlt">images</span> recorded from a nautical radar are transformed with a fast Fourier transformation to the wavenumber frequency domain resulting in a three dimensional <span class="hlt">image</span> power spectrum. The spectral energy is localized on a shell defined by the surface wave dispersion relation. The sum of the sensor's velocity and the near surface current profile deforms the</p> <div class="credits"> <p class="dwt_author">Christian M. Senet; Jorg Seemann; F. Ziemer</p> <p class="dwt_publisher"></p> <p class="publishDate">1997-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">63</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.9577N"> <span id="translatedtitle">Monitoring urban development using <span class="hlt">satellite</span> <span class="hlt">time</span> <span class="hlt">series</span> data and GIS technologies: a case study of Vienna 1986-2011</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The spatial and temporal distribution of urban areas is a fundamental information for a series of applications such as land management, future urban planning, ecology and others. This project deals with a classification approach for the area of Vienna during the time from 1986 to 2011 using Landsat 5 TM datasets. <span class="hlt">Time</span> <span class="hlt">series</span> of Landsat 5 TM data were downloaded and pre-processed. To minimize the effect of vegetation phenology and sun illumination geometry, Landsat 5 TM acquisitions were limited to a specific time window (June-July). Due to the high amount of data collected an automated approach was necessary. Conventional supervised classification algorithms based only on spectral features were not successful in differentiating urban areas from bare soils due to similarities in the spectral reflectance. To further distinguish these two land cover types their attributes in texture were used. Urban areas showed a high variance in texture data within a uniform reference unit whereas agricultural or bare soil fields demonstrated a very uniform distribution of texture value. For the textural analysis a new pixel value was assigned dependent on the spectral differences of each pixel concerning its neighbouring pixels. The textural analysis was included as an additional feature within the Landsat 5 TM dataset. Furthermore it was evaluated which combination of bands (spectral and textural) was best to discriminate above mentioned areas. These bands were then used for a supervised classification. The distribution of vegetation land cover was calculated and an accuracy assessment was performed based on an independent data set derived from the visual interpretation of high resolution <span class="hlt">images</span> and ancillary information. Furthermore, a GIS analysis was carried out to evaluate the expansions (in space and time) of the Vienna urban area for each municipality. Preliminary results are presented and discussed.</p> <div class="credits"> <p class="dwt_author">Neugebauer, N.; Vuolo, F.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">64</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50860938"> <span id="translatedtitle">Examining change and long-term trends in the marine environment using <span class="hlt">satellite</span>-based <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The oceans and coastal areas are dynamic environments in which variability occurs at a wide range of temporal scales, from seconds to years to decades and longer. Some very good <span class="hlt">time</span> <span class="hlt">series</span> now exist at specific locations, that permit characterization of this variability as well as of longer-term trends, but for much of the world ocean the in situ data</p> <div class="credits"> <p class="dwt_author">G. A. Borstad; L. N. Brown; D. B. Fissel</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">65</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ssec.wisc.edu/data/volcano.html"> <span id="translatedtitle">Volcano Watch <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">The University of Wisconsin's Space Science and Engineering Center displays these <span class="hlt">satellite</span> <span class="hlt">images</span> of the world's ten most active volcanoes. Users can view <span class="hlt">images</span> of the Colima Volcano in Central Mexico or Mount Etna in Sicily, Italy. The latest <span class="hlt">images</span> are updated every half-hour. Also, a Java animation feature splices together the last four <span class="hlt">images</span> to show a simulation over a two-hour period.</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">66</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/39663884"> <span id="translatedtitle">Trend analysis of air temperature <span class="hlt">time</span> <span class="hlt">series</span> in Greece and their relationship with circulation using surface and <span class="hlt">satellite</span> data: 1955–2001</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Summary In this study, trends of annual and seasonal surface air temperature <span class="hlt">time</span> <span class="hlt">series</span> were examined for 20 stations in Greece for the period 1955–2001, and <span class="hlt">satellite</span> data for the period 1980–2001. Two statistical tests based on the least square method and one based on the Mann-Kendall test, which is also capable of detecting the starting year of possible climatic</p> <div class="credits"> <p class="dwt_author">H. Feidas; T. Makrogiannis; E. Bora-Senta</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">67</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/70028278"> <span id="translatedtitle">A 16-year <span class="hlt">time</span> <span class="hlt">series</span> of 1 km AVHRR <span class="hlt">satellite</span> data of the conterminous United States and Alaska</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">The U.S. Geological Survey (USGS) has developed a 16-year <span class="hlt">time</span> <span class="hlt">series</span> of vegetation condition information for the conterminous United States and, Alaska using 1 km Advanced Very High Resolution Radiometer (AVHRR) data. The AVHRR data have been processed using consistent methods that account for radiometric variability due to calibration uncertainty, the effects of the atmosphere on surface radiometric measurements obtained from wide field-of-view observations, and the geometric registration accuracy. The conterminous United States and Alaska data sets have an atmospheric correction for water vapor, ozone, and Rayleigh scattering and include a cloud mask derived using the Clouds from AVHRR (CLAVR) algorithm. In comparison with other AVHRR <span class="hlt">time</span> <span class="hlt">series</span> data sets, the conterminous United States and Alaska data are processed using similar techniques. The primary difference is that the conterminous United States and Alaska data are at 1 km resolution, while others are at 8 km resolution. The <span class="hlt">time</span> <span class="hlt">series</span> consists of weekly and biweekly maximum normalized difference vegetation index (NDVI) composites. ?? 2006 American Society for Photogrammetry and Remote Sensing.</p> <div class="credits"> <p class="dwt_author">Eldenshink, J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">68</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010EGUGA..1214986B"> <span id="translatedtitle">The <span class="hlt">Time</span> <span class="hlt">Series</span> Toolbox</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Many applications commonly used in sensor service networks operate on the same type of data repeatedly over time. This kind of data is most naturally represented in the form of "<span class="hlt">time</span> <span class="hlt">series</span>". In its simplest form, a <span class="hlt">time</span> <span class="hlt">series</span> may consist of a single floating point number (e.g. temperature), that is recorded at regular intervals. More complex forms of <span class="hlt">time</span> <span class="hlt">series</span> include <span class="hlt">time</span> <span class="hlt">series</span> of complex observations (e.g. aggregations of related measurements, spectra, 2D coverages/<span class="hlt">images</span>, ...), and <span class="hlt">time</span> <span class="hlt">series</span> recorded at irregular intervals. In addition, the <span class="hlt">time</span> <span class="hlt">series</span> may contain meta-information describing e.g. the provenance, uncertainty, and reliability of observations. The <span class="hlt">Time</span> <span class="hlt">Series</span> Toolbox (TS Toolbox) provides a set of software components and application programming interfaces that simplify recording, storage, processing and publishing of <span class="hlt">time</span> <span class="hlt">series</span>. This includes (1) "data connector" components implementing access to data using various protocols and data formats; (2) core components interfacing with the connector components and providing specific additional functionalities like data processing or caching; and (3) front-end components implementing interface functionality (user interfaces or software interfaces). The functionalities implemented by TS Toolbox components provide application developers with higher-level building blocks than typical general purpose libraries, and allow rapid development of fully fledged applications. The TS Toolbox also includes example applications that can be either used as they are, or as a basis for developing more complex applications. The TS-Toolbox, which was initially developed by the Austrian Institute of Technology in the scope of SANY "Sensors Anywhere", is written in Java, published under the terms of the GPL, and available for download on the SANY web site.</p> <div class="credits"> <p class="dwt_author">Boži?, Bojan; Havlik, Denis</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">69</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://school.discovery.com/lessonplans/programs/satelliteimages/index.html"> <span id="translatedtitle">Reading <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">This lesson plan is part of the DiscoverySchool.com lesson plan library for grades 6-8. It focuses on <span class="hlt">satellite</span> <span class="hlt">images</span> and how they are made by active, passive, and remote-sensing instruments. Students analyze <span class="hlt">satellite</span> <span class="hlt">images</span> and answer questions about them. Included are objectives, materials, procedures, discussion questions, evaluation ideas, suggested readings, and vocabulary. There are videos available to order which complement this lesson, an audio-enhanced vocabulary list, and links to teaching tools for making custom quizzes, worksheets, puzzles and lesson plans.</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">70</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.nasa.gov/multimedia/imagegallery/image_feature_1649.html"> <span id="translatedtitle">Oil Slick <span class="hlt">Satellite</span> <span class="hlt">Image</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">NASA Aqua <span class="hlt">Satellite</span> <span class="hlt">image</span>, captured on April 25, 2010, of an oil slick caused by the April 20, 2010 explosion and sinking of the Deepwater Horizon oil platform in the Gulf of Mexico off the coasts of Louisiana, Alabama, and Florida.</p> <div class="credits"> <p class="dwt_author">Nasa</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-04-27</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">71</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50462951"> <span id="translatedtitle"><span class="hlt">Time-Series</span> <span class="hlt">Imaging</span> of Ocean Waves with an Airborne RGB and NIR Sensor</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Measurements from the Airborne Remote Optical Spotlight System (AROSS), an airborne, panchromatic, <span class="hlt">imaging</span> system, have been used to successfully produce frequency-wavenumber spectra of shoaling ocean waves. The fidelity and quality of the spectra have enabled accurate retrievals of water depths, currents, and surf characteristics and these results have been reported in previous publications. A next-generation system, based on AROSS, has</p> <div class="credits"> <p class="dwt_author">B. A. Hooper; J. Z. Williams; J. P. Dugan; C. Goldman; M. Yi; D. Campion</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">72</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2848603"> <span id="translatedtitle">A Quantitative <span class="hlt">Image</span> Cytometry Technique for <span class="hlt">Time</span> <span class="hlt">Series</span> or Population Analyses of Signaling Networks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Background Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. Methodology/Principal Findings We developed a fully automatable assay technique, termed quantitative <span class="hlt">image</span> cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision <span class="hlt">image</span>-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. Conclusions/Significance The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell <span class="hlt">imaging</span>. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.</p> <div class="credits"> <p class="dwt_author">Ozaki, Yu-ichi; Uda, Shinsuke; Saito, Takeshi H.; Chung, Jaehoon; Kubota, Hiroyuki; Kuroda, Shinya</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">73</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AIPC.1559...80H"> <span id="translatedtitle">Measure the change of vessel edges across <span class="hlt">time</span> <span class="hlt">series</span> retinal <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The measure of the retinal vessel diameter change reflects the vessel wall change which may be caused by a certain disease or physiological abnormality. There is no established method to measure the changes of the vessel edges across multiple retinal <span class="hlt">images</span> over time. In this paper, we propose two methods to monitor the longitudinal change along the retinal vessel wall: 1) monitoring the change of the fixed points on the edges; and 2) calculating the change of the diameters vertical to the vessel direction. This paper will determine the proper method for the future analysis of the retinal pulsation and the longitudinal change along the retinal vessel wall. The comparison of the two methods shows that both methods can be used if the purpose is only to assess the difference of the vessel edges over time when the real value of the vessel diameter is not considered. Otherwise, centerline vertical diameter is complying more with the standard practice.</p> <div class="credits"> <p class="dwt_author">Hao, Hao; Kumar, Dinesh Kant; Aliahmad, Behzad</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">74</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3527382"> <span id="translatedtitle">Modelling Temporal Stability of EPI <span class="hlt">Time</span> <span class="hlt">Series</span> Using Magnitude <span class="hlt">Images</span> Acquired with Multi-Channel Receiver Coils</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">In 2001, Krueger and Glover introduced a model describing the temporal SNR (tSNR) of an EPI <span class="hlt">time</span> <span class="hlt">series</span> as a function of <span class="hlt">image</span> SNR (SNR0). This model has been used to study physiological noise in fMRI, to optimize fMRI acquisition parameters, and to estimate maximum attainable tSNR for a given set of MR <span class="hlt">image</span> acquisition and processing parameters. In its current form, this noise model requires the accurate estimation of <span class="hlt">image</span> SNR. For multi-channel receiver coils, this is not straightforward because it requires export and reconstruction of large amounts of k-space raw data and detailed, custom-made <span class="hlt">image</span> reconstruction methods. Here we present a simple extension to the model that allows characterization of the temporal noise properties of EPI <span class="hlt">time</span> <span class="hlt">series</span> acquired with multi-channel receiver coils, and reconstructed with standard root-sum-of-squares combination, without the need for raw data or custom-made <span class="hlt">image</span> reconstruction. The proposed extended model includes an additional parameter ? which reflects the impact of noise correlations between receiver channels on the data and scales an apparent <span class="hlt">image</span> SNR (SNR?0) measured directly from root-sum-of-squares reconstructed magnitude <span class="hlt">images</span> so that ??=?SNR?0/SNR0 (under the condition of SNR0>50 and number of channels ?32). Using Monte Carlo simulations we show that the extended model parameters can be estimated with high accuracy. The estimation of the parameter ? was validated using an independent measure of the actual SNR0 for non-accelerated phantom data acquired at 3T with a 32-channel receiver coil. We also demonstrate that compared to the original model the extended model results in an improved fit to human task-free non-accelerated fMRI data acquired at 7T with a 24-channel receiver coil. In particular, the extended model improves the prediction of low to medium tSNR values and so can play an important role in the optimization of high-resolution fMRI experiments at lower SNR levels.</p> <div class="credits"> <p class="dwt_author">Hutton, Chloe; Balteau, Evelyne; Lutti, Antoine; Josephs, Oliver; Weiskopf, Nikolaus</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">75</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2006AGUFMIN33B1341P"> <span id="translatedtitle">Remote Sensing <span class="hlt">Time</span> <span class="hlt">Series</span> Product Tool</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The TSPT (<span class="hlt">Time</span> <span class="hlt">Series</span> Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination <span class="hlt">time</span> <span class="hlt">series</span>, such as NDVI (Normalized Difference Vegetation Index) <span class="hlt">images</span>, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB®, allows users to create and display various MODIS (Moderate Resolution <span class="hlt">Imaging</span> Spectroradiometer) or simulated VIIRS (Visible/Infrared <span class="hlt">Imager</span> Radiometer Suite) products as single <span class="hlt">images</span>, as <span class="hlt">time</span> <span class="hlt">series</span> plots at a selected location, or as temporally processed <span class="hlt">image</span> videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate <span class="hlt">satellite</span> imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua <span class="hlt">satellites</span>, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise <span class="hlt">time</span> <span class="hlt">series</span> plots and <span class="hlt">image</span> videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting "what-if" scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or <span class="hlt">images</span>. This type of <span class="hlt">time</span> <span class="hlt">series</span> analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI <span class="hlt">time</span> <span class="hlt">series</span> over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.</p> <div class="credits"> <p class="dwt_author">Prados, D.; Ryan, R. E.; Ross, K. W.</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">76</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011SPIE.8059E..14P"> <span id="translatedtitle"><span class="hlt">Image</span> sets for <span class="hlt">satellite</span> <span class="hlt">image</span> processing systems</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The development of novel <span class="hlt">image</span> processing algorithms requires a diverse and relevant set of training <span class="hlt">images</span> to ensure the general applicability of such algorithms for their required tasks. <span class="hlt">Images</span> must be appropriately chosen for the algorithm's intended applications. <span class="hlt">Image</span> processing algorithms often employ the discrete wavelet transform (DWT) algorithm to provide efficient compression and near-perfect reconstruction of <span class="hlt">image</span> data. Defense applications often require the transmission of <span class="hlt">images</span> and video across noisy or low-bandwidth channels. Unfortunately, the DWT algorithm's performance deteriorates in the presence of noise. Evolutionary algorithms are often able to train <span class="hlt">image</span> filters that outperform DWT filters in noisy environments. Here, we present and evaluate two <span class="hlt">image</span> sets suitable for the training of such filters for <span class="hlt">satellite</span> and unmanned aerial vehicle imagery applications. We demonstrate the use of the first <span class="hlt">image</span> set as a training platform for evolutionary algorithms that optimize discrete wavelet transform (DWT)-based <span class="hlt">image</span> transform filters for <span class="hlt">satellite</span> <span class="hlt">image</span> compression. We evaluate the suitability of each <span class="hlt">image</span> as a training <span class="hlt">image</span> during optimization. Each <span class="hlt">image</span> is ranked according to its suitability as a training <span class="hlt">image</span> and its difficulty as a test <span class="hlt">image</span>. The second <span class="hlt">image</span> set provides a test-bed for holdout validation of trained <span class="hlt">image</span> filters. These <span class="hlt">images</span> are used to independently verify that trained filters will provide strong performance on unseen <span class="hlt">satellite</span> <span class="hlt">images</span>. Collectively, these <span class="hlt">image</span> sets are suitable for the development of <span class="hlt">image</span> processing algorithms for <span class="hlt">satellite</span> and reconnaissance imagery applications.</p> <div class="credits"> <p class="dwt_author">Peterson, Michael R.; Horner, Toby; Temple, Asael</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">77</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/42529919"> <span id="translatedtitle">Modelling uncertainty of a land management map derived from a <span class="hlt">time</span> <span class="hlt">series</span> of <span class="hlt">satellite</span> <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The agricultural management practice of leaving land fallow during winter is a key pressure on ground water quality in Canterbury, New Zealand. This is because any nitrate present is likely to be leached down through the soil profile since there is no plant uptake. Remote sensing imagery has been successfully used to identify land with low potential for nitrate uptake</p> <div class="credits"> <p class="dwt_author">L. R. Lilburne; H. C. North</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">78</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005PhDT.......167D"> <span id="translatedtitle">A statistical framework for the analysis of long <span class="hlt">image</span> <span class="hlt">time</span> <span class="hlt">series</span>: The effect of anthropogenic change on land surface phenology</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Significant global changes affect the carbon and water cycles as well as the biodiversity on earth. Mapping and monitoring these changes can aid in the understanding and distinction between anthropogenic and biophysical impacts on the land surface. In the context of scientific and social debate on the pace and extent of global climate change, it is extremely important to have methods that are capable of distinguishing between expected variability and significant change. In this dissertation I have presented a statistical framework for the analysis of long <span class="hlt">image</span> <span class="hlt">time</span> <span class="hlt">series</span> that consists of robust techniques for step change analysis, temporal trend analysis, and the modeling of land surface phenology (LSP) and analysis of LSP change. This framework helps to fill a gap in the remote sensing literature on appropriate approaches to quantitative change analysis. I have described two main application areas for the statistical framework: (1) Quality analysis of NOAA AVHRR NDVI datasets. The analysis of more than 2 million km2 of desert and semi-desert ecoregions in Central Asia revealed significant sensor artifacts in the Pathfinder AVHRR Land (PAL) NDVI dataset. I have found that the comparison of data from any combination of NOAA-7, NOAA-9 and NOAA-14 can be used for land surface change analyses, but that the inclusion of NOAH-11 AVHRR NDVI data in trend analyses may result in the detection of spurious trends. Furthermore, I have shown that two versions of NOAA AVHRR NDVI datasets with similar characteristics can yield very different conclusions on land surface change. (2) Using the PAL NDVI data, I applied the framework to address the question of whether the institutional changes accompanying the collapse of the Soviet Union resulted in significant changes in land surface phenologies across Northern Eurasia and Kazakhstan in particular. Using multiple lines of evidence provided by the statistical framework, I was able to distinguish between anthropogenic impacts and interannual climatic fluctuations on the land surface phenology.</p> <div class="credits"> <p class="dwt_author">de Beurs, Kirsten M.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">79</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012atph.book..433M"> <span id="translatedtitle">Contrail Detection in <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Methods for detecting linear contrail pixels in <span class="hlt">satellite</span> infrared <span class="hlt">images</span> are described. An objective contrail detection algorithm has been developed and extensively applied to data from various polar and geostationary <span class="hlt">satellite</span> sensors. The method uses the contrast in brightness temperatures near 11 and 12 ?m wavelengths and detects linear contrails using <span class="hlt">image</span> processing techniques. The paper discusses the development of the algorithms, detection efficiency, false alarm rate, some of the results, and their validation. The contrail detection algorithm detects only a fraction of all contrail cirrus. Progress is expected from combining spatiotemporal <span class="hlt">satellite</span> data in correlation with traffic and meteorological data.</p> <div class="credits"> <p class="dwt_author">Mannstein, Hermann; Vázquez-Navarro, Margarita; Graf, Kaspar; Duda, David P.; Schumann, Ulrich</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">80</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.satimagingcorp.com/svc/hurricane_mitigation.html"> <span id="translatedtitle"><span class="hlt">Satellite</span> <span class="hlt">Imaging</span> Corporation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary"><span class="hlt">Satellite</span> imagery and aerial photography incorporated with geographic information systems GIS can give coastal resource managers and emergency officials a wealth of information for assessment analysis and monitoring of natural disasters such as hurricane,s tornadoes and cyclone damage from small to large regions around the globe.</p> <div class="credits"> <p class="dwt_author">Romeijn, Monique; Corporation, Satellite I.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" 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onClick='return showDiv("page_22");' href="#">22</a> <a onClick='return showDiv("page_23");' href="#">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_6");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">81</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://robjhyndman.com/TSDL/"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> Data Library</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">This is a collection of <span class="hlt">time</span> <span class="hlt">series</span> datasets covering many application areas, but are all for <span class="hlt">time</span> <span class="hlt">series</span> analysis. Some of the topics covered are: agriculture, chemistry, crime, demography, ecology, finance, health, hydrology, industry, labor market, macroeconomics, physics, production, sales, sport, transportation, tourism, tree rings and utilities. The data are in text format, thus they can be used without any additional software.</p> <div class="credits"> <p class="dwt_author">Hyndman, Robert</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-08-13</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">82</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://ww2010.atmos.uiuc.edu/(Gh)/guides/rs/sat/img/ir.rxml"> <span id="translatedtitle">Infrared <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">This site from the University of Illinois presents an explanation of how infrared <span class="hlt">imaging</span> provides information about clouds. <span class="hlt">Images</span> and commentary show how altitude, temperature, and humidity can be inferred from the infrared <span class="hlt">images</span>. The site also contains links to descriptions of other kinds of remote sensing.</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate">2008-03-28</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">83</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50342002"> <span id="translatedtitle">Improved estimates of the terrestrial carbon cycle by coupling of a process-based global vegetation model (LPJ-DGVM) with a 17-year <span class="hlt">time</span> <span class="hlt">series</span> of <span class="hlt">satellite</span>-observed fPAR data (AVHRR)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Coupling of a state-of-the-art Dynamic Global Vegetation Model (LPJ-DGVM) with a 17-year <span class="hlt">time</span> <span class="hlt">series</span> of fPAR data (AVHRR) allows improved derivation of important global carbon cycle parameters such as global net primary production (NPP), heterotrophic respiration (Rh) and net ecosystem exchange (NEE) by combining <span class="hlt">satellite</span> observations with the process knowledge encoded in the model. Global net primary production is estimated</p> <div class="credits"> <p class="dwt_author">B. E. Schroder; W. Lucht</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">84</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/5368721"> <span id="translatedtitle"><span class="hlt">Satellite</span> imagery meets prepress - Producing <span class="hlt">image</span> maps</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary"><span class="hlt">Satellite</span> imagery provided by Landsat, SPOT, AVHRR, and ERS-1 is being exploited for production of <span class="hlt">satellite</span> <span class="hlt">image</span> maps which incorporate <span class="hlt">images</span>. <span class="hlt">Satellite</span> <span class="hlt">image</span> maps produced by transforming digital imagery acquired by spaceborn platforms into lithographic printed maps are used in two primary areas: large scale orthophoto maps for the engineering and construction industries and small-scale <span class="hlt">satellite</span> <span class="hlt">image</span> maps for the military and environmental resource organizations.</p> <div class="credits"> <p class="dwt_author">Audrain, V.; Fehrenbach, J.; Reading, M.; Stauffer, R. (Intergraph Corp., Huntsville, AL (United States))</p> <p class="dwt_publisher"></p> <p class="publishDate">1993-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">85</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/r0726646326tt500.pdf"> <span id="translatedtitle">Finding similar <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Similarity of objects is one of the crucial concepts in several applications, including data mining. For complex objects, similarity is nontrivial to define. In this paper we present an intuitive model for measuring the similarity between two <span class="hlt">time</span> <span class="hlt">series</span>. The model takes into account outliers, different scaling functions, and variable sampling rates. Using methods from computational geometry, we show that</p> <div class="credits"> <p class="dwt_author">Gautam Das; Dimitrios Gunopulos; Heikki Mannila</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">86</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/43559586"> <span id="translatedtitle">Unsupervised Land Cover Change Detection: Meaningful Sequential <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">An automated land cover change detection method is proposed that uses coarse spatial resolution hyper-temporal earth observation <span class="hlt">satellite</span> <span class="hlt">time</span> <span class="hlt">series</span> data. The study compared three different unsupervised clustering approaches that operate on short term Fourier transform coefficients computed over subsequences of 8-day composite MODerate-resolution <span class="hlt">Imaging</span> Spectroradiometer (MODIS) surface reflectance data that were extracted with a temporal sliding window. The method</p> <div class="credits"> <p class="dwt_author">Brian P. Salmon; Jan Corne Olivier; Konrad J. Wessels; Waldo Kleynhans; Frans van den Bergh; Karen C. Steenkamp</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">87</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/x51380754235612k.pdf"> <span id="translatedtitle">Modelling Financial <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Financial <span class="hlt">time</span> <span class="hlt">series</span>, in general, exhibit average behaviour at “long” time scales and stochastic behaviour at ‘short” time\\u000a scales. As in statistical physics, the two have to be modelled using different approaches — deterministic for trends and probabilistic\\u000a for fluctuations about the trend. In this talk, we will describe a new wavelet based approach to separate the trend from the</p> <div class="credits"> <p class="dwt_author">P. Manimaran; J. C. Parikh; P. K. Panigrahi; S. Basu; C. M. Kishtawal; M. B. Porecha</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">88</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011JARS....5a3525C"> <span id="translatedtitle">Wavelet filtering of <span class="hlt">time-series</span> moderate resolution <span class="hlt">imaging</span> spectroradiometer data for rice crop mapping using support vector machines and maximum likelihood classifier</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Rice is the most important economic crop in Vietnam's Mekong Delta (MD). It is the main source of employment and income for rural people in this region. Yearly estimates of rice growing areas and delineation of spatial distribution of rice crops are needed to devise agricultural economic plans and to ensure security of the food supply. The main objective of this study is to map rice cropping systems with respect to monitoring agricultural practices in the MD using <span class="hlt">time-series</span> moderate resolution <span class="hlt">imaging</span> spectroradiometer (MODIS) normalized difference vegetation index (NDVI) 250-m data. These <span class="hlt">time-series</span> NDVI data were derived from the 8-day MODIS 250-m data acquired in 2008. Various spatial and nonspatial data were also used for accuracy verification. The method used in this study consists of the following three main steps: 1. filtering noise from the <span class="hlt">time-series</span> NDVI data using wavelet transformation (Coiflet 4); 2. classification of rice cropping systems using parametric and nonparametric classification algorithms: the maximum likelihood classifier (MLC) and support vector machines (SVMs); and 3. verification of classification results using ground truth data and government rice statistics. Good results can be found using wavelet transformation for cleaning rice signatures. The results of classification accuracy assessment showed that the SVMs outperformed the MLC. The overall accuracy and Kappa coefficient achieved by the SVMs were 89.7% and 0.86, respectively, while those achieved by the MLC were 76.2% and 0.68, respectively. Comparison of the MODIS-derived areas obtained by the SVMs with the government rice statistics at the provincial level also demonstrated that the results achieved by the SVMs (R2 = 0.95) were better than the MLC (R2 = 0.91). This study demonstrates the effectiveness of using a nonparametric classification algorithm (SVMs) and <span class="hlt">time-series</span> MODIS NVDI data for rice crop mapping in the Vietnamese MD.</p> <div class="credits"> <p class="dwt_author">Chen, Chi-Farn; Son, Nguyen-Thanh; Chen, Cheng-Ru; Chang, Ly-Yu</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">89</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008AGUFM.B31D0312W"> <span id="translatedtitle">Analysis of Forest Fire Disturbance in the Western United States Using Landsat <span class="hlt">Time</span> <span class="hlt">Series</span> <span class="hlt">Images</span>: 1985 to 2005</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this study we used two different disturbance maps (both utilizing 30 m resolution Landsat imagery) to assess disturbance trends in Western US forests. The first are maps developed by the NAFD project (North American Forest Dynamics). Each NAFD data cube contains an annual-biennial record of forest disturbance events from 1984-2005. We complimented the NAFD maps with MTBS maps (Monitoring Trends in Burn Severity). MTBS solely maps fire disturbance, recording historical (1985-2005) and contemporary burn severity and fire perimeter across the United States. We used Landsat <span class="hlt">time</span> <span class="hlt">series</span> stacks for four locations: Oregon (Landsat path 45 row 29), California (p43r33), Idaho (p41r29), and Utah (p32r37). In all four stacks, fire was a relatively small percentage of the total forest disturbance (ranging from 8% in Utah to 27% in Oregon for the entire 20 year period). We also found that the years with greatest burned area were years with a high aridity index (lower precipitation and higher temperatures), a condition necessary, but not sufficient for fire activity. To assess post-disturbance vegetation regrowth we used two spectral indices, the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR). Both indices are sensitive to well-defined spectral paths that forests follow during and after disturbance. As expected, NDVI and NBR were lowest (highest) for the highest (lowest) severity class burned area. However, NBR and NDVI only appear to respond to vegetative reflectance in the first decade after a burn. Therefore, they give useful information on location, timing, and magnitude of disturbance, but direct measurement of biomass with other sensors would be necessary to obtain additional ecological information.</p> <div class="credits"> <p class="dwt_author">Wicklein, H. F.; Collatz, G. J.; Masek, J.; Williams, C.</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">90</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23277606"> <span id="translatedtitle">Random <span class="hlt">time</span> <span class="hlt">series</span> in astronomy.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Progress in astronomy comes from interpreting the signals encoded in the light received from distant objects: the distribution of light over the sky (<span class="hlt">images</span>), over photon wavelength (spectrum), over polarization angle and over time (usually called light curves by astronomers). In the time domain, we see transient events such as supernovae, gamma-ray bursts and other powerful explosions; we see periodic phenomena such as the orbits of planets around nearby stars, radio pulsars and pulsations of stars in nearby galaxies; and we see persistent aperiodic variations ('noise') from powerful systems such as accreting black holes. I review just a few of the recent and future challenges in the burgeoning area of time domain astrophysics, with particular attention to persistently variable sources, the recovery of reliable noise power spectra from sparsely sampled <span class="hlt">time</span> <span class="hlt">series</span>, higher order properties of accreting black holes, and time delays and correlations in multi-variate <span class="hlt">time</span> <span class="hlt">series</span>. PMID:23277606</p> <div class="credits"> <p class="dwt_author">Vaughan, Simon</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-12-31</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">91</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/48712351"> <span id="translatedtitle"><span class="hlt">Time-Series</span> Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">\\u000a <span class="hlt">Time-series</span> analysis aims to investigate the temporal behavior of one of several variables x(t). Examples include the investigation of long-term records of mountain uplift , sea-level fluctuations, orbitally-induced\\u000a insolation variations and their influence on the ice-age cycles, millenium-scale variations in the atmosphere-ocean system,\\u000a the effect of the El Niño\\/Southern Oscillation on tropical rainfall and sedimentation (Fig. 5.1) and tidal influences</p> <div class="credits"> <p class="dwt_author">Martin H. Trauth</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">92</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2004ntsa.book.....K"> <span id="translatedtitle">Nonlinear <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The time variability of many natural and social phenomena is not well described by standard methods of data analysis. However, nonlinear <span class="hlt">time</span> <span class="hlt">series</span> analysis uses chaos theory and nonlinear dynamics to understand seemingly unpredictable behavior. The results are applied to real data from physics, biology, medicine, and engineering in this volume. Researchers from all experimental disciplines, including physics, the life sciences, and the economy, will find the work helpful in the analysis of real world systems. First Edition Hb (1997): 0-521-55144-7 First Edition Pb (1997): 0-521-65387-8</p> <div class="credits"> <p class="dwt_author">Kantz, Holger; Schreiber, Thomas</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">93</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012amld.book..617L"> <span id="translatedtitle">Pattern Recognition in <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Perhaps the most commonly encountered data types are <span class="hlt">time</span> <span class="hlt">series</span>, touching almost every aspect of human life, including astronomy. One obvious problem of handling <span class="hlt">time-series</span> databases concerns with its typically massive size—gigabytes or even terabytes are common, with more and more databases reaching the petabyte scale. For example, in telecommunication, large companies like AT&T produce several hundred millions long-distance records per day [Cort00]. In astronomy, time-domain surveys are relatively new—these are surveys that cover a significant fraction of the sky with many repeat observations, thereby producing <span class="hlt">time</span> <span class="hlt">series</span> for millions or billions of objects. Several such time-domain sky surveys are now completed, such as the MACHO [Alco01],OGLE [Szym05], SDSS Stripe 82 [Bram08], SuperMACHO [Garg08], and Berkeley’s Transients Classification Pipeline (TCP) [Star08] projects. The Pan-STARRS project is an active sky survey—it began in 2010, a 3-year survey covering three-fourths of the sky with ˜60 observations of each field [Kais04]. The Large Synoptic Survey Telescope (LSST) project proposes to survey 50% of the visible sky repeatedly approximately 1000 times over a 10-year period, creating a 100-petabyte <span class="hlt">image</span> archive and a 20-petabyte science database (http://www.lsst.org/). The LSST science database will include <span class="hlt">time</span> <span class="hlt">series</span> of over 100 scientific parameters for each of approximately 50 billion astronomical sources—this will be the largest data collection (and certainly the largest <span class="hlt">time</span> <span class="hlt">series</span> database) ever assembled in astronomy, and it rivals any other discipline’s massive data collections for sheer size and complexity. More common in astronomy are <span class="hlt">time</span> <span class="hlt">series</span> of flux measurements. As a consequence of many decades of observations (and in some cases, hundreds of years), a large variety of flux variations have been detected in astronomical objects, including periodic variations (e.g., pulsating stars, rotators, pulsars, eclipsing binaries, planetary transits), quasi-periodic variations (e.g., star spots, neutron star oscillations, active galactic nuclei), outburst events (e.g., accretion binaries, cataclysmic variable stars, symbiotic stars), transient events (e.g., gamma-ray bursts (GRB), flare stars, novae, supernovae (SNe)), stochastic variations (e.g., quasars, cosmic rays, luminous blue variables (LBVs)), and random events with precisely predictable patterns (e.g., microlensing events). Several such astrophysical phenomena are wavelength-specific cases, or were discovered as a result of wavelength-specific flux variations, such as soft gamma ray repeaters, x-ray binaries, radio pulsars, and gravitational waves. Despite the wealth of discoveries in this space of time variability, there is still a vast unexplored region, especially at low flux levels and short time scales (see also the chapter by Bloom and Richards in this book). Figure 28.1 illustrates the gap in astronomical knowledge in this time-domain space. The LSST project aims to explore phenomena in the time gap. In addition to flux-based <span class="hlt">time</span> <span class="hlt">series</span>, astronomical data also include motion-based <span class="hlt">time</span> <span class="hlt">series</span>. These include the trajectories of planets, comets, and asteroids in the Solar System, the motions of stars around the massive black hole at the center of the Milky Way galaxy, and the motion of gas filaments in the interstellar medium (e.g., expanding supernova blast wave shells). In most cases, the motions measured in the <span class="hlt">time</span> <span class="hlt">series</span> correspond to the actual changing positions of the objects being studied. In other cases, the detected motions indirectly reflect other changes in the astronomical phenomenon, such as light echoes reflecting across vast gas and dust clouds, or propagating waves.</p> <div class="credits"> <p class="dwt_author">Lin, Jessica; Williamson, Sheri; Borne, Kirk D.; DeBarr, David</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-03-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">94</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010OptEn..49i7007L"> <span id="translatedtitle">Simulation scheme of dusk scene using piece-wise multiple regression based on <span class="hlt">time-series</span> color-block <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Dusk and dawn are usually the most beautiful moments of the day, and are almost always too short for busy people nowadays to witness their coming. In this work, an efficient strategy for simulating a dusk scene of an outdoor scene <span class="hlt">image</span> taken at other times before the sunset is presented. The strategy is a hybrid approach combining the piece-wise multiple regression (PMR) of data, discrete cosine transformation (DCT), and a look-up table algorithm. The process begins using a series of color-block <span class="hlt">images</span> taken in the afternoon of a day. The best fitting functions of PMR for these color block <span class="hlt">images</span> exist on separate planes (red, green, and blue) in the DCT domain individually. The reference databases of the DCT coefficients varying with respect to time are then established according to the best fitting functions of PMR. Finally, the dusk scene of an outdoor scene taken in the afternoon is synthesized by querying the reference database. The experiment results show that the presented algorithm can precisely simulate the desired dusk scene from a scene <span class="hlt">image</span> taken in the afternoon.</p> <div class="credits"> <p class="dwt_author">Liu, Chen-Chung; Yang, Chih-Chao</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">95</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51414264"> <span id="translatedtitle">Observing Changes of Surface Solar Irradiance in Oregon: A Comparison of <span class="hlt">Satellite</span> and Ground-Based Long-Term <span class="hlt">Time-Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Significant increases over time are found in direct normal irradiance (DNI) in Oregon using both ground and <span class="hlt">satellite</span>-derived measurements of DNI. Linear regression of all locations in both data sets shows strong positive trends of .4% to .6% per year. Ground measurements are analyzed from 1980 (and at one site from 1978) until 2004. These 25 years of ground measurements</p> <div class="credits"> <p class="dwt_author">L. D. Riihimaki; F. E. Vignola; S. Lohmann; R. Meyer</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">96</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/56927834"> <span id="translatedtitle">TIALA — <span class="hlt">Time</span> <span class="hlt">series</span> alignment analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The analysis of <span class="hlt">time</span> <span class="hlt">series</span> expression data is widely employed for investigating biological mechanisms. Microarrays are often used to generate <span class="hlt">time</span> <span class="hlt">series</span> for several different experimental conditions. These <span class="hlt">time</span> <span class="hlt">series</span> then need to be compared to each other. For a successful comparison it is necessary to perform a <span class="hlt">time</span> <span class="hlt">series</span> alignment because the experiments can differ in the number of</p> <div class="credits"> <p class="dwt_author">Gunter Jager; Florian Battke; Kay Nieselt</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">97</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/t320760u95343765.pdf"> <span id="translatedtitle">From Depth Scale to Time Scale: Transforming Sediment <span class="hlt">Image</span> Color Data into a High-Resolution <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">High-resolution time-scales are important for the precise correlation of spatially distributed geological records, and further development of process-oriented models used to predict climate change and other terrestrial processes. The extraction of digital line-scan data from <span class="hlt">images</span> of laminated sediments provides a tool for the rapid and non-invasive analysis of sedimentary records, including sediment and ice cores, and tree ring growth</p> <div class="credits"> <p class="dwt_author">Andreas Prokoph; R. Patterson</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">98</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010EGUGA..1212335P"> <span id="translatedtitle">Geomatics techniques applied to <span class="hlt">time</span> <span class="hlt">series</span> of aerial <span class="hlt">images</span> for multitemporal geomorphological analysis of the Miage Glacier (Mont Blanc).</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The Miage glacier is the major one in the Italian side of the Mont Blanc Massif, the third by area and the first by longitudinal extent among Italian glaciers. It is a typical debris covered glacier, since the end of the L.I.A. The debris coverage reduces ablation, allowing a relative stability of the glacier terminus, which is characterized by a wide and articulated moraine apparatus. For its conservative landforms, the Miage Glacier has a great importance for the analysis of the geomorphological response to recent climatic changes. Thanks to an organized existing archive of multitemporal aerial <span class="hlt">images</span> (1935 to present) a photogrammetric approach has been applied to detect recent geomorphological changes in the Miage glacial basin. The research team provided: a) to digitize all the available <span class="hlt">images</span> (still in analogic form) through photogrammetric scanners (very low <span class="hlt">image</span> distortions devices) taking care of correctly defining the resolution of the acquisition compared to the scale mapping <span class="hlt">images</span> are suitable for; b) to import digitized <span class="hlt">images</span> into an appropriate digital photogrammetry software environment; c) to manage <span class="hlt">images</span> in order, where possible, to carried out the stereo models orientation necessary for 3D navigation and plotting of critical geometric features of the glacier. Recognized geometric feature, referring to different periods, can be transferred to vector layers and imported in a GIS for further comparisons and investigations; d) to produce multi-temporal Digital Elevation Models for glacier volume changes; e) to perform orthoprojection of such <span class="hlt">images</span> to obtain multitemporal orthoimages useful for areal an planar terrain evaluation and thematic analysis; f) to evaluate both planimetric positioning and height determination accuracies reachable through the photogrammetric process. Users have to known reliability of the measures they can do over such products. This can drive them to define the applicable field of this approach and this can help them to better program future flights for glacier survey; All produced data, differently from the original ones, can be considered as map products. All of them represent geocoded entity and maps that can be easily imported in a GIS for assessment and management. The operational workflow allowed to the definition of changes occurred over the Miage glacier area and to the interpretation of related significant geomorphological processes. Particular attention has been paid to the identification of changes in the debris cove pattern, to the differences calculation of glacial mass volumes, to the natural instability phenomena (landslides, debris flows, glacier lakes). Short-term climate trend has been evoked to the glacial expansion of mid 1980s quantified by remote sensing interpretation; contemporary activation of local glacial risks on the outer moraines has been mapped too. Glacial mass contraction of 1990-2000 has been traced and repeated rock falls accumulation over the Miage Glacier have been individualized. Later differential uplifts and subsidences of glacier topography have been interpreted as local intense differential ablation processes, recently associated to ephemeral epiglacial lakes formation.</p> <div class="credits"> <p class="dwt_author">Perotti, Luigi; Carletti, Roberto; Giardino, Marco; Mortara, Giovanni</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">99</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013NJPh...15j3023V"> <span id="translatedtitle">Modelling bursty <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Many human-related activities show power-law decaying interevent time distribution with exponents usually varying between 1 and 2. We study a simple task-queuing model, which produces bursty <span class="hlt">time</span> <span class="hlt">series</span> due to the non-trivial dynamics of the task list. The model is characterized by a priority distribution as an input parameter, which describes the choice procedure from the list. We give exact results on the asymptotic behaviour of the model and we show that the interevent time distribution is power-law decaying for any kind of input distributions that remain normalizable in the infinite list limit, with exponents tunable between 1 and 2. The model satisfies a scaling law between the exponents of interevent time distribution (?) and autocorrelation function (?): ? + ? = 2. This law is general for renewal processes with power-law decaying interevent time distribution. We conclude that slowly decaying autocorrelation function indicates long-range dependence only if the scaling law is violated.</p> <div class="credits"> <p class="dwt_author">Vajna, Szabolcs; Tóth, Bálint; Kertész, János</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">100</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010EGUGA..1210939D"> <span id="translatedtitle">Estimating the solar meridional flow by normal mode decomposition of long <span class="hlt">time</span> <span class="hlt">series</span> of Doppler <span class="hlt">imaging</span> data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Although investigations have been carried out for many decades the solar magnetic cycle is not yet understood in all its basic properties and it still is one of the main research foci of today's solar physics. An important ingredient to most dynamic dynamo models is the solar meridional flow; on the surface of each hemisphere, a polewards flow in the order of 10 - 20 m/s can be measured with different techniques. From mass conservation, one expects a much slower equatorwards return-flow in deeper layers of the solar convection zone which reaches down to about 200 mega meters below the surface. Numerous attempts have been made to derive the depth profile of the flow using a variety of helioseismic techniques (e.g. Giles, P.M., 2000). While most results agree well about the horizontal velocity structures in the upper 20 Mm, sometimes contrary findings have been published for the lower parts of the convection zone. We use a Fourier-Legendre decomposition of the surface wave field generated by the solar normal modes into directly opposed travelling wave fields, corresponding a modification of a method suggested earlier by Braun & Fan (1998). The partition allows for the estimation of the frequency difference, caused by the horizontal meridional flow between waves that propagate polewards and equatorwards respectively. These frequency shifts are used to determine the meridional flow profile as a function of depth and latitude by a SOLA (Subtractive Optimally Localized Averaging) inversion method. Because low-degree modes penetrate deeper into the solar interior than high-degree modes, decomposing the seismic wave field within large patches on the solar surface allows to probe a large fraction of the solar convection zone for the average meridional flow. Smaller patches allow us to study the latitudinal dependence of the flow in higher layers and also a direct comparison of our findings with other methods like ring-diagram analysis. For our analysis, we use Doppler <span class="hlt">imaging</span> data provided by the ground based instruments of the GONG (Global Oscillation Network Group) network as well as from the MDI (Michelson Doppler <span class="hlt">Imager</span>) instrument aboard the SOHO (Solar and Heliospheric Observatory) spacecraft. Both observatories now provide data spanning about one decade and thus allow us to study the variation with time of the meridional flow during the past solar cycle. Beside a short but broad overview about the significance of the meridional flow for modelling the solar internal processes, several new results of the ongoing analysis are presented. We are able to extend the seismic probing of the solar interior beyond those shallow regions that were accessible to other methods.</p> <div class="credits"> <p class="dwt_author">Doerr, Hans-Peter; Roth, Markus; Krieger, Lars</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-05-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_4");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" 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id="NextPageLink" onclick='return showDiv("page_7");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">101</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005AGUFM.A43D0126R"> <span id="translatedtitle">Observing Changes of Surface Solar Irradiance in Oregon: A Comparison of <span class="hlt">Satellite</span> and Ground-Based Long-Term <span class="hlt">Time-Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Significant increases over time are found in direct normal irradiance (DNI) in Oregon using both ground and <span class="hlt">satellite</span>-derived measurements of DNI. Linear regression of all locations in both data sets shows strong positive trends of .4% to .6% per year. Ground measurements are analyzed from 1980 (and at one site from 1978) until 2004. These 25 years of ground measurements come from three climatically diverse sites in the state of Oregon using an Eppley Normal Incidence Pyrheliometer (NIP). The NIP is a good candidate for long term trend analysis as its responsivity remains consistent over time. The sensitivity of the Eppley Precision Spectral Pyranometer (PSP) which measures total radiation, on the other hand, degrades over time, approximately .5% to 2% per year. This uniquely long data set is compared to DNI calculated from the International <span class="hlt">Satellite</span> Cloud Climatology Project (ISCCP). The ISCCP D series applied here has 280 km x 280 km boxes, each of which includes one of the ground based sites, giving cloud and atmospheric input data from 1983 until 2001. Radiative transfer calculations are done using the two-stream method from the library for radiative transfer (libRadtran). The three hourly <span class="hlt">satellite</span> observations allow comparison of different time integration periods. Besides annual average comparisons, monthly averages are examined to look for seasonal variation and confirm that the observations show a regional trend. Ground measurements of DNI for this length of time are rare, making this study a unique opportunity to test the capability to calculate direct normal irradiance based on ISCCP results. The agreement of the ISCCP derived irradiances to the measurements is very good: the trends differ between .08 and .3 W/m{2 depending on the site. From 1998 through 2002 <span class="hlt">satellite</span> data were used to produce a solar radiation database on a 0.1i° grid. Comparisons between the modeled beam irradiance for the coordinates of the ground based station will be compared to the average for the area of the ISCCP grid to check how representative each ground site is of the ISCCP box. The successful verification of ISCCP for this application at three independent sites in this region allows us to use this approach to also analyze similar changes over other regions. Comparing these two methods of obtaining direct irradiance also provides valuable information about the sources of seasonal and inter-annual changes in cloud cover and other atmospheric constituents.</p> <div class="credits"> <p class="dwt_author">Riihimaki, L. D.; Vignola, F. E.; Lohmann, S.; Meyer, R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">102</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009EGUGA..1112071R"> <span id="translatedtitle">Large scale variability, long-term trends and extreme events in total ozone over the northern mid-latitudes based on <span class="hlt">satellite</span> <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Various generations of <span class="hlt">satellites</span> (e.g. TOMS, GOME, OMI) made spatial datasets of column ozone available to the scientific community. This study has a special focus on column ozone over the northern mid-latitudes. Tools from geostatistics and extreme value theory are applied to analyze variability, long-term trends and frequency distributions of extreme events in total ozone. In a recent case study (Rieder et al., 2009) new tools from extreme value theory (Coles, 2001; Ribatet, 2007) have been applied to the world's longest total ozone record from Arosa, Switzerland (e.g. Staehelin 1998a,b), in order to describe extreme events in low and high total ozone. Within the current study this analysis is extended to <span class="hlt">satellite</span> datasets for the northern mid-latitudes. Further special emphasis is given on patterns and spatial correlations and the influence of changes in atmospheric dynamics (e.g. tropospheric and lower stratospheric pressure systems) on column ozone. References: Coles, S.: An Introduction to Statistical Modeling of Extreme Values, Springer Series in Statistics, ISBN:1852334592, Springer, Berlin, 2001. Ribatet, M.: POT: Modelling peaks over a threshold, R News, 7, 34-36, 2007. Rieder, H.E., Staehelin, J., Maeder, J.A., Ribatet, M., Stübi, R., Weihs, P., Holawe, F., Peter, T., and Davison, A.C.: From ozone mini holes and mini highs towards extreme value theory: New insights from extreme events and non stationarity, submitted to J. Geophys. Res., 2009. Staehelin, J., Kegel, R., and Harris, N. R.: Trend analysis of the homogenized total ozone series of Arosa (Switzerland), 1929-1996, J. Geophys. Res., 103(D7), 8389-8400, doi:10.1029/97JD03650, 1998a. Staehelin, J., Renaud, A., Bader, J., McPeters, R., Viatte, P., Hoegger, B., Bugnion, V., Giroud, M., and Schill, H.: Total ozone series at Arosa (Switzerland): Homogenization and data comparison, J. Geophys. Res., 103(D5), 5827-5842, doi:10.1029/97JD02402, 1998b.</p> <div class="credits"> <p class="dwt_author">Rieder, H. E.; Staehelin, J.; Maeder, J. A.; Ribatet, M.; Davison, A. C.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">103</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/55039407"> <span id="translatedtitle">Analysis of astronomical <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents basic concepts of <span class="hlt">time</span> <span class="hlt">series</span> analysis (TSA), emphasizes statistical aspects of TSA, and reviews available TSA tools, particularly those with applications in astronomy. The importance of statistical principles in evaluation of <span class="hlt">time</span> <span class="hlt">series</span> in astronomical practice is discussed. The author draws attention to the distortions in the analysis of <span class="hlt">time</span> <span class="hlt">series</span>, their causes, effects and possible cures.</p> <div class="credits"> <p class="dwt_author">A. Schwarzenberg-Czerny</p> <p class="dwt_publisher"></p> <p class="publishDate">1993-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">104</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005SPIE.5750..153S"> <span id="translatedtitle">User-guided automated segmentation of <span class="hlt">time-series</span> ultrasound <span class="hlt">images</span> for measuring vasoreactivity of the brachial artery induced by flow mediation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Endothelial dysfunction in response to vasoactive stimuli is closely associated with diseases such as atherosclerosis, hypertension and congestive heart failure. The current method of using ultrasound to <span class="hlt">image</span> the brachial artery along the longitudinal axis is insensitive for measuring the small vasodilatation that occurs in response to flow mediation. The goal of this study is to overcome this limitation by using cross-sectional <span class="hlt">imaging</span> of the brachial artery in conjunction with the User-Guided Automated Boundary Detection (UGABD) algorithm for extracting arterial boundaries. High-resolution ultrasound <span class="hlt">imaging</span> was performed on rigid plastic tubing, on elastic rubber tubing phantoms with steady and pulsatile flow, and on the brachial artery of a healthy volunteer undergoing reactive hyperemia. The area of cross section of <span class="hlt">time-series</span> <span class="hlt">images</span> was analyzed by UGABD by propagating the boundary from one frame to the next. The UGABD results were compared by linear correlation with those obtained by manual tracing. UGABD measured the cross-sectional area of the phantom tubing to within 5% of the true area. The algorithm correctly detected pulsatile vasomotion in phantoms and in the brachial artery. A comparison of area measurements made using UGABD with those made by manual tracings yielded a correlation of 0.9 and 0.8 for phantoms and arteries, respectively. The peak vasodilatation due to reactive hyperemia was two orders of magnitude greater in pixel count than that measured by longitudinal <span class="hlt">imaging</span>. Cross-sectional <span class="hlt">imaging</span> is more sensitive than longitudinal <span class="hlt">imaging</span> for measuring flow-mediated dilatation of brachial artery, and thus may be more suitable for evaluating endothelial dysfunction.</p> <div class="credits"> <p class="dwt_author">Sehgal, Chandra M.; Kao, Yen H.; Cary, Ted W.; Arger, Peter H.; Mohler, Emile R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">105</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23102373"> <span id="translatedtitle">From networks to <span class="hlt">time</span> <span class="hlt">series</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">In this Letter, we propose a framework to transform a complex network to a <span class="hlt">time</span> <span class="hlt">series</span>. The transformation from complex networks to <span class="hlt">time</span> <span class="hlt">series</span> is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic <span class="hlt">time</span> <span class="hlt">series</span>, small-world networks to noisy periodic <span class="hlt">time</span> <span class="hlt">series</span>, and random networks to random <span class="hlt">time</span> <span class="hlt">series</span>. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices. PMID:23102373</p> <div class="credits"> <p class="dwt_author">Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-10-10</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">106</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012PhRvL.109o8701S"> <span id="translatedtitle">From Networks to <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this Letter, we propose a framework to transform a complex network to a <span class="hlt">time</span> <span class="hlt">series</span>. The transformation from complex networks to <span class="hlt">time</span> <span class="hlt">series</span> is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic <span class="hlt">time</span> <span class="hlt">series</span>, small-world networks to noisy periodic <span class="hlt">time</span> <span class="hlt">series</span>, and random networks to random <span class="hlt">time</span> <span class="hlt">series</span>. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices.</p> <div class="credits"> <p class="dwt_author">Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">107</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013AIPC.1558.2237N"> <span id="translatedtitle"><span class="hlt">Satellite</span> <span class="hlt">image</span> classification using convolutional learning</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A <span class="hlt">satellite</span> <span class="hlt">image</span> classification method using Convolutional Neural Network (CNN) architecture is proposed in this paper. As a special case of deep learning, CNN classifies classes of <span class="hlt">images</span> without any feature extraction step while other existing classification methods utilize rather complex feature extraction processes. Experiments on a set of <span class="hlt">satellite</span> <span class="hlt">image</span> data and the preliminary results show that the proposed classification method can be a promising alternative over existing feature extraction-based schemes in terms of classification accuracy and classification speed.</p> <div class="credits"> <p class="dwt_author">Nguyen, Thao; Han, Jiho; Park, Dong-Chul</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">108</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50804216"> <span id="translatedtitle"><span class="hlt">Satellite</span> Cloud <span class="hlt">Image</span> Enhancement by Genetic Algorithm with Fuzzy Technique</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In order to efficiently enhance contrast of the <span class="hlt">satellite</span> cloud <span class="hlt">image</span>, an efficient <span class="hlt">satellite</span> cloud <span class="hlt">image</span> enhancing method is proposed. Most of existing <span class="hlt">satellite</span> cloud <span class="hlt">image</span> enhancing methods do not consider uncertainties of the <span class="hlt">image</span>, that is to say, fuzziness in the <span class="hlt">satellite</span> cloud <span class="hlt">image</span> processing. A new kind of <span class="hlt">image</span> measure function is proposed by combing fuzzy theory with</p> <div class="credits"> <p class="dwt_author">Changjiang Zhang; Juan Lu</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">109</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005SPIE.5909..391A"> <span id="translatedtitle">Applications based on restored <span class="hlt">satellite</span> <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Satellites</span> orbit the earth and obtain imagery of the ground below. The quality of <span class="hlt">satellite</span> <span class="hlt">images</span> is affected by the properties of the atmospheric <span class="hlt">imaging</span> path, which degrade the <span class="hlt">image</span> by blurring it and reducing its contrast. Applications involving <span class="hlt">satellite</span> <span class="hlt">images</span> are many and varied. <span class="hlt">Imaging</span> systems are also different technologically and in their physical and optical characteristics such as sensor types, resolution, field of view (FOV), spectral range of the acquiring channels - from the visible to the thermal IR (TIR), platforms (mobilization facilities; aircrafts and/or spacecrafts), altitude above ground surface etc. It is important to obtain good quality <span class="hlt">satellite</span> <span class="hlt">images</span> because of the variety of applications based on them. The more qualitative is the recorded <span class="hlt">image</span>, the more information is yielded from the <span class="hlt">image</span>. The restoration process is conditioned by gathering much data about the atmospheric medium and its characterization. In return, there is a contribution to the applications based on those restorations i.e., <span class="hlt">satellite</span> communication, warfare against long distance missiles, geographical aspects, agricultural aspects, economical aspects, intelligence, security, military, etc. Several manners to use restored Landsat 7 enhanced thematic mapper plus (ETM+) <span class="hlt">satellite</span> <span class="hlt">images</span> are suggested and presented here. In particular, using the restoration results for few potential geographical applications such as color classification and mapping (roads and streets localization) methods.</p> <div class="credits"> <p class="dwt_author">Arbel, D.; Levin, S.; Nir, M.; Bhasteker, I.</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">110</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/854980"> <span id="translatedtitle">Sequoia 2000 metadata schema for <span class="hlt">satellite</span> <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Sequoia 2000 schema development is based on emerging geospatial standards to accelerate development and facilitate data exchange. This paper focuses on the metadata schema for digital <span class="hlt">satellite</span> <span class="hlt">images</span>. We examine how <span class="hlt">satellite</span> metadata are defined, used, and maintained. We discuss the geospatial standards we are using, and describe a SQL prototype that is based on the Spatial Archive and Interchange</p> <div class="credits"> <p class="dwt_author">Jean T. Anderson; Michael Stonebraker</p> <p class="dwt_publisher"></p> <p class="publishDate">1994-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">111</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50033500"> <span id="translatedtitle"><span class="hlt">Image</span> processing for weather <span class="hlt">satellite</span> cloud segmentation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Image</span> segmentation of weather <span class="hlt">satellite</span> imagery is an important first step in an automated weather forecasting system. Accurate cloud extraction is also important in the determination of solar radiative transfer in atmospheric research, where <span class="hlt">satellite</span> observations are used as inputs to global climate models to predict climatic change. Most of the current cloud extraction algorithms tend to be quite complicated</p> <div class="credits"> <p class="dwt_author">I. J. H. Leung; J. E. Jordan</p> <p class="dwt_publisher"></p> <p class="publishDate">1995-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">112</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010EGUGA..12.4751V"> <span id="translatedtitle"><span class="hlt">Time-series</span> of biomass burning products from ground-based FTIR measurements at Reunion Island (21°S, 55°E) and comparisons with the CTM <span class="hlt">IMAGES</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Reunion Island (21°S, 55°E) is part of the Network for the Detection of Atmospheric Composition Change (NDACC), a network dedicated to performing high-quality long-term ground-based observations of atmospheric trace gases at globally distributed sites. Up to now, only a few NDACC stations are located in the Southern Hemisphere, and particularly very few at tropical and subtropical latitudes. Furthermore, Reunion Island is situated in the Indian Ocean, at 2000 km from southeast Africa and at only 700 km from Madagascar. It is therefore a good location to study the transport of biomass burning products from these regions to Reunion Island. Ground-based Fourier transform infrared (FTIR) solar absorption observations are sensitive to a large number of biomass burning products. At present, we have a record of such FTIR observations at Reunion Island from three measurement campaigns, namely in October 2002, from August to October 2004, and from May to October 2007, and from continuous observations that started in May 2009. The measurements in 2007 and 2009-2010 allow the observation of seasonal variability. In this work, we present retrieved <span class="hlt">time-series</span> of several biomass burning products such as C2H2, C2H6 and HCN. These ground-based data are compared to the CTM <span class="hlt">IMAGES</span>. The Lagrangian particle dispersion model FLEXPART is used to explain the day-to-day variability of these species by the transport pathways.</p> <div class="credits"> <p class="dwt_author">Vigouroux, Corinne; de Mazière, Martine; Dils, Bart; Müller, Jean-François; Senten, Cindy; Stavrakou, Trissevgeni; Vanhaelewyn, Gauthier; Fally, Sophie; Duflot, Valentin; Baray, Jean-Luc</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">113</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23622523"> <span id="translatedtitle">Potential of <span class="hlt">time</span> <span class="hlt">series</span>-hyperspectral <span class="hlt">imaging</span> (TS-HSI) for non-invasive determination of microbial spoilage of salmon flesh.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">This study investigated the potential of using <span class="hlt">time</span> <span class="hlt">series</span>-hyperspectral <span class="hlt">imaging</span> (TS-HSI) in visible and near infrared region (400-1700 nm) for rapid and non-invasive determination of surface total viable count (TVC) of salmon flesh during spoilage process. Hyperspectral cubes were acquired at different spoilage stages for salmon chops and their spectral data were extracted. The reference TVC values of the same samples were measured using standard plate count method and then calibrated with their corresponding spectral data based on two calibration methods of partial least square regression (PLSR) and least-squares support vector machines (LS-SVM), respectively. Competitive adaptive reweighted sampling (CARS) was conducted to identify the most important wavelengths/variables that had the greatest influence on the TVC prediction throughout the whole wavelength range. As a result, eight variables representing the wavelengths of 495 nm, 535 nm, 550 nm, 585 nm, 625 nm, 660 nm, 785 nm, and 915 nm were selected, which were used to reduce the high dimensionality of the hyperspectral data. On the basis of the selected variables, the models of PLSR and LS-SVM were established and their performances were compared. The CARS-PLSR model established using Spectral Set I (400-1000 nm) was considered to be the best for the TVC determination of salmon flesh. The model led to a coefficient of determination (rP(2)) of 0.985 and residual predictive deviation (RPD) of 5.127. At last, the best model was used to predict the TVC values of each pixel within the ROI of salmon chops for visualizing the TVC distribution of salmon flesh. The research demonstrated that TS-HSI technique has a potential for rapid and non-destructive determination of bacterial spoilage in salmon flesh during the spoilage process. PMID:23622523</p> <div class="credits"> <p class="dwt_author">Wu, Di; Sun, Da-Wen</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-03-22</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">114</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://virga.sfsu.edu/scripts/mwir_archloop.html"> <span id="translatedtitle">Animation of Archived Composite Infrared <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">With this tool, users can build their own animations from infrared <span class="hlt">satellite</span> imagery superimposed on a world map. Animations are constructed by selecting year, month, date, and time for the archived <span class="hlt">images</span>. Users can also adjust the animation length, interval between <span class="hlt">images</span>, and speed of the animation.</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">115</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/252246"> <span id="translatedtitle">Rule Discovery from <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We consider the problem of finding rules relating pat- terns in a <span class="hlt">time</span> <span class="hlt">series</span> to other patterns in that series, or patterns in one series to patterns in another se- ries. A simple example is a rule such as \\</p> <div class="credits"> <p class="dwt_author">Gautam Das; King-ip Lin; Heikki Mannila; Gopal Renganathan; Padhraic Smyth</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">116</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/21280811"> <span id="translatedtitle">Auroral <span class="hlt">imaging</span> from a spinning <span class="hlt">satellite</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">For optimizing in situ particle and field measurements, auroral research <span class="hlt">satellites</span> are best operated in a spinning mode. Simultaneous <span class="hlt">imaging</span> of the optical aurora from such <span class="hlt">satellites</span> requires either a stable platform or the derotation of the camera itself. Either of these requirements is complex and expensive. Either of these solutions also suffers from the problem that <span class="hlt">image</span> blur often occurs due to the misalignments between the actual and the nominal spin axes of the <span class="hlt">satellite</span>. Here we propose a novel solution in which the camera(s) are mounted solidly on the spacecraft to observe parallel to the spin axis of the <span class="hlt">satellite</span> while a despinning flat 45° mirror directs the field of view toward the spacecraft nadir. The resultant <span class="hlt">image</span> will appear to rotate in the frame of reference of the detector in the camera. In our scheme the <span class="hlt">images</span> are exposed rapidly and a derotation algorithm is applied to the coordinates of each pixel in real time before the <span class="hlt">images</span> are co-added in memory. The derotation algorithm uses only look up tables and integer additions and can be executed rapidly in hardware so that the system can support relatively fast <span class="hlt">satellite</span> spin cycles. The system was simulated including a 1.8° misalignment between the nominal <span class="hlt">satellite</span> spin axis (parallel to the mirror rotation axis) and the actual spin axis. It was shown that the look up table based algorithm can despin the <span class="hlt">images</span> and correct for the axes misalignment, allowing the observation of the aurora at full resolution and with continuous coverage. PMID:21280811</p> <div class="credits"> <p class="dwt_author">Mende, Stephen B</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">117</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012SPIE.8391E...3S"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> modeling for automatic target recognition</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> modeling is proposed for identification of targets whose <span class="hlt">images</span> are not clearly seen. The model building takes into account air turbulence, precipitation, fog, smoke and other factors obscuring and distorting the <span class="hlt">image</span>. The complex of library data (of <span class="hlt">images</span>, etc.) serving as a basis for identification provides the deterministic part of the identification process, while the partial <span class="hlt">image</span> features, distorted parts, irrelevant pieces and absence of particular features comprise the stochastic part of the target identification. The missing data approach is elaborated that helps the prediction process for the <span class="hlt">image</span> creation or reconstruction. The results are provided.</p> <div class="credits"> <p class="dwt_author">Sokolnikov, Andre</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">118</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://sofia.er.usgs.gov/projects/remote_sens/sflsatmap.html"> <span id="translatedtitle">Northern Everglades, Florida, <span class="hlt">satellite</span> <span class="hlt">image</span> map</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">These <span class="hlt">satellite</span> <span class="hlt">image</span> 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 <span class="hlt">satellite</span> <span class="hlt">imaging</span> systems have been georeferenced and processed to facilitate data fusion and analysis. These <span class="hlt">image</span> maps were created using <span class="hlt">image</span> fusion techniques developed as part of this project.</p> <div class="credits"> <p class="dwt_author">Thomas, Jean-Claude; Jones, John W.</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">119</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.agu.org/journals/ja/v088/iA11/JA088iA11p08743/JA088iA11p08743.pdf"> <span id="translatedtitle">Saturn's small <span class="hlt">satellites</span> - Voyager <span class="hlt">imaging</span> results</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Voyagers 1 and 2 provided <span class="hlt">images</span> of sufficient resolution for morphologic and photometric studies of Saturn's small <span class="hlt">satellites</span>. These objects, all very difficult to observe from earth, orbit Saturn at distances of 2.3 to 6.3 Saturn radii (just outside the A ring to the orbit of Dione) and range in mean diameter from 22 to 188 km. All are irregularly</p> <div class="credits"> <p class="dwt_author">P. Thomas; J. Veverka; D. Morrison; M. Davies; T. V. Johnson</p> <p class="dwt_publisher"></p> <p class="publishDate">1983-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">120</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/533870"> <span id="translatedtitle">Road Detection in Panchromatic SPOT <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The goal of this study is to detect the main road network in high resolution, panchromatic SPOT <span class="hlt">satellite</span> <span class="hlt">images</span>. We describe an automatic procedure for road detection which has the following advantages over the previous approaches: 1) it does not require manual initialization; 2) it is able to detect some of the secondary roads in addition to the main highways;</p> <div class="credits"> <p class="dwt_author">Nicolae Duta</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_5");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" 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showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_8");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">121</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010SPIE.7546E.130S"> <span id="translatedtitle"><span class="hlt">Satellite</span> <span class="hlt">image</span> compression using wavelet</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Image</span> data is a combination of information and redundancies, the information is part of the data be protected because it contains the meaning and designation data. Meanwhile, the redundancies are part of data that can be reduced, compressed, or eliminated. Problems that arise are related to the nature of <span class="hlt">image</span> data that spends a lot of memory. In this paper will compare 31 wavelet function by looking at its impact on PSNR, compression ratio, and bits per pixel (bpp) and the influence of decomposition level of PSNR and compression ratio. Based on testing performed, Haar wavelet has the advantage that is obtained PSNR is relatively higher compared with other wavelets. Compression ratio is relatively better than other types of wavelets. Bits per pixel is relatively better than other types of wavelet.</p> <div class="credits"> <p class="dwt_author">Santoso, Alb. Joko; Soesianto, F.; Dwiandiyanto, B. Yudi</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-02-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">122</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/18335552"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> and dependent variables</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We present a new method for analyzing <span class="hlt">time</span> <span class="hlt">series</span> which is designed to extract inherent deterministic dependencies in the series. The method is particularly suited to series with broad-band spectra such as chaotic series with or without noise. We derive quantities, deltaj(?), based on conditional probabilities, whose magnitude, roughly speaking, is an indicator of the extent to which the kth</p> <div class="credits"> <p class="dwt_author">Robert Savit; Matthew Green</p> <p class="dwt_publisher"></p> <p class="publishDate">1991-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">123</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://oaspub.epa.gov/eims/eimsapi.dispdetail?deid=37820"> <span id="translatedtitle">CHEMICAL <span class="hlt">TIME-SERIES</span> SAMPLING</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p class="result-summary">The rationale for chemical <span class="hlt">time-series</span> sampling has its roots in the same fundamental relationships as govern well hydraulics. Samples of ground water are collected as a function of increasing time of pumpage. The most efficient pattern of collection consists of logarithmically s...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">124</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.vldb2007.org/program/papers/research/p459-papadimitriou.pdf"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> Compressibility and Privacy</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper we study the trade-offs between <span class="hlt">time</span> <span class="hlt">series</span> compressibility and partial information hiding and their fun- damental implications on how we should introduce uncer- tainty about individual values by perturbing them. More specifically, if the perturbation does not have the same com- pressibility properties as the original data, then it can be detected and filtered out, reducing uncertainty.</p> <div class="credits"> <p class="dwt_author">Spiros Papadimitriou; Feifei Li; George Kollios; Philip S. Yu</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">125</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/58437524"> <span id="translatedtitle">Interactive management of <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">At tbe IBM Pisa Scientific Center an interactive package has been developed under CP-67\\/CMS, which is particularly helpful when the data to be processed are <span class="hlt">time</span> <span class="hlt">series</span>. The interactive facilities of the operating system CP-67\\/CMS are strenghtened in such a way as to allow an easy interactive correction procedure during the execution of any command. The central file of time</p> <div class="credits"> <p class="dwt_author">Carlo Bianchi; Giorgio Calzolari; Paolo Corsi</p> <p class="dwt_publisher"></p> <p class="publishDate">1974-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">126</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50575200"> <span id="translatedtitle">Cumulative Sum Charts - A Novel Technique for Processing Daily <span class="hlt">Time</span> <span class="hlt">Series</span> of MODIS Data for Burnt Area Mapping in Portugal</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Portugal has experienced severe forest fires in the recent years. European Commission (EC) requires accurate burned area assessment for Portugal every year. <span class="hlt">Satellite</span> data from Moderate Resolution <span class="hlt">Imaging</span> Spectroradiometer (MODIS) were found to be the most appropriate for the task. In this paper we describe an algorithm for burned area mapping in Portugal. The algorithm utilizes daily <span class="hlt">time</span> <span class="hlt">series</span> data</p> <div class="credits"> <p class="dwt_author">J. Kucera; P. Barbosa; P. Strobl</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">127</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/g2v081541uku2337.pdf"> <span id="translatedtitle">Contented-Based <span class="hlt">Satellite</span> Cloud <span class="hlt">Image</span> Processing and Information Retrieval</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Satellite</span> cloud <span class="hlt">image</span> is a kind of useful <span class="hlt">image</span> which includes abundant information, for acquired this information, the <span class="hlt">image</span>\\u000a processing and character extraction method adapt to <span class="hlt">satellite</span> cloud <span class="hlt">image</span> has to be used. Content-based <span class="hlt">satellite</span> cloud <span class="hlt">image</span>\\u000a processing and information retrieval (CBIPIR) is a very important problem in <span class="hlt">image</span> processing and analysis field. The basic\\u000a character, like color, texture, edge</p> <div class="credits"> <p class="dwt_author">Yanling Hao; Wei Shangguan; Yi Zhu; Yanhong Tang</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">128</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2004cosp...35.2207D"> <span id="translatedtitle">Monitoring of wetlands Ecosystems using <span class="hlt">satellite</span> <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Wetlands are very sensitive ecosystems, functioning as habitat for many organisms. Protection and regeneration of wetlands has been the crucial importance in ecological research and in nature conservation. Knowledge on biophysical properties of wetlands vegetation retrieved from <span class="hlt">satellite</span> <span class="hlt">images</span> will enable us to improve monitoring of these unique areas, very often impenetrable. The study covers Biebrza wetland situated in the Northeast part of Poland and is considered as Ramsar Convention test site. The research aims at establishing of changes in biophysical parameters as the scrub encroachment, lowering of the water table, and changes of the farming activity caused ecological changes at these areas. Data from the optical and microwave <span class="hlt">satellite</span> <span class="hlt">images</span> collected for the area of Biebrza marshland ecosystem have been analysed and compared with the detailed soil-vegetation ground measurements conducted in conjunction with the overflights. <span class="hlt">Satellite</span> data include Landsat ETM, ERS-2 ATSR and SAR, SPOT VEGETATION, ENVISAT MERIS and ASAR, and NOAA AVHRR. From the optical data various vegetation indices have been calculated, which characterize the vegetation surface roughness, its moisture conditions and stage of development. Landsat ETM <span class="hlt">image</span> has been used for classification of wetlands vegetation. For each class of vegetation various moisture indices have been developed. Ground data collected include wet and dry biomass, LAI, vegetation height, and TDR soil moisture. The water cloud model has been applied for retrieval of soil vegetation parameters taking into account microwave <span class="hlt">satellite</span> <span class="hlt">images</span> acquired at VV, HV and HH polarisations at different viewing angles. The vegetation parameters have been used for to distinguish changes, which occurred at the area. For each of the vegetation class the soil moisture was calculated from microwave data using developed algorithms. Results of this study will help mapping and monitoring wetlands with the high spatial and temporal resolution for better management and protection of this ecosystems. The research has been conducted under AO ID-122 ESA Project</p> <div class="credits"> <p class="dwt_author">Dabrowska-Zielinska, K.; Gruszczynska, M.; Yesou, H.; Hoscilo, A.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">129</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2002SPIE.4875..408B"> <span id="translatedtitle">Cloud motion detection from infrared <span class="hlt">satellite</span> <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The estimation of cloud motion from a sequence of <span class="hlt">satellite</span> <span class="hlt">images</span> can be considered a challenging task due to the complexity of phenomena implied. Being a non-rigid motion and implying non-linear events, most motion models are not suitable and new algorithms have to be developed. We propose a novel technique, combining a Block Matching Algorithm (BMA) and a best candidate block search along with a vector median regularisation.</p> <div class="credits"> <p class="dwt_author">Brad, Remus; Letia, Ioan A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-07-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">130</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/70042065"> <span id="translatedtitle">Estimating seasonal evapotranspiration from temporal <span class="hlt">satellite</span> <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">Estimating seasonal evapotranspiration (ET) has many applications in water resources planning and management, including hydrological and ecological modeling. Availability of <span class="hlt">satellite</span> remote sensing <span class="hlt">images</span> is limited due to repeat cycle of <span class="hlt">satellite</span> or cloud cover. This study was conducted to determine the suitability of different methods namely cubic spline, fixed, and linear for estimating seasonal ET from temporal remotely sensed <span class="hlt">images</span>. Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model in conjunction with the wet METRIC (wMETRIC), a modified version of the METRIC model, was used to estimate ET on the days of <span class="hlt">satellite</span> overpass using eight Landsat <span class="hlt">images</span> during the 2001 crop growing season in Midwest USA. The model-estimated daily ET was in good agreement (R2 = 0.91) with the eddy covariance tower-measured daily ET. The standard error of daily ET was 0.6 mm (20%) at three validation sites in Nebraska, USA. There was no statistically significant difference (P > 0.05) among the cubic spline, fixed, and linear methods for computing seasonal (July–December) ET from temporal ET estimates. Overall, the cubic spline resulted in the lowest standard error of 6 mm (1.67%) for seasonal ET. However, further testing of this method for multiple years is necessary to determine its suitability.</p> <div class="credits"> <p class="dwt_author">Singh, Ramesh K.; Liu, Shuguang; Tieszen, Larry L.; Suyker, Andrew E.; Verma, Shashi B.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">131</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/39339588"> <span id="translatedtitle">A review on <span class="hlt">time</span> <span class="hlt">series</span> data mining</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> is an important class of temporal data objects and it can be easily obtained from scientific and financial applications. A <span class="hlt">time</span> <span class="hlt">series</span> is a collection of observations made chronologically. The nature of <span class="hlt">time</span> <span class="hlt">series</span> data includes: large in data size, high dimensionality and necessary to update continuously. Moreover <span class="hlt">time</span> <span class="hlt">series</span> data, which is characterized by its numerical and</p> <div class="credits"> <p class="dwt_author">Tak-chung Fu</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">132</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1992scma.conf..349K"> <span id="translatedtitle">Aperiodic <span class="hlt">time</span> <span class="hlt">series</span> in astronomy.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Many different sorts of astronomical quantities vary aperiodically. Examples discussed in this review include the pulse arrival times of radio pulsars, the X-ray flux of accreting stellar mass black holes, and the flux in virtually all bands from active galactic nuclei. It is hoped that these fluctuations can be used to learn more about the underlying systems, and to serve as probes of other structures. Unfortunately, acquiring good quality sampling of the time variation of these systems is difficult. Both ground- and space-based observations are subject to many kinds of uncontrollable interruptions, so that the resulting <span class="hlt">time</span> <span class="hlt">series</span> are almost always highly irregular in density. Special techniques must be invented in order to cope with these problems. Error analysis for derived quantities is particularly important.</p> <div class="credits"> <p class="dwt_author">Krolik, J. H.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">133</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51104224"> <span id="translatedtitle">Uneven cloud and fog removing for <span class="hlt">satellite</span> remote sensing <span class="hlt">image</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Haze is an important influence factor of visible light RS data's obtaining and using. Based on dark channel prior and haze <span class="hlt">image</span> model, this paper studies the dehaze technology from a single <span class="hlt">satellite</span> RS <span class="hlt">image</span>. Aim at the characteristic of uneven cloud in <span class="hlt">satellite</span> RS <span class="hlt">image</span> and the problem of the unreasonable estimate for airlight in dehaze method, this paper</p> <div class="credits"> <p class="dwt_author">Liya Zhou; Zhiyuan Qin</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">134</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/54934334"> <span id="translatedtitle">Integrate <span class="hlt">satellite</span> observing <span class="hlt">images</span> for the Gulf of Mexico</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A number of <span class="hlt">satellite</span> <span class="hlt">image</span> sources providing meteorological and environmental information are available over the Gulf of Mexico (GOM). Those <span class="hlt">satellite</span> <span class="hlt">images</span> are taken periodically in order to observe weather changes. However, users usually face problems when they want to search, retrieve and combine <span class="hlt">images</span> from multiple data sources. Without an adequate system and skilled personnel for managing data, the</p> <div class="credits"> <p class="dwt_author">Longzhuang Li; Shanxian Mao</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">135</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/53957804"> <span id="translatedtitle">Automatically locating the typhoon center based on <span class="hlt">satellite</span> cloud <span class="hlt">image</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">An automatic locating algorithm is presented for typhoon center locating using cloud motion wind vectors derived from the <span class="hlt">satellite</span> cloud <span class="hlt">images</span>. The cloud motion wind vectors are obtained by implementing template matching to a pair of interrelated <span class="hlt">satellite</span> cloud <span class="hlt">images</span> with stated time interval. The template matching is a process to find the child <span class="hlt">image</span> that corresponds to the given</p> <div class="credits"> <p class="dwt_author">Zhengguang Liu; Juntao Xue; Yuanfei Yu; Bing Wu; Gary Shen</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">136</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/12642335"> <span id="translatedtitle">Nonlinear multivariate and <span class="hlt">time</span> <span class="hlt">series</span> analysis by neural network methods</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Methods in multivariate statistical analysis are essential for working with large amounts of geophysical data, data from observational arrays, from <span class="hlt">satellites</span>, or from numerical model output. In classical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base, followed by principal component analysis (PCA) and finally canonical correlation analysis (CCA). A multivariate <span class="hlt">time</span> <span class="hlt">series</span></p> <div class="credits"> <p class="dwt_author">William W. Hsieh</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">137</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50346448"> <span id="translatedtitle">Generation of attenuation <span class="hlt">time-series</span> for EHF SATCOM simulation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, a method for deriving <span class="hlt">time-series</span> of attenuation on fixed <span class="hlt">satellite</span> or terrestrial links is described. The method uses meteorological model forecast data and radar data and hence permits time coincident derivations for multiple sites that include the spatial correlation properties inherent in weather systems. The success of the technique depends upon insertion of the short interval temporal</p> <div class="credits"> <p class="dwt_author">Duncan Hodges; R. Watson; A. Page; P. Watson</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">138</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51178572"> <span id="translatedtitle">Exploration of Subsidence Estimation by Persistent Scatterer InSAR on <span class="hlt">Time</span> <span class="hlt">Series</span> of High Resolution TerraSAR-X <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Ground subsidence is a major concern for land use planning and engineering risk assessment. This paper explores subsidence detection by the persistent scatterer (PS) interfer- ometric synthetic aperture radar (InSAR) technique using the multitemporal high resolution spaceborne SAR <span class="hlt">images</span>. We first describe the mathematical models and the data reduction proce- dures of the PS solution. The experiments of subsidence detection</p> <div class="credits"> <p class="dwt_author">Guoxiang Liu; Hongguo Jia; Rui Zhang; Huixin Zhang; Hongliang Jia; Bing Yu; Mingzhi Sang</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">139</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50442132"> <span id="translatedtitle"><span class="hlt">Satellite</span> <span class="hlt">imaging</span> order scheduling with stochastic weather condition forecast</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper deals with the <span class="hlt">imaging</span> order scheduling problems of FORMOSA-2, a low-earth-orbit, remote-sensing <span class="hlt">satellite</span> which takes <span class="hlt">images</span> of ocean and landmass in the vicinity of Taiwan according to customers' requests. The <span class="hlt">satellite</span> <span class="hlt">imaging</span> order scheduling considers current and future weather conditions to provide an <span class="hlt">imaging</span> plan to satisfy customer requirements with quality <span class="hlt">imaging</span> pictures. We first formulate the problem</p> <div class="credits"> <p class="dwt_author">Da-Yin Liao; Yu-Tsung Yang</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">140</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/55105707"> <span id="translatedtitle">Geostationary <span class="hlt">satellite</span> <span class="hlt">imaging</span> spectrometry for GEOSS: importance and expected benefits</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Satellite</span> infrared hyperspectral instruments provide atmospheric soundings with high spatial resolution. Already implemented aboard polar orbiting <span class="hlt">satellites</span>, these instruments have provided data that are proving to improve greatly global Numerical Weather Prediction (NWP). When implemented aboard geostationary <span class="hlt">satellites</span> as <span class="hlt">imaging</span> spectrometers, even greater impacts on global NWP are expected from their capability to observe vertically resolved cloud and water vapor</p> <div class="credits"> <p class="dwt_author">W. Smith Sr.; S. Mango</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_6");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' 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onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">141</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/56961787"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> analysis and signal processing</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> analysis is the analysis of the data collected sequentially in time. These data are usually represented as linear\\/nonlinear discrete-time models. The <span class="hlt">time-series</span> models are used to analyse and predict the data. A linear <span class="hlt">time</span> <span class="hlt">series</span> is modeled by linear difference equations involving the <span class="hlt">time</span> <span class="hlt">series</span> and the white noise or the innovation process. Such ARMA(p, q) models can</p> <div class="credits"> <p class="dwt_author">S. A. Pavan Kumar; P. K. Bora</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">142</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://decon.edu.uy/publica/2000/Doc1000.pdf"> <span id="translatedtitle">Symbolic <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis in Economics</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper I describe and apply the methods of Symbolic <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis (STSA) to an experimental framework. The idea behind Symbolic <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis is simple: the values of a given <span class="hlt">time</span> <span class="hlt">series</span> data are transformed into a finite set of symbols obtaining a finite string. Then, we can process the symbolic sequence using tools from information theory</p> <div class="credits"> <p class="dwt_author">Juan Gabriel Brida</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">143</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/18282549"> <span id="translatedtitle">Complex network-based <span class="hlt">time</span> <span class="hlt">series</span> analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Recent works show that complex network theory may be a powerful tool in <span class="hlt">time</span> <span class="hlt">series</span> analysis. We propose in this paper a reliable procedure for constructing complex networks from the correlation matrix of a <span class="hlt">time</span> <span class="hlt">series</span>. An original stock <span class="hlt">time</span> <span class="hlt">series</span>, the corresponding return series and its amplitude series are considered. The degree distribution of the original series can be</p> <div class="credits"> <p class="dwt_author">Yue Yang; Huijie Yang</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">144</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010JGRD..11521128L"> <span id="translatedtitle">Integration of the GG model with SEBAL to produce <span class="hlt">time</span> <span class="hlt">series</span> of evapotranspiration of high spatial resolution at watershed scales</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Lack of good quality <span class="hlt">satellite</span> <span class="hlt">images</span> because of cloud contamination or long revisit time severely degrades predictions of evapotranspiration (ET) <span class="hlt">time</span> <span class="hlt">series</span> at watershed/regional scales from <span class="hlt">satellite</span>-based surface flux models. We integrate the feedback model developed by Granger and Gray (the GG model) with the Surface Energy Balance Algorithm for Land (SEBAL), with the objective to generate ET <span class="hlt">time</span> <span class="hlt">series</span> of high spatial resolution and reliable temporal distribution at watershed scales. First, SEBAL is employed to yield estimates of ET for the Baiyangdian watershed in a semihumid climatic zone in north China on cloud-free days, where there exists the complementary relationship (CR) between actual ET and pan ET. These estimates constitute input to the GG model to inversely derive the relationship between the relative evaporation and the relative drying power of the air. Second, the modified GG model is used to yield ET <span class="hlt">time</span> <span class="hlt">series</span> on a daily basis simply by using routine meteorological data and Moderate Resolution <span class="hlt">Imaging</span> Spectroradiometer (MODIS) albedo and leaf area index products. Results suggest that the modified GG model that has incorporated remotely sensed ET can effectively extend remote sensing based ET to days without <span class="hlt">images</span> and improve spatial representation of ET at watershed scales. Utility of the evaporative fraction method and the crop coefficients approaches to extrapolate ET <span class="hlt">time</span> <span class="hlt">series</span> depends largely on the number and interval of good quality <span class="hlt">satellite</span> <span class="hlt">images</span>. Comparison of ET <span class="hlt">time</span> <span class="hlt">series</span> from the two techniques and the proposed integration method for days with daily net radiation larger than 100 W m-2 and corresponding pan ET clearly shows that only the integration method can exhibit an asymmetric CR at the watershed scale and daily time scale. Validation performed using hydrologic budget calculations indicate that the proposed method has the highest accuracy in terms of annual estimates of ET for both watersheds in north China.</p> <div class="credits"> <p class="dwt_author">Long, Di; Singh, Vijay P.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-11-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">145</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/54143296"> <span id="translatedtitle">Prospects of application of survey <span class="hlt">satellite</span> <span class="hlt">image</span> for meteorology</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The maximal interest is represented with the information from geostationary <span class="hlt">satellites</span>. These <span class="hlt">satellites</span> repeat shootings the chosen territories, allowing to study dynamics of <span class="hlt">images</span>. Most interesting shootings in IR a range. Studying of survey <span class="hlt">image</span> is applied to studying linear elements of clouds (LEC). It is established, that \\</p> <div class="credits"> <p class="dwt_author">A. B. Kapochkina; B. B. Kapochkin; N. V. Kucherenko</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">146</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/47900639"> <span id="translatedtitle"><span class="hlt">Time-Series</span> Models in Marketing</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Marketing data appear in a variety of forms. An often-seen form is <span class="hlt">time-series</span> data, like sales per month, prices over the last few years, market shares per week. <span class="hlt">Time-series</span> data can be summarized in <span class="hlt">time-series</span> models. In this chapter we review a few of these, focusing in particular on domains that have received considerable attention in the marketing literature. These</p> <div class="credits"> <p class="dwt_author">Marnik G. Dekimpe; Philip Hans Franses; Dominique M. Hanssens; Prasad A. Naik</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">147</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AdSpR..47..323P"> <span id="translatedtitle">Combination methods of tropospheric <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this article we present two methods for combination of different Global Navigation <span class="hlt">Satellite</span> Systems (GNSS) Zenith Total Delay (ZTD) <span class="hlt">time-series</span> for the same GNSS site, but from different producers or different processing setups. One method has been setup at ASI/CGS, the other at KNMI. Using Near Real-Time (NRT) ZTD data covering 1 year from the E-GVAP project, the performance of the two methods is inter-compared and validation is made against a combined ZTD solution from EUREF, based on post-processed ZTDs. Further, validation of the ASI combined solutions is made against independent ZTDs derived from radiosonde, Numerical Weather Prediction (NWP) model and Very Long Baseline Interferometry (VLBI) ZTD.It is found that the two combined solutions perform quite similar, with a bias from -0.17 mm to 1.52 mm and a standard deviation from 1.60 mm to 3.82 mm. Compared with respect to EUREF post-processed solutions, the NRT combined solutions shows a small but positive bias which could be due to a different way of dealing with phase ambiguities in the data reduction process. Further, it is found that the ASI combined solution compares better to both radiosonde, NWP model and VLBI ZTDs than the individual <span class="hlt">time-series</span> upon which it is based.It is concluded that the combined NRT solutions appear a promising tool for rapid control of the NRT ZTDs produced today by a number of Analysis Centres (ACs) across Europe for use in meteorology. It is known that the NRT processing is prone to certain types of errors rarely seen in post-processing. These errors can lead to a large number of ZTDs from a given AC having correlated errors, which can do serious damage if the data are used in Numerical Weather Prediction, even if it is a rare occurrence. Identification and blocking of such data is therefore a goal in the NRT GNSS data processing and validation.</p> <div class="credits"> <p class="dwt_author">Pacione, R.; Pace, B.; Vedel, H.; de Haan, S.; Lanotte, R.; Vespe, F.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">148</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005EJPh...26..969F"> <span id="translatedtitle"><span class="hlt">Satellite</span> <span class="hlt">image</span> eavesdropping: a multidisciplinary science education project</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Amateur reception of <span class="hlt">satellite</span> <span class="hlt">images</span> gathers a wide number of concepts and technologies which makes it attractive as an educational tool. We here introduce the reception of <span class="hlt">images</span> emitted from NOAA series low-altitude Earth-orbiting <span class="hlt">satellites</span>. We tackle various issues including the identification and prediction of the pass time of visible <span class="hlt">satellites</span>, the building of the radio-frequency receiver and antenna after modelling their radiation pattern, and then the demodulation of the resulting audio signal for finally displaying an <span class="hlt">image</span> of the Earth as seen from space.</p> <div class="credits"> <p class="dwt_author">Friedt, Jean-Michel</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-11-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">149</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2399814"> <span id="translatedtitle">Macintosh Program performs <span class="hlt">time-series</span> analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A Macintosh computer program that can perform many <span class="hlt">time-series</span> analysis procedures is now available on the Internet free of charge. Although AnalySeries was originally designed for paleoclimatic <span class="hlt">time</span> <span class="hlt">series</span>, it can be useful for most fields of Earth sciences. The program's graphical user interface allows easy access even for people unfamiliar with computer calculations. Previous versions of the program are</p> <div class="credits"> <p class="dwt_author">Didier Paillard; Laurent Labeyrie; Pascal Yiou</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">150</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/38747857"> <span id="translatedtitle">Neural Network Models for <span class="hlt">Time</span> <span class="hlt">Series</span> Forecasts</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, <span class="hlt">time</span> <span class="hlt">series</span> forecasts produced by neural networks are compared with forecasts from six statistical <span class="hlt">time</span> <span class="hlt">series</span> methods generated in a major forecasting competition (Makridakis et al. [Makridakis, S., A. Anderson, R. Carbone, R. Fildes, M. Hibon, R. Lewandowski, J. Newton, E. Parzen, R.</p> <div class="credits"> <p class="dwt_author">Tim Hill; Marcus OConnor; William Remus</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">151</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.icors2009.unipr.it/presentations/fried.pdf"> <span id="translatedtitle">Outliers and interventions in INGARCH <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We consider intervention eects generating various types of outliers in a linear count <span class="hlt">time</span> <span class="hlt">series</span> model which belongs to the class of observation driven models. Such models are widely used, because they extend the class of Gaussian linear <span class="hlt">time</span> <span class="hlt">series</span> models in a natural way. However, studies about eects of covariates and interventions have largely fallen behind due to the</p> <div class="credits"> <p class="dwt_author">R. Fried; K. Fokianos</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">152</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://kissen.informatik.uni-dortmund.de/DOKUMENTE/rueping_2001a.pdf"> <span id="translatedtitle">SVM Kernels for <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> analysis is an important and complex problem in machine learning and statistics. Real-world applications can consist of very large and high dimensional <span class="hlt">time</span> <span class="hlt">series</span> data. Support Vector Machines (SVMs) are a popular tool for the analysis of such data sets. This paper presents some SVM kernel functions and disusses their relative merits, depending on the type of data</p> <div class="credits"> <p class="dwt_author">Stefan R</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">153</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/90864"> <span id="translatedtitle">SVM Kernels for <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> analysis is an important and complex problem in machine learning and statistics. Real-worldapplications can consist of very large and high dimensional <span class="hlt">time</span> <span class="hlt">series</span> data. Support Vector Machines (SVMs) area popular tool for the analysis of such data sets. This paper presents some SVM kernel functions and disusses theirrelative merits, depending on the type of data that is used.</p> <div class="credits"> <p class="dwt_author">Stefan Rüping</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">154</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/6565085"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> Analysis with Neural Networks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> data constitute a large portion of the data that are available in many fields such as business and scientific applications: stock prices, sales numbers, weather, geological and environmental data. Various types of neural networks are applied to <span class="hlt">time</span> <span class="hlt">series</span> data to achieve different goals, such as multi-layer perceptrons, radial basis networks for classification, approximation, clustering, prediction, etc. In</p> <div class="credits"> <p class="dwt_author">Efsun SARIOGLU; Kamran IQBAL; Coskun BAYRAK</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">155</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/58291673"> <span id="translatedtitle">Heuristic Analysis of <span class="hlt">Time</span> <span class="hlt">Series</span> Internal Structure</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A method of analysis of <span class="hlt">Time</span> <span class="hlt">Series</span> Internal Structures based on Singular Spectrum Analysis is discussed. It has been shown that in the case when the <span class="hlt">Time</span> <span class="hlt">Series</span> contains deterministic additive components rank of the trajectory matrices equal to number of parameters of the components. Also it was proved that both eigen and factor vectors repeat shapes of the additive</p> <div class="credits"> <p class="dwt_author">Cihan Mert; Alexander Milnikov</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">156</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://public.rz.fh-wolfenbuettel.de/~hoeppnef/paper/Hoeppner-WKDSTD-2002.pdf"> <span id="translatedtitle">Learning Dependencies in Multivariate <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper sketches an approach to learn interdependencies be- tween multiple <span class="hlt">time</span> <span class="hlt">series</span>. At the beginning the <span class="hlt">time</span> <span class="hlt">series</span> are seg- mented and thereby transformed into sequences of labeled intervals. The labels denote qualitative aspects of the signal in the respective intervals. Then, from the sequence of labeled intervals, we discover rules where premise and conclusion consist of temporal patterns.</p> <div class="credits"> <p class="dwt_author">Frank H</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">157</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/16090007"> <span id="translatedtitle">Volatility of linear and nonlinear <span class="hlt">time</span> <span class="hlt">series</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Previous studies indicated that nonlinear properties of Gaussian distributed <span class="hlt">time</span> <span class="hlt">series</span> with long-range correlations, u(i), can be detected and quantified by studying the correlations in the magnitude series |u(i)|, the "volatility." However, the origin for this empirical observation still remains unclear and the exact relation between the correlations in u(i) and the correlations in |u(i)| is still unknown. Here we develop analytical relations between the scaling exponent of linear series u(i) and its magnitude series |u(i)|. Moreover, we find that nonlinear <span class="hlt">time</span> <span class="hlt">series</span> exhibit stronger (or the same) correlations in the magnitude <span class="hlt">time</span> <span class="hlt">series</span> compared with linear <span class="hlt">time</span> <span class="hlt">series</span> with the same two-point correlations. Based on these results we propose a simple model that generates multifractal <span class="hlt">time</span> <span class="hlt">series</span> by explicitly inserting long range correlations in the magnitude series; the nonlinear multifractal <span class="hlt">time</span> <span class="hlt">series</span> is generated by multiplying a long-range correlated <span class="hlt">time</span> <span class="hlt">series</span> (that represents the magnitude series) with uncorrelated <span class="hlt">time</span> <span class="hlt">series</span> [that represents the sign series sgn (u(i))]. We apply our techniques on daily deep ocean temperature records from the equatorial Pacific, the region of the El-Ninõ phenomenon, and find: (i) long-range correlations from several days to several years with 1/f power spectrum, (ii) significant nonlinear behavior as expressed by long-range correlations of the volatility series, and (iii) broad multifractal spectrum. PMID:16090007</p> <div class="credits"> <p class="dwt_author">Kalisky, Tomer; Ashkenazy, Yosef; Havlin, Shlomo</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-07-21</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">158</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=https://eprints.kfupm.edu.sa/37178/1/37178.pdf"> <span id="translatedtitle">Efficient <span class="hlt">Time</span> <span class="hlt">Series</span> Matching by Wavelets</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> stored as feature vectors can be indexed by multi- dimensional index trees like R-Trees for fast retrieval. Due to the dimensionality curse problem, transformations are applied to <span class="hlt">time</span> <span class="hlt">series</span> to reduce the number of dimensions of the feature vec- tors. Different transformations like Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT), Karhunen-Loeve (K- L) transform or Singular Value</p> <div class="credits"> <p class="dwt_author">Kin-pong Chan; Ada Wai-chee Fu</p> <p class="dwt_publisher"></p> <p class="publishDate">1999-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">159</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.agu.org/journals/wr/v018/i004/WR018i004p01011/WR018i004p01011.pdf"> <span id="translatedtitle">ARMA Model identification of hydrologic <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In recent years, ARMA models have become popular for modeling geophysical <span class="hlt">time</span> <span class="hlt">series</span> in general and hydrologic <span class="hlt">time</span> <span class="hlt">series</span> in particular. The identification of the appropriate order of the model is an important stage in ARMA modeling. Such model identification is generally based on the autocorrelation and partial autocorrelation functions, although recently improvements have been obtained using the inverse autocorrelation</p> <div class="credits"> <p class="dwt_author">J. D. Salas; J. T. B. Obeysekera</p> <p class="dwt_publisher"></p> <p class="publishDate">1982-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">160</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/54687045"> <span id="translatedtitle">Detecting functional relationships between simultaneous <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We describe a method to characterize the predictability and functionality between two simultaneously generated <span class="hlt">time</span> <span class="hlt">series</span>. This nonlinear method requires minimal assumptions and can be applied to data measured either from coupled systems or from different positions on a spatially extended system. This analysis generates a function statistic, Thetac0, that quantifies the level of predictability between two <span class="hlt">time</span> <span class="hlt">series</span>. We</p> <div class="credits"> <p class="dwt_author">C. L. Goodridge; L. M. Pecora; T. L. Carroll; F. J. Rachford</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_7");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' 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onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">161</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EL....10350011M"> <span id="translatedtitle">Coupling between <span class="hlt">time</span> <span class="hlt">series</span>: A network view</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Recently, the visibility graph has been introduced as a novel method for analyzing <span class="hlt">time</span> <span class="hlt">series</span>, which maps a <span class="hlt">time</span> <span class="hlt">series</span> to a complex network. In this paper we introduce a new algorithm of visibility, “cross-visibility”, which reveals the conjugation of two coupled <span class="hlt">time</span> <span class="hlt">series</span>. The correspondence between the two <span class="hlt">time</span> <span class="hlt">series</span> is mapped to a network, “the cross-visibility graph”, to demonstrate the correlation between them. We have applied the algorithm to several correlated and uncorrelated <span class="hlt">time</span> <span class="hlt">series</span>, generated by the linear stationary ARFIMA process, in order to better understand the results of the cross-visibility of empirical series. The comparison between the degree distribution of coupled and uncoupled (shuffled) series' networks demonstrates the emergence of super nodes (extremely high-degree nodes) in the uncoupled ones. Furthermore, we have applied the algorithm to real-world data from the financial trades of two companies and oil, and observed significant small-scale coupling in their dynamics.</p> <div class="credits"> <p class="dwt_author">Mehraban, S.; Shirazi, A. H.; Zamani, M.; Jafari, G. R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">162</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008AGUFM.G23A..06F"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> of Deformation in Southern California From 15 Years of InSAR Observations</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We present <span class="hlt">time</span> <span class="hlt">series</span> of line-of-sight (LOS) displacements derived from the Synthetic Aperture Radar (SAR) data collected over the Southern San Andreas Fault System. We use data acquired by the ERS <span class="hlt">satellites</span> from the descending tracks 127 and 356 over a time period between 1992 and 2007. For each coherent pixel of the radar <span class="hlt">images</span> we compute time-dependent surface displacements as well as an average LOS velocity. We compare the mean LOS velocity fields calculated using the Small BAseline Subset Algorithm (SBAS) and Atmospheric Noise Reduction (ANR) scheme. The velocity fields inferred using the two methods are in excellent agreement, suggesting that estimates of time-dependent deformation are robust. The inferred LOS velocity fields also favorably compare to the continuous GPS data (projected onto the <span class="hlt">satellite</span> line of sight). However, we find that velocity estimates obtained without orbital corrections have small but systematic biases compared to GPS data. This implies that orbital errors are not randomly distributed throughout the history of radar acquisitions, and auxiliary data (e.g., tie points using GPS-derived velocities) may be necessary for correcting the effects of imprecise <span class="hlt">satellite</span> orbits. We use the dense InSAR and GPS <span class="hlt">time</span> <span class="hlt">series</span> to investigate interseismic deformation rates due to major faults of the Southern San Andreas system. We model the new InSAR and available GPS data to constrain secular slip rates on major faults, as well as to detect and quantify any possible transient slip.</p> <div class="credits"> <p class="dwt_author">Fialko, Y.; Manzo, M.; Casu, F.; Pepe, A.; Lanari, R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">163</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005PhDT.......174M"> <span id="translatedtitle">Long sequence <span class="hlt">time</span> <span class="hlt">series</span> analysis of Moroccan ecosystem dynamics</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The principal technique used in this investigation was a Principal Components-based <span class="hlt">time</span> <span class="hlt">series</span> analysis (TSA). Using a set of 240 monthly composite multi-band AVHRR <span class="hlt">images</span> for Morocco, a 20-year <span class="hlt">time</span> <span class="hlt">series</span> of monthly NDVI <span class="hlt">images</span> was analyzed to understand the environmental dynamics in arid and semi-arid regions using different vegetation indices. In addition, a second analysis was conducted using a vegetation index specifically designed for use in areas of sparse vegetation--the Modified Soil-Adjusted Vegetation Index (MSAVI). The results showed that the NDVI archive produced a series of readily-interpreted components, including variations in biomass relating to geographic context (Component 1) and seasonality (Component 2). Of particular interest was one that was found to relate to the North Atlantic Oscillation (NAO) and another that showed a linear trend of increasing biomass levels over the entire series. The NAO index has a great impact on Moroccan agriculture. Success to model its occurrence results in a prediction of good and bad years in yield. Such process will help to plan for agriculture planning. In this research I have mapped spatially the occurrence of the NAO index and have found the concordance between component five and the occurrence of NAO. One problematic element in the NDVI analysis was its sensitivity to orbital decay. As the time of equatorial crossing decays over time, the NDVI measure is affected. This was picked up in several components and led to uncertainty in the interpretation of several. As a result, an initial exploratory analysis was undertaken of the MODIS instrument aboard the TERRA and AQUA <span class="hlt">satellites</span>. Although the archive is currently very short, this product has a higher spatial resolution and is very well calibrated. An analysis of a three year sequence for Morocco clearly demonstrated the superiority of the product. However, it also corroborated the main interpretations of the AVHRR NDVI sequence. Surprisingly, the MSAVI analysis proved to be quite inconsistent with that from the NDVI analyses using AVHRR and MODIS data. Its greater sensitivity in areas of sparse vegetation was substantiated. However, the components were unusual and very difficult to interpret.</p> <div class="credits"> <p class="dwt_author">Marzouk, Abdelkrim</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">164</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=ADA273867"> <span id="translatedtitle">Human Visual System Enhancement of Reconstructed <span class="hlt">Satellite</span> <span class="hlt">Images</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">This research investigated the enhancement of <span class="hlt">satellite</span> <span class="hlt">images</span>. The goal was to develop and test a suite of <span class="hlt">image</span> enhancement software routines to improve the quality of reconstructed <span class="hlt">images</span> for the human visual system. The primary focus was to enhance sa...</p> <div class="credits"> <p class="dwt_author">J. E. Treleaven</p> <p class="dwt_publisher"></p> <p class="publishDate">1993-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">165</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010AGUFMAE24A..02H"> <span id="translatedtitle">Geostationary Lightning <span class="hlt">Imager</span> for FY-4 Meteorological <span class="hlt">Satellite</span> (Invited)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The FY-4 <span class="hlt">satellite</span> scheduled to launch in 2015 is a second-generation Chinese geostationary meteorological <span class="hlt">satellite</span>. The main payloads for FY-4 <span class="hlt">satellite</span> include Geostationary Lightning <span class="hlt">Imager</span> (GLI), Advanced Geostationary Visible and Infrared <span class="hlt">Imager</span> (AGVII), and Geostationary Interfering Infrared Sounder (GIIRS). Since the GLI is the first lightning detection <span class="hlt">imager</span> without any heritage on a Chinese meteorological <span class="hlt">satellite</span>, it is a great challenge to implement this mission. The GLI covers the most part of China, land and ocean and nearby areas. The continuous and real time lightning <span class="hlt">imaging</span> products from GLI will be applied to weather forecasting, convection event monitoring, and typhoon tracking. The instrument formulation studies started 4 years ago, and now it is at implementation stage of making prototype models. A working group has begun to develop the L1 and L2 algorithms for lightning <span class="hlt">imaging</span> data processing. At present, we are focusing on resolving several critical issues for GLI. The first one is how to make sure the Real Time Event Processor (RTEP) works well in orbit, which relates whether or not the lightning information could be picked up correctly. The second is how to make best uses of lightning <span class="hlt">imaging</span> products from GLI in all kinds of application fields. Since the Geostationary Lightning Mapper (GLM) and Lighting <span class="hlt">Imager</span> (LI) are lighting <span class="hlt">imagers</span> on geostationary <span class="hlt">satellites</span> with similar instrument structure and working principles to GLI, we welcome international collaboration on GLI lightning products: algorithm development, lightning <span class="hlt">imaging</span> applications, and other relative topics.</p> <div class="credits"> <p class="dwt_author">Huang, F.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">166</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009EGUGA..11.7495K"> <span id="translatedtitle">Long GPS coordinate <span class="hlt">time</span> <span class="hlt">series</span>: multipath and geometry effects</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Within analyses of Global Positioning System (GPS) observations, unmodelled sub-daily signals are known to propagate into long-period signals via a number of different mechanisms. In this paper, we investigate the effects of time-variable <span class="hlt">satellite</span> geometry and the propagation of an unmodelled multipath signal that is analogous to a change in the elevation dependant phase centre of the receiving antenna. Multipath reflectors at H=0.1 m, 0.2 m and 1.5 m below the antenna are modeled and their effects on GPS coordinate <span class="hlt">time</span> <span class="hlt">series</span> are examined. Simulated <span class="hlt">time</span> <span class="hlt">series</span> at 20 global IGS sites for 2000-2008 were derived using the <span class="hlt">satellite</span> geometry as defined by daily broadcast orbits, in addition to that defined using a perfectly repeating synthetic orbit. For the simulations generated using the broadcast orbits with a perfectly clear horizon, we observe the introduction of a time variable bias in the <span class="hlt">time</span> <span class="hlt">series</span> of up to several centimeters. Considerable site to site variability of the frequency and magnitude of the signal is observed, in addition to variation as a function of multipath source. When adopting realistic GPS observation geometries obtained from real data (e.g., those that include the effects of tracking outages, local obstructions, etc.), we observe concerning levels of temporal coordinate variation in the presence of the multipath signals. In these cases, we observe spurious signals across the frequency domain, in addition to what appears as offsets and secular trends. Velocity biases of more than 1mm/yr are evident at some few sites. The propagated signal in the vertical component is consistent with a noise model with a spectral index marginally above flicker noise (mean index -1.4), with some sites exhibiting power law magnitudes at comparable levels to actual height <span class="hlt">time</span> <span class="hlt">series</span> generated in GIPSY. The propagated signal also shows clear spectral peaks across all coordinate components at harmonics of the draconitic year for a GPS <span class="hlt">satellite</span> (351.4 days). When a perfectly repeating synthetic GPS constellation is used, the simulations show near-negligible power law variability highlighting that subtle variations in the GPS constellation can propagate multipath signals differently over time, producing significant temporal variations in <span class="hlt">time</span> <span class="hlt">series</span>. We conclude that the time variable nature of GPS observation geometry and <span class="hlt">satellite</span> orbits combined with a multipath signal that is manifested as an elevation dependant bias can introduce a spurious signal that is a potential significant contributor to flicker noise present in GPS <span class="hlt">time</span> <span class="hlt">series</span>. Further, the spurious signal also makes a potential significant contribution to the energy present at frequencies related to the draconitic year and harmonic thereof observed in GPS analyses.</p> <div class="credits"> <p class="dwt_author">King, M. A.; Watson, C. S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">167</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009AGUFM.G11B0641K"> <span id="translatedtitle">Long GPS coordinate <span class="hlt">time</span> <span class="hlt">series</span>: multipath and geometry effects</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Within analyses of Global Positioning System (GPS) observations, unmodelled sub-daily signals are known to propagate into long-period signals via a number of different mechanisms. We report on the effects of time-variable <span class="hlt">satellite</span> geometry and the propagation of an unmodelled multipath signal. Multipath reflectors at H=0.1 m, 0.2 m and 1.5 m below the antenna are modeled and their effects on GPS coordinate <span class="hlt">time</span> <span class="hlt">series</span> are examined. Simulated <span class="hlt">time</span> <span class="hlt">series</span> at 20 global IGS sites for 2000-2008 were derived using the <span class="hlt">satellite</span> geometry as defined by daily broadcast orbits, in addition to that defined using a perfectly repeating synthetic orbit. For the simulations generated using the broadcast orbits with a perfectly clear horizon, we observe the introduction of a time variable bias in the <span class="hlt">time</span> <span class="hlt">series</span> of up to several centimeters. Considerable site to site variability of the frequency and magnitude of the signal is observed, in addition to variation as a function of multipath source. When adopting realistic GPS observation geometries obtained from real data (e.g., those that include the effects of tracking outages, local obstructions, etc.), we observe concerning levels of temporal coordinate variation in the presence of the multipath signals. In these cases, we observe spurious signals across the frequency domain, in addition to what appears as offsets and secular trends. Velocity biases of more than 1mm/yr are evident at some few sites. The propagated signal in the vertical component is consistent with a noise model with a spectral index marginally above flicker noise (mean index -1.4), with some sites exhibiting power law magnitudes at comparable levels to actual height <span class="hlt">time</span> <span class="hlt">series</span> generated in GIPSY. The propagated signal also shows clear spectral peaks across all coordinate components at harmonics of the draconitic year for a GPS <span class="hlt">satellite</span> (351.2 days). When a perfectly repeating synthetic GPS constellation is used, the simulations show near-negligible power law variability highlighting that subtle variations in the GPS constellation can propagate multipath signals differently over time, producing significant temporal variations in <span class="hlt">time</span> <span class="hlt">series</span>. We conclude that the time variable nature of GPS observation geometry and <span class="hlt">satellite</span> orbits combined with a multipath signal that is manifested as an elevation dependant bias can introduce a spurious signal that is a potential significant contributor to time-correlated noise present in GPS <span class="hlt">time</span> <span class="hlt">series</span>. Further, the spurious signal also makes a potential significant contribution to the energy present at frequencies related to the draconitic year and harmonic thereof observed in GPS analyses.</p> <div class="credits"> <p class="dwt_author">King, M.; Watson, C. S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">168</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010AGUFM.H13G..03C"> <span id="translatedtitle">River flood events as natural tracer tests for investigating a coupled river-aquifer system: improved time-lapse 3D <span class="hlt">imaging</span> of flow patterns by deconvolving ERT <span class="hlt">time-series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We are investigating how temporal fluctuations in 3D apparent resistivity data can be used to <span class="hlt">image</span> freshly infiltrated river water in an aquifer. To this end, we have installed 18 wells within a gravel aquifer in the vicinity of the losing river Thur in Switzerland. A sequence of ˜15,000 crosswell apparent resistivity measurements is acquired every 7 h. A neighboring river gauge and 14 loggers also record water table, temperature, and electrical resistivity of water. Following precipitation events, the river stage increases quickly (e.g., 2 m in 6 h) and the salinity of the river water decreases (e.g., 30%). The changing electrical characteristics of the infiltrating water can thus be used as a natural conservative tracer that we can track in space and time in the aquifer. The time-lapse ERT data are sensitive to variations in salinity and watertable height, with the relative contributions of these two opposing effects depending on time and electrode configuration. Initial time-lapse inversions of the raw data display strong artifacts related to the watertable fluctuations. Here, we focus on correcting the apparent resistivity data to avoid these effects. We assume that variations in the apparent resistivity for each electrode configuration can be predicted at all times through a convolution of unknown smoothly varying finite linear impulse responses (to be determined) with variations in the river stage and the electrical resistivity of the river water. Prior to deconvolution, the apparent resistivities of each time-lapse sequence are resampled to a common time. We also filter out the effects of long-term variations in temperature on the apparent resistivities. The transfer functions estimated through deconvolution allow us to estimate accurately the variations in the apparent resistivity data (the mean correlation coefficient cc is 0.92). The ERT data filtered for the watertable effect have an increased correlation with the <span class="hlt">time-series</span> of the groundwater electrical resistivity (cc from 0.75 to 0.81) and are practically uncorrelated with those of the watertable (cc = -0.16). To test the generality of the estimated transfer functions, we use input signals outside the calibration period to predict the apparent resistivity <span class="hlt">time-series</span> with overall satisfactory results. From data recorded within the calibration period, we extract <span class="hlt">time-series</span> corresponding to a specific flooding event and perform time-lapse inversion of the filtered data. <span class="hlt">Time-series</span> of the inverted electrical resistivity at different locations within the aquifer display reduced correlation with water table fluctuations (cc from -0.77 to -0.49 similar to the correlation of the input signals) and much higher correlation with the groundwater resistivity data (cc from 0.77 to 0.86). The time-lapse inversions reveal that a central 2-m-thick high resistivity part of the aquifer displays the largest resistivity time variations. We observe resistivity increases up to 10%, with the arrival peak moving at approximately 10 m/day.</p> <div class="credits"> <p class="dwt_author">Coscia, I.; Linde, N.; Greenhalgh, S. A.; Vogt, T.; Doetsch, J. A.; Green, A. G.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">169</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://reference.kfupm.edu.sa/content/n/e/near_realtime_satellite_image_processing_1463175.pdf"> <span id="translatedtitle">Near-real-time <span class="hlt">satellite</span> <span class="hlt">image</span> processing: metacomputing in CC++</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Metacomputing combines heterogeneous system elements in a seamless computing service. In this case study, we introduce the elements of metacomputing and describe an application for cloud detection and visualization of infrared and visible-light <span class="hlt">satellite</span> <span class="hlt">images</span>. The application processes the <span class="hlt">satellite</span> <span class="hlt">images</span> by using Compositional C++ (CC++)-a simple, yet powerful extension of C++-and its runtime system, Nexus, to integrate specialized resources,</p> <div class="credits"> <p class="dwt_author">Craig A. Lee; Carl Kesselman; Stephen Schwab</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">170</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2458734"> <span id="translatedtitle"><span class="hlt">Satellite</span> <span class="hlt">Image</span> Processing Applications in MedioGRID</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents a high level architectural specification of MedioGRID, a research project aiming at implementing a real-time <span class="hlt">satellite</span> <span class="hlt">image</span> processing system for extracting relevant environmental and meteorological parameters on a grid system. The presentation focuses on the key architectural decisions of the GRID-aware <span class="hlt">satellite</span> <span class="hlt">image</span> processing system, highlighting the technologies for each of the major components. An essential part</p> <div class="credits"> <p class="dwt_author">Ovidiu Muresan; textbfFlorin Pop; Dorian Gorgan; Valentin Cristea</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">171</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010PhDT........43B"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> change detection: Algorithms for land cover change</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The climate and earth sciences have recently undergone a rapid transformation from a data-poor to a data-rich environment. In particular, climate and ecosystem related observations from remote sensors on <span class="hlt">satellites</span>, as well as outputs of climate or earth system models from large-scale computational platforms, provide terabytes of temporal, spatial and spatio-temporal data. These massive and information-rich datasets offer huge potential for advancing the science of land cover change, climate change and anthropogenic impacts. One important area where remote sensing data can play a key role is in the study of land cover change. Specifically, the conversion of natural land cover into humandominated cover types continues to be a change of global proportions with many unknown environmental consequences. In addition, being able to assess the carbon risk of changes in forest cover is of critical importance for both economic and scientific reasons. In fact, changes in forests account for as much as 20% of the greenhouse gas emissions in the atmosphere, an amount second only to fossil fuel emissions. Thus, there is a need in the earth science domain to systematically study land cover change in order to understand its impact on local climate, radiation balance, biogeochemistry, hydrology, and the diversity and abundance of terrestrial species. Land cover conversions include tree harvests in forested regions, urbanization, and agricultural intensification in former woodland and natural grassland areas. These types of conversions also have significant public policy implications due to issues such as water supply management and atmospheric CO2 output. In spite of the importance of this problem and the considerable advances made over the last few years in high-resolution <span class="hlt">satellite</span> data, data mining, and online mapping tools and services, end users still lack practical tools to help them manage and transform this data into actionable knowledge of changes in forest ecosystems that can be used for decision making and policy planning purposes. In particular, previous change detection studies have primarily relied on examining differences between two or more <span class="hlt">satellite</span> <span class="hlt">images</span> acquired on different dates. Thus, a technological solution that detects global land cover change using high temporal resolution <span class="hlt">time</span> <span class="hlt">series</span> data will represent a paradigm-shift in the field of land cover change studies. To realize these ambitious goals, a number of computational challenges in spatio-temporal data mining need to be addressed. Specifically, analysis and discovery approaches need to be cognizant of climate and ecosystem data characteristics such as seasonality, non-stationarity/inter-region variability, multi-scale nature, spatio-temporal autocorrelation, high-dimensionality and massive data size. This dissertation, a step in that direction, translates earth science challenges to computer science problems, and provides computational solutions to address these problems. In particular, three key technical capabilities are developed: (1) Algorithms for <span class="hlt">time</span> <span class="hlt">series</span> change detection that are effective and can scale up to handle the large size of earth science data; (2) Change detection algorithms that can handle large numbers of missing and noisy values present in <span class="hlt">satellite</span> data sets; and (3) Spatio-temporal analysis techniques to identify the scale and scope of disturbance events.</p> <div class="credits"> <p class="dwt_author">Boriah, Shyam</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">172</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013IJMPC..2450006W"> <span id="translatedtitle">Multiscale Entropy Analysis of Traffic <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">There has been considerable interest in quantifying the complexity of different <span class="hlt">time</span> <span class="hlt">series</span>, such as physiologic <span class="hlt">time</span> <span class="hlt">series</span>, traffic <span class="hlt">time</span> <span class="hlt">series</span>. However, these traditional approaches fail to account for the multiple time scales inherent in <span class="hlt">time</span> <span class="hlt">series</span>, which have yielded contradictory findings when applied to real-world datasets. Then multi-scale entropy analysis (MSE) is introduced to solve this problem which has been widely used for physiologic <span class="hlt">time</span> <span class="hlt">series</span>. In this paper, we first apply the MSE method to different correlated series and obtain an interesting relationship between complexity and Hurst exponent. A modified MSE method called multiscale permutation entropy analysis (MSPE) is then introduced, which replaces the sample entropy (SampEn) with permutation entropy (PE) when measuring entropy for coarse-grained series. We employ the traditional MSE method and MSPE method to investigate complexities of different traffic series, and obtain that the complexity of weekend traffic <span class="hlt">time</span> <span class="hlt">series</span> differs from that of the workday <span class="hlt">time</span> <span class="hlt">series</span>, which helps to classify the series when making predictions.</p> <div class="credits"> <p class="dwt_author">Wang, Jing; Shang, Pengjian; Zhao, Xiaojun; Xia, Jianan</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-02-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">173</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50382942"> <span id="translatedtitle">Biophysical drought metrics extraction by <span class="hlt">time</span> <span class="hlt">series</span> analysis of SPOT Vegetation data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The repeated occurrence of severe wildfires has highlighted the need for development of effective vegetation moisture monitoring tools. The normalized difference infrared index (NDII) derived from SPOT Vegetation <span class="hlt">satellite</span> data and the Keetch-Byram drought index derived from temperature and rainfall data are both related to vegetation moisture dynamics. Autocorrelation of <span class="hlt">time</span> <span class="hlt">series</span> is a major issue when <span class="hlt">time</span> <span class="hlt">series</span> derived</p> <div class="credits"> <p class="dwt_author">Jan Verbesselt; Stefaan Lhermitte; Pol Coppin; Lars Eklundh; Per Jönsson</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">174</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ars.usda.gov/research/publications/Publications.htm?seq_no_115=289967"> <span id="translatedtitle">An approach to constructing a homogeneous <span class="hlt">time</span> <span class="hlt">series</span> of soil mositure using SMOS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p class="result-summary">Overlapping soil moisture <span class="hlt">time</span> <span class="hlt">series</span> derived from two <span class="hlt">satellite</span> microwave radiometers (SMOS, Soil Moisture and Ocean Salinity; AMSR-E, Advanced Microwave Scanning Radiometer - Earth Observing System) are used to generate a soil moisture <span class="hlt">time</span> <span class="hlt">series</span> from 2003 to 2010. Two statistical methodologies f...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">175</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/5677402"> <span id="translatedtitle">Diffraction-limited <span class="hlt">imaging</span> of <span class="hlt">satellites</span> using bispectral speckle interferometry</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">We have developed and implemented a new technology for removing the effects of atmospheric turbulence from telescope <span class="hlt">images</span>. This technology, bispectral speckle interferometry, permits <span class="hlt">imaging</span> of astronomical objects and <span class="hlt">satellites</span> to the diffraction limit of the collecting telescope. We have successfully applied this technique to speckle <span class="hlt">images</span> we obtained with a 1.6 meter telescope at the Air Force Maui Optical Station on Mt. Haleakala, Maui. We have extracted diffraction-limited features of several <span class="hlt">satellites</span>, including the Hubble Space Telescope. This technology should have a positive impact on both astronomical and defense <span class="hlt">imaging</span> problems. 18 ref., 4 figs.</p> <div class="credits"> <p class="dwt_author">Lawrence, T.W.; Goodman, D.M.; Fitch, J.P.; Johansson, E.M.</p> <p class="dwt_publisher"></p> <p class="publishDate">1990-11-21</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">176</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/18244779"> <span id="translatedtitle">Knowledge discovery in <span class="hlt">time</span> <span class="hlt">series</span> databases.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Adding the dimension of time to databases produces <span class="hlt">time</span> <span class="hlt">series</span> databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. In this correspondence, we introduce a general methodology for knowledge discovery in TSDB. The process of knowledge discovery in TSDR includes cleaning and filtering of <span class="hlt">time</span> <span class="hlt">series</span> data, identifying the most important predicting attributes, and extracting a set of association rules that can be used to predict the <span class="hlt">time</span> <span class="hlt">series</span> behavior in the future. Our method is based on signal processing techniques and the information-theoretic fuzzy approach to knowledge discovery. The computational theory of perception (CTP) is used to reduce the set of extracted rules by fuzzification and aggregation. We demonstrate our approach on two types of <span class="hlt">time</span> <span class="hlt">series</span>: stock-market data and weather data. PMID:18244779</p> <div class="credits"> <p class="dwt_author">Last, M; Klein, Y; Kandel, A</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">177</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2005APS..MARV22009K"> <span id="translatedtitle">Entropic Analysis of Electromyography <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We are in the process of assessing the effectiveness of fractal and entropic measures for the diagnostic of low back pain from surface electromyography (EMG) <span class="hlt">time</span> <span class="hlt">series</span>. Surface electromyography (EMG) is used to assess patients with low back pain. In a typical EMG measurement, the voltage is measured every millisecond. We observed back muscle fatiguing during one minute, which results in a <span class="hlt">time</span> <span class="hlt">series</span> with 60,000 entries. We characterize the complexity of <span class="hlt">time</span> <span class="hlt">series</span> by computing the Shannon entropy time dependence. The analysis of the <span class="hlt">time</span> <span class="hlt">series</span> from different relevant muscles from healthy and low back pain (LBP) individuals provides evidence that the level of variability of back muscle activities is much larger for healthy individuals than for individuals with LBP. In general the time dependence of the entropy shows a crossover from a diffusive regime to a regime characterized by long time correlations (self organization) at about 0.01s.</p> <div class="credits"> <p class="dwt_author">Kaufman, Miron; Sung, Paul</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-03-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">178</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2004APS..OSS.B8006Z"> <span id="translatedtitle">Nonlinear Analysis of Surface EMG <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Applications of nonlinear analysis of surface electromyography <span class="hlt">time</span> <span class="hlt">series</span> of patients with and without low back pain are presented. Limitations of the standard methods based on the power spectrum are discussed.</p> <div class="credits"> <p class="dwt_author">Zurcher, Ulrich; Kaufman, Miron; Sung, Paul</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">179</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/servlets/purl/5070920"> <span id="translatedtitle">Detecting nonlinear structure in <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">We describe an approach for evaluating the statistical significance of evidence for nonlinearity in a <span class="hlt">time</span> <span class="hlt">series</span>. The formal application of our method requires the careful statement of a null hypothesis which characterizes a candidate linear process, the generation of an ensemble of surrogate'' data sets which are similar to the original <span class="hlt">time</span> <span class="hlt">series</span> but consistent with the null hypothesis, and the computation of a discriminating statistic for the original and for each of the surrogate data sets. The idea is to test the original <span class="hlt">time</span> <span class="hlt">series</span> against the null hypothesis by checking whether the discriminating statistic computed for the original <span class="hlt">time</span> <span class="hlt">series</span> differs significantly from the statistics computed for each of the surrogate sets. While some data sets very cleanly exhibit low-dimensional chaos, there are many cases where the evidence is sketchy and difficult to evaluate. We hope to provide a framework within which such claims of nonlinearity can be evaluated. 5 refs., 4 figs.</p> <div class="credits"> <p class="dwt_author">Theiler, J.</p> <p class="dwt_publisher"></p> <p class="publishDate">1991-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">180</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011SPIE.8175E..21V"> <span id="translatedtitle">Generalized <span class="hlt">satellite</span> <span class="hlt">image</span> processing: eight years of ocean colour data for any region on earth</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">During the past decade, the world's oceans have been systematically observed by orbiting spectroradiometers such as MODIS and MERIS. These sensors have generated a huge amount of data with unprecedented temporal and spatial coverage. The data is freely available, but not always accessible for marine researchers with no <span class="hlt">image</span> processing experience. In order to provide historical and current oceanographic parameters for the jellyfish forecasting in the JELLYFOR project, a tool for the generalized processing and archiving of <span class="hlt">satellite</span> data was created (GRIMAS). Using this generalized software, the large amount of remote sensing data can be accessed, and parameters such as chlorophyll a concentration (CHL), sea surface temperature (SST) and total suspended matter concentration (TSM) can be extracted and gridded for any region on earth. <span class="hlt">Time-series</span> and climatologies can be easily extracted from this data archive. The products generated can be based on the standard products, as supplied by space agencies, or can be new or regionally calibrated products. All available MODIS and MERIS L2 <span class="hlt">images</span> from an eight year period (2003-2010) were processed in order to create a gridded dataset of CHL, SST (MODIS only) and of TSM for the three JELLYFOR regions. For two of the regions, data for an extended region was also processed. Multi-year composites (climatologies) of <span class="hlt">satellite</span> data and <span class="hlt">time-series</span> can provide a wealth of information for different projects in any region. Climatologies from the two sensors are in good agreement, while significant differences can occur on a scene per scene basis. Total suspended matter concentrations match favourably with in situ data derived from sensors on autonomous buoys. MODIS sea surface temperature corresponds closely to temperature continuously measured underway on research vessels.</p> <div class="credits"> <p class="dwt_author">Vanhellemont, Quinten; Ruddick, Kevin</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-10-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_8");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a 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showDiv("page_11");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">181</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFM.A51A0237K"> <span id="translatedtitle">Ozone <span class="hlt">Time</span> <span class="hlt">Series</span> From GOMOS and SAGE II Measurements</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary"><span class="hlt">Satellite</span> measurements are essential for monitoring changes in the global stratospheric ozone distribution. Both the natural variation and anthropogenic change are strongly dependent on altitude. Stratospheric ozone has been measured from space with good vertical resolution since 1985 by the SAGE II solar occultation instrument. The advantage of the occultation measurement principle is the self-calibration, which is essential to ensuring stable <span class="hlt">time</span> <span class="hlt">series</span>. SAGE II measurements in 1985-2005 have been a valuable data set in investigations of trends in the vertical distribution of ozone. This <span class="hlt">time</span> <span class="hlt">series</span> can now be extended by the GOMOS measurements started in 2002. GOMOS is a stellar occultation instrument and offers, therefore, a natural continuation of SAGE II measurements. In this paper we study how well GOMOS and SAGE II measurements agree with each other in the period 2002-2005 when both instruments were measuring. We detail how the different spatial and temporal sampling of these two instruments affect the conformity of measurements. We study also how the retrieval specifics like absorption cross sections and assumed aerosol modeling affect the results. Various combined <span class="hlt">time</span> <span class="hlt">series</span> are constructed using different estimators and latitude-time grids. We also show preliminary results from a novel <span class="hlt">time</span> <span class="hlt">series</span> analysis based on Markov chain Monte Carlo approach.</p> <div class="credits"> <p class="dwt_author">Kyrola, E. T.; Laine, M.; Tukiainen, S.; Sofieva, V.; Zawodny, J. M.; Thomason, L. W.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">182</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/3hw71122p7u03872.pdf"> <span id="translatedtitle">Forecasting Mortality: A Parameterized <span class="hlt">Time</span> <span class="hlt">Series</span> Approach</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This article links parameterized model mortality schedules with <span class="hlt">time</span> <span class="hlt">series</span> methods to develop forecasts of U.S. mortality\\u000a to the year 2000. The use of model mortality schedules permits a relatively concise representation of the history of mortality\\u000a by age and sex from 1900 to 1985, and the use of modern <span class="hlt">time</span> <span class="hlt">series</span> methods to extend this history forward to the</p> <div class="credits"> <p class="dwt_author">Robert McNown; Andrei Rogers</p> <p class="dwt_publisher"></p> <p class="publishDate">1989-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">183</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1784564"> <span id="translatedtitle">A <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis of Microarray Data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">As the capture and analysis of single-time-point microar- ray expression data becomes routine, investigators are turn- ing to <span class="hlt">time-series</span> expression data to investigate complex gene regulation schemes and metabolic pathways. These in- vestigations are facilitated by algorithms that can extract and cluster related behaviors from the full population of <span class="hlt">time-series</span> behaviors observed. Although traditional clus- tering techniques have shown to</p> <div class="credits"> <p class="dwt_author">Selnur Erdal; Ozgur Ozturk; David L. Armbruster; Hakan Ferhatosmanoglu; William C. Ray</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">184</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/80n242v67621r0r5.pdf"> <span id="translatedtitle">Mining Causal Relationships in Multidimensional <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> are ubiquitous in all domains of human endeavor. They are generated, stored, and manipulated during any kind of\\u000a activity. The goal of this chapter is to introduce a novel approach to mine multidimensional <span class="hlt">time-series</span> data for causal relationships.\\u000a The main feature of the proposed system is supporting discovery of causal relations based on automatically discovered recurring\\u000a patterns in</p> <div class="credits"> <p class="dwt_author">Yasser F. O. Mohammad; Toyoaki Nishida</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">185</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.isprs.org/congresses/istanbul2004/comm7/papers/48.pdf"> <span id="translatedtitle">FOREST CANOPY DENSITY MONITORING, USING <span class="hlt">SATELLITE</span> <span class="hlt">IMAGES</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The increasing use of <span class="hlt">satellite</span> Remote Sensing for civilian use has proved to be the most cost effective means of mapping and monitoring environmental changes in terms of vegetation and non-renewable resources, especially in developing countries. Data can be obtained as frequently as required to provide information for determination of quantitative and qualitative changes in terrain. Forests as one part</p> <div class="credits"> <p class="dwt_author">M. Saei; A. A. Abkar</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">186</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/12624258"> <span id="translatedtitle">Cassini <span class="hlt">imaging</span> of Jupiter's atmosphere, <span class="hlt">satellites</span>, and rings.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The Cassini <span class="hlt">Imaging</span> Science Subsystem acquired about 26,000 <span class="hlt">images</span> of the Jupiter system as the spacecraft encountered the giant planet en route to Saturn. We report findings on Jupiter's zonal winds, convective storms, low-latitude upper troposphere, polar stratosphere, and northern aurora. We also describe previously unseen emissions arising from Io and Europa in eclipse, a giant volcanic plume over Io's north pole, disk-resolved <span class="hlt">images</span> of the <span class="hlt">satellite</span> Himalia, circumstantial evidence for a causal relation between the <span class="hlt">satellites</span> Metis and Adrastea and the main jovian ring, and information on the nature of the ring particles. PMID:12624258</p> <div class="credits"> <p class="dwt_author">Porco, Carolyn C; West, Robert A; McEwen, Alfred; Del Genio, Anthony D; Ingersoll, Andrew P; Thomas, Peter; Squyres, Steve; Dones, Luke; Murray, Carl D; Johnson, Torrence V; Burns, Joseph A; Brahic, Andre; Neukum, Gerhard; Veverka, Joseph; Barbara, John M; Denk, Tilmann; Evans, Michael; Ferrier, Joseph J; Geissler, Paul; Helfenstein, Paul; Roatsch, Thomas; Throop, Henry; Tiscareno, Matthew; Vasavada, Ashwin R</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">187</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=PB86130796"> <span id="translatedtitle">Experimental <span class="hlt">Satellite</span> <span class="hlt">Image</span> Map of Sturgeon Bay, Wisconsin.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">The map, compiled from a Landsat-5 Thematic Mapper <span class="hlt">image</span> recorded on July 18, 1984, illustrates how digital <span class="hlt">satellite</span> <span class="hlt">images</span> can be used to analyze earth resources data. The research that led to the development of the prototype map was aimed at (1) evalua...</p> <div class="credits"> <p class="dwt_author">T. Lillesand T. Lo</p> <p class="dwt_publisher"></p> <p class="publishDate">1985-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">188</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4641298"> <span id="translatedtitle">Suggestions for using <span class="hlt">satellite</span> <span class="hlt">images</span> in K-12 education</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Suggestions are forwarded for using <span class="hlt">satellite</span> <span class="hlt">images</span> in K-12 education. Variable classroom computer capability is accommodated. Example lesson plans are presented. Computer equipment in the classroom is not required for these lessons. Instead, they are designed with the expectation that teachers access and print <span class="hlt">images</span> at home, using photocopies of these prints in the classroom. Lesson plans also allow the</p> <div class="credits"> <p class="dwt_author">James R. Carr</p> <p class="dwt_publisher"></p> <p class="publishDate">1999-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">189</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51184386"> <span id="translatedtitle">Saliency and Gist Features for Target Detection in <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Reliably detecting objects in broad-area overhead or <span class="hlt">satellite</span> <span class="hlt">images</span> has become an increasingly pressing need, as the capabilities for <span class="hlt">image</span> acquisition are growing rapidly. The problem is particularly difficult in the presence of large in- traclass variability, e.g., finding \\</p> <div class="credits"> <p class="dwt_author">Zhicheng Li; Laurent Itti</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">190</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://dx.doi.org/10.1117/12.620097"> <span id="translatedtitle">Potential for calibration of geostationary meteorological <span class="hlt">satellite</span> <span class="hlt">imagers</span> using the Moon</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">Solar-band imagery from geostationary meteorological <span class="hlt">satellites</span> has been utilized in a number of important applications in Earth Science that require radiometric calibration. Because these <span class="hlt">satellite</span> systems typically lack on-board calibrators, various techniques have been employed to establish "ground truth", including observations of stable ground sites and oceans, and cross-calibrating with coincident observations made by instruments with on-board calibration systems. The Moon appears regularly in the margins and corners of full-disk operational <span class="hlt">images</span> of the Earth acquired by meteorological instruments with a rectangular field of regard, typically several times each month, which provides an excellent opportunity for radiometric calibration. The USGS RObotic Lunar Observatory (ROLO) project has developed the capability for on-orbit calibration using the Moon via a model for lunar spectral irradiance that accommodates the geometries of illumination and viewing by a spacecraft. The ROLO model has been used to determine on-orbit response characteristics for several NASA EOS instruments in low Earth orbit. Relative response trending with precision approaching 0.1% per year has been achieved for SeaWiFS as a result of the long <span class="hlt">time-series</span> of lunar observations collected by that instrument. The method has a demonstrated capability for cross-calibration of different instruments that have viewed the Moon. The Moon appears skewed in high-resolution meteorological <span class="hlt">images</span>, primarily due to <span class="hlt">satellite</span> orbital motion during acquisition; however, the geometric correction for this is straightforward. By integrating the lunar disk <span class="hlt">image</span> to an equivalent irradiance, and using knowledge of the sensor's spectral response, a calibration can be developed through comparison against the ROLO lunar model. The inherent stability of the lunar surface means that lunar calibration can be applied to observations made at any time, including retroactively. Archived geostationary <span class="hlt">imager</span> data that contains the Moon can be used to develop response histories for these instruments, regardless of their current operational status.</p> <div class="credits"> <p class="dwt_author">Stone, T. C.; Kieffer, H. H.; Grant, I. F.</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">191</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50709592"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> Clustering Based on ICA for Stock Data Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> clustering is an important task in <span class="hlt">time</span> <span class="hlt">series</span> data mining. Compared to traditional clustering problems, <span class="hlt">time</span> <span class="hlt">series</span> clustering poses additional difficulties. The unique structure of <span class="hlt">time</span> <span class="hlt">series</span> makes many traditional clustering methods unable to apply directly. This paper presents a novel feature-based approach to <span class="hlt">time</span> <span class="hlt">series</span> clustering, which first converts the raw <span class="hlt">time</span> <span class="hlt">series</span> data into feature vectors</p> <div class="credits"> <p class="dwt_author">Chonghui Guo; Hongfeng Jia; Na Zhang</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">192</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008SPIE.7114E...5B"> <span id="translatedtitle">Improved <span class="hlt">satellite</span> <span class="hlt">image</span> compression and reconstruction via genetic algorithms</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A wide variety of signal and <span class="hlt">image</span> processing applications, including the US Federal Bureau of Investigation's fingerprint compression standard [3] and the JPEG-2000 <span class="hlt">image</span> compression standard [26], utilize wavelets. This paper describes new research that demonstrates how a genetic algorithm (GA) may be used to evolve transforms that outperform wavelets for <span class="hlt">satellite</span> <span class="hlt">image</span> compression and reconstruction under conditions subject to quantization error. The new approach builds upon prior work by simultaneously evolving real-valued coefficients representing matched forward and inverse transform pairs at each of three levels of a multi-resolution analysis (MRA) transform. The training data for this investigation consists of actual <span class="hlt">satellite</span> photographs of strategic urban areas. Test results show that a dramatic reduction in the error present in reconstructed <span class="hlt">satellite</span> <span class="hlt">images</span> may be achieved without sacrificing the compression capabilities of the forward transform. The transforms evolved during this research outperform previous start-of-the-art solutions, which optimized coefficients for the reconstruction transform only. These transforms also outperform wavelets, reducing error by more than 0.76 dB at a quantization level of 64. In addition, transforms trained using representative <span class="hlt">satellite</span> <span class="hlt">images</span> do not perform quite as well when subsequently tested against <span class="hlt">images</span> from other classes (such as fingerprints or portraits). This result suggests that the GA developed for this research is automatically learning to exploit specific attributes common to the class of <span class="hlt">images</span> represented in the training population.</p> <div class="credits"> <p class="dwt_author">Babb, Brendan; Moore, Frank; Peterson, Michael; Lamont, Gary</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">193</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1996PhDT.........9H"> <span id="translatedtitle">Pattern Recognition and <span class="hlt">Image</span> Processing of Infrared Astronomical <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The Infrared Astronomical <span class="hlt">Satellite</span> (IRAS) <span class="hlt">images</span> with wavelengths of 60 mu m and 100 mu m contain mainly information on both extra-galactic sources and low-temperature interstellar media. The low-temperature interstellar media in the Milky Way impose a "cirrus" screen of IRAS <span class="hlt">images</span>, especially in <span class="hlt">images</span> with 100 mu m wavelength. This dissertation deals with the techniques of removing the "cirrus" clouds from the 100 mu m band in order to achieve accurate determinations of point sources and their intensities (fluxes). We employ an <span class="hlt">image</span> filtering process which utilizes mathematical morphology and wavelet analysis as the key tools in removing the "cirrus" foreground emission. The filtering process consists of extraction and classification of the size information, and then using the classification results in removal of the cirrus component from each pixel of the <span class="hlt">image</span>. Extraction of size information is the most important step in this process. It is achieved by either mathematical morphology or wavelet analysis. In the mathematical morphological method, extraction of size information is done using the "sieving" process. In the wavelet method, multi-resolution techniques are employed instead. The classification of size information distinguishes extra-galactic sources from cirrus using their averaged size information. The cirrus component for each pixel is then removed by using the averaged cirrus size information. The filtered <span class="hlt">image</span> contains much less cirrus. Intensity alteration for extra-galactic sources in the filtered <span class="hlt">image</span> are discussed. It is possible to retain the fluxes of the point sources when we weigh the cirrus component differently pixel by pixel. The importance of the uni-directional size information extractions are addressed in this dissertation. Such uni-directional extractions are achieved by constraining the structuring elements, or by constraining the sieving process to be sequential. The generalizations of mathematical morphology operations based on the dynamic hit-or-miss transform are presented in this dissertation. The generalized erosion (gamma-erosion) bridges traditional erosion and dilation. It also enriches the morphological operators available in the field of signal and <span class="hlt">image</span> processing. Traditional closing is generalized into gamma -closing, which bridges traditional closing and opening. Properties of gamma-erosion and gamma -closing are discussed. The sieving process is generalized based on gamma-closing, and is bi-directional, with the polarity directly related to the parameter gamma. The size information extractors of morphological methods and wavelet methods are justified quantitatively using a prototype peak with fixed slope. The non-linearity of the sieving process is analyzed. It is shown that the sieving process can approach an approximate linearity at positions where the input signal has sharp peaks (i.e., the slopes are large). The spatial discriminating properties of the size information extractors are also very important.</p> <div class="credits"> <p class="dwt_author">He, Lun Xiong</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">194</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3645413"> <span id="translatedtitle">Highly comparative <span class="hlt">time-series</span> analysis: the empirical structure of <span class="hlt">time</span> <span class="hlt">series</span> and their methods</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific <span class="hlt">time-series</span> data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated <span class="hlt">time</span> <span class="hlt">series</span>, and over 9000 <span class="hlt">time-series</span> analysis algorithms are analysed in this work. We introduce reduced representations of both <span class="hlt">time</span> <span class="hlt">series</span>, in terms of their properties measured by diverse scientific methods, and of <span class="hlt">time-series</span> analysis methods, in terms of their behaviour on empirical <span class="hlt">time</span> <span class="hlt">series</span>, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize <span class="hlt">time-series</span> datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for <span class="hlt">time-series</span> classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine <span class="hlt">time</span> <span class="hlt">series</span>, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in <span class="hlt">time-series</span> analysis for applications across the scientific disciplines.</p> <div class="credits"> <p class="dwt_author">Fulcher, Ben D.; Little, Max A.; Jones, Nick S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">195</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010ems..confE.161D"> <span id="translatedtitle">Homogenising <span class="hlt">time</span> <span class="hlt">series</span>: Beliefs, dogmas and facts</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">For obtaining reliable information about climate change and climate variability the use of high quality data series is essentially important, and one basic tool of quality improvements is the statistical homogenisation of observed <span class="hlt">time</span> <span class="hlt">series</span>. In the recent decades large number of homogenisation methods has been developed, but the real effects of their application on <span class="hlt">time</span> <span class="hlt">series</span> are still not known entirely. The ongoing COST HOME project (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed <span class="hlt">time</span> <span class="hlt">series</span>. This dataset offers much better opportunity than ever to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. The author believes that several old theoretical rules have to be re-evaluated. Some examples of the hot questions, a) Statistically detected change-points can be accepted only with the confirmation of metadata information? b) Do semi-hierarchic algorithms for detecting multiple change-points in <span class="hlt">time</span> <span class="hlt">series</span> function effectively in practise? c) Is it good to limit the spatial comparison of candidate series with up to five other series in the neighbourhood? Empirical results - those from the COST benchmark, and other experiments too - show that real observed <span class="hlt">time</span> <span class="hlt">series</span> usually include several inhomogeneities of different sizes. Small inhomogeneities seem like part of the climatic variability, thus the pure application of classic theory that change-points of observed <span class="hlt">time</span> <span class="hlt">series</span> can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of <span class="hlt">time</span> <span class="hlt">series</span> are usually much closer to the reality, than in raw <span class="hlt">time</span> <span class="hlt">series</span>. The developers and users of homogenisation methods have to bear in mind that the eventual purpose of homogenisation is not to find change-points, but to have the observed <span class="hlt">time</span> <span class="hlt">series</span> with statistical properties those characterise well the climate change and climate variability.</p> <div class="credits"> <p class="dwt_author">Domonkos, P.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">196</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013Chaos..23c3110K"> <span id="translatedtitle">Detecting chaos in irregularly sampled <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Recently, Wiebe and Virgin [Chaos 22, 013136 (2012)] developed an algorithm which detects chaos by analyzing a <span class="hlt">time</span> <span class="hlt">series</span>' power spectrum which is computed using the Discrete Fourier Transform (DFT). Their algorithm, like other <span class="hlt">time</span> <span class="hlt">series</span> characterization algorithms, requires that the <span class="hlt">time</span> <span class="hlt">series</span> be regularly sampled. Real-world data, however, are often irregularly sampled, thus, making the detection of chaotic behavior difficult or impossible with those methods. In this paper, a characterization algorithm is presented, which effectively detects chaos in irregularly sampled <span class="hlt">time</span> <span class="hlt">series</span>. The work presented here is a modification of Wiebe and Virgin's algorithm and uses the Lomb-Scargle Periodogram (LSP) to compute a series' power spectrum instead of the DFT. The DFT is not appropriate for irregularly sampled <span class="hlt">time</span> <span class="hlt">series</span>. However, the LSP is capable of computing the frequency content of irregularly sampled data. Furthermore, a new method of analyzing the power spectrum is developed, which can be useful for differentiating between chaotic and non-chaotic behavior. The new characterization algorithm is successfully applied to irregularly sampled data generated by a model as well as data consisting of observations of variable stars.</p> <div class="credits"> <p class="dwt_author">Kulp, C. W.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">197</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/24089946"> <span id="translatedtitle">Detecting chaos in irregularly sampled <span class="hlt">time</span> <span class="hlt">series</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Recently, Wiebe and Virgin [Chaos 22, 013136 (2012)] developed an algorithm which detects chaos by analyzing a <span class="hlt">time</span> <span class="hlt">series</span>' power spectrum which is computed using the Discrete Fourier Transform (DFT). Their algorithm, like other <span class="hlt">time</span> <span class="hlt">series</span> characterization algorithms, requires that the <span class="hlt">time</span> <span class="hlt">series</span> be regularly sampled. Real-world data, however, are often irregularly sampled, thus, making the detection of chaotic behavior difficult or impossible with those methods. In this paper, a characterization algorithm is presented, which effectively detects chaos in irregularly sampled <span class="hlt">time</span> <span class="hlt">series</span>. The work presented here is a modification of Wiebe and Virgin's algorithm and uses the Lomb-Scargle Periodogram (LSP) to compute a series' power spectrum instead of the DFT. The DFT is not appropriate for irregularly sampled <span class="hlt">time</span> <span class="hlt">series</span>. However, the LSP is capable of computing the frequency content of irregularly sampled data. Furthermore, a new method of analyzing the power spectrum is developed, which can be useful for differentiating between chaotic and non-chaotic behavior. The new characterization algorithm is successfully applied to irregularly sampled data generated by a model as well as data consisting of observations of variable stars. PMID:24089946</p> <div class="credits"> <p class="dwt_author">Kulp, C W</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">198</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://edc.usgs.gov/earthshots/slow/tableofcontents"> <span id="translatedtitle">Earthshots: <span class="hlt">Satellite</span> <span class="hlt">Images</span> of Environmental Change</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">This is an e-book of before-and-after Landsat <span class="hlt">images</span> (1972-present), showing recent environmental events and introducing the concept of remote sensing. Some changes are due to natural causes and some are due to human causes. <span class="hlt">Image</span> topics include agriculture, cities, deserts, disasters, and geology. Each set of <span class="hlt">images</span> includes a detailed description, photographs and maps, a list of references, and a question/answer section.</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">199</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://earthshots.usgs.gov/earthshots/"> <span id="translatedtitle">Earthshots: <span class="hlt">Satellite</span> <span class="hlt">Images</span> of Environmental Change</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">This is an e-book of before-and-after Landsat <span class="hlt">images</span> (1972-present), showing recent environmental events and introducing the concept of remote sensing. Some changes are due to natural causes and some are due to human causes. <span class="hlt">Image</span> topics include agriculture, cities, deserts, disasters, and geology. Each set of <span class="hlt">images</span> includes a detailed description, photographs and maps, a list of references, and a question/answer section.</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate">2011-09-07</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">200</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010EGUGA..12.1852S"> <span id="translatedtitle">A <span class="hlt">time-series</span> analysis of flood disaster around Lena river using Landsat TM/ETM+</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Landsat <span class="hlt">satellite</span> has provided a continuous record of earth observation since 1972, gradually improving sensors (i.e. MSS, TM and ETM+). Already processed archives of Landsat <span class="hlt">image</span> are now available free of charge from the internet. The Landsat <span class="hlt">image</span> of 30 m spatial resolution with multiple spectral bands between 450 and 2350 nm is appropriate for detailed mapping of natural resource at wide geographical areas. However, one of the biggest concerns in the use of Landsat <span class="hlt">image</span> is the uncertainty in the timing of acquisitions. Although detection of land cover change usually requires acquisitions before and after the change, the Landsat <span class="hlt">image</span> is often unavailable because of the long-term intervals (16 days) and variation in atmosphere. Nearly cloud-free <span class="hlt">image</span> is acquired at least once per year (total of 22 or 23 scenes per year). Therefore, it may be difficult to acquire appropriate <span class="hlt">images</span> for monitoring natural disturbances caused at short-term intervals (e.g., flood, forest fire and hurricanes). Our objectives are: (1) to examine whether a <span class="hlt">time-series</span> of Landsat <span class="hlt">image</span> is available for monitoring a flood disaster, and (2) to evaluate the impact and timing of the flood disaster around Lena river in Siberia. A set of Landsat TM/ETM+ <span class="hlt">satellite</span> <span class="hlt">images</span> was used to enable acquisition of cloud-free <span class="hlt">image</span>, although Landsat ETM+ <span class="hlt">images</span> include failure of the Scan Line Corrector (SLC) from May 2003. The overlap area of a <span class="hlt">time</span> <span class="hlt">series</span> of 20 Landsat TM/ETM+ <span class="hlt">images</span> (path 120-122, row 17) from April 2007 to August 2007 was clipped (approximately 33 km × 90 km), and the other area was excluded from the analyses. <span class="hlt">Image</span> classification was performed on each <span class="hlt">image</span> separately using an unsupervised ISODATA method, and each Landsat TM/ETM+ <span class="hlt">image</span> was classified into three land cover types: (1) ice, (2) water, and (3) land. From three land cover types, the area of Lena river was estimated. The area of Lena river dramatically changed after spring breakup. The middle part of Lena river around Tabaga (61.83°N, 129.60°E) was frozen hard until early May 2007. River-ice breakup began in patches on 13 May 2007. Then, the area of Lena river rapidly increased due to overhead flooding on 14 May 2007, and reached the peak on 15 May 2007. In the brief period of one or two days, the area of Lena river was more than twice. After this, the area of Lena river exponentially decreased over three months, and it was quite stable in late August 2007. A <span class="hlt">time-series</span> of Landsat TM/ETM+ <span class="hlt">images</span> could detect these large temporal variations. In addition, the temporal variations in the area of Lena river synchronized with water stage measured in the field. These results indicate that a <span class="hlt">time-series</span> of Landsat TM/ETM+ <span class="hlt">images</span> enables to monitor natural disturbances caused at short-term intervals, although significantly limited to local scales. The requirement of spatial and temporal resolution is often application specific in the context of the desired measurement goals. This type of research and resultant information is critical for the utilization of remote sensing data to the fullest extent.</p> <div class="credits"> <p class="dwt_author">Sakai, Toru; Hatta, Shigemi; Okumura, Makoto; Takeuchi, Wataru; Hiyama, Tetsuya; Inoue, Gen</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-05-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_9");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" 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showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_12");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">201</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3780998"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> regression studies in environmental epidemiology</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> regression studies have been widely used in environmental epidemiology, notably in investigating the short-term associations between exposures such as air pollution, weather variables or pollen, and health outcomes such as mortality, myocardial infarction or disease-specific hospital admissions. Typically, for both exposure and outcome, data are available at regular time intervals (e.g. daily pollution levels and daily mortality counts) and the aim is to explore short-term associations between them. In this article, we describe the general features of <span class="hlt">time</span> <span class="hlt">series</span> data, and we outline the analysis process, beginning with descriptive analysis, then focusing on issues in <span class="hlt">time</span> <span class="hlt">series</span> regression that differ from other regression methods: modelling short-term fluctuations in the presence of seasonal and long-term patterns, dealing with time varying confounding factors and modelling delayed (‘lagged’) associations between exposure and outcome. We finish with advice on model checking and sensitivity analysis, and some common extensions to the basic model.</p> <div class="credits"> <p class="dwt_author">Bhaskaran, Krishnan; Gasparrini, Antonio; Hajat, Shakoor; Smeeth, Liam; Armstrong, Ben</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">202</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1982WRR....18.1011S"> <span id="translatedtitle">ARMA Model Identification of Hydrologic <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In recent years, ARMA models have become popular for modeling geophysical <span class="hlt">time</span> <span class="hlt">series</span> in general and hydrologic <span class="hlt">time</span> <span class="hlt">series</span> in particular. The identification of the appropriate order of the model is an important stage in ARMA modeling. Such model identification is generally based on the autocorrelation and partial autocorrelation functions, although recently improvements have been obtained using the inverse autocorrelation and the inverse partial autocorrelation functions. This paper demonstrates the use of the generalized partial autocorrelation function (GPAF) and the R and S functions of Gray et al. (1978) for ARMA model identification of hydrologic <span class="hlt">time</span> <span class="hlt">series</span>. These functions are defined, and some recursive relations are given for ease of computation. All three functions, when presented in tabular form, have certain characteristic patterns that are useful in ARMA model identification. Several examples are included to demonstrate the usefulness of the proposed identification technique. Actual applications are made using the Saint Lawrence River and Nile River annual streamflow series.</p> <div class="credits"> <p class="dwt_author">Salas, J. D.; Obeysekera, J. T. B.</p> <p class="dwt_publisher"></p> <p class="publishDate">1982-08-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">203</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1432964"> <span id="translatedtitle">Fusion of Multispectral and Panchromatic <span class="hlt">Satellite</span> <span class="hlt">Images</span> Using the Curvelet Transform</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A useful technique in various applications of remote sensing involves the fusion of different types of <span class="hlt">satellite</span> <span class="hlt">images</span>, namely multispectral (MS) <span class="hlt">satellite</span> <span class="hlt">images</span> with a high spectral and low spatial resolution and panchromatic (Pan) <span class="hlt">satellite</span> <span class="hlt">image</span> with a low spectral and high spatial resolution. Recent studies show that wavelet-based <span class="hlt">image</span> fusion provides high-quality spectral content in fused <span class="hlt">images</span>. However, the</p> <div class="credits"> <p class="dwt_author">Myungjin Choi; Rae Young Kim; Myeong-Ryong Nam; Hong Oh Kim</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">204</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/588634"> <span id="translatedtitle">Physical oceanographic <span class="hlt">time-series</span> sensors</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">This article describes a prototype sensor system designed for the acquisition of long-term <span class="hlt">time-series</span> data on oceanographic parameters which can give a picture of climate change features in the physical properties of the oceans. Ship based monitoring systems are extremely expensive to field, and are often subject to availability as specific times. Small profilers which can be moored or allowed to drift can give more complete <span class="hlt">time-series</span> records to look for variations over periods ranging from seasonal to decades in length. The article describes the design and deployment plans for such sensors.</p> <div class="credits"> <p class="dwt_author">Fougere, A.J. [Falmouth Scientific Inc., Cataumet, MA (United States); Toole, J. [Woods Hole Oceanographic Institution, MA (United States)</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-02-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">205</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=AD707509"> <span id="translatedtitle"><span class="hlt">Image</span> Transformations of <span class="hlt">Satellite</span> Cloud Photography.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">The report describes a study program which was concerned with the investigation of photographic <span class="hlt">image</span> transformations. Samples of cloud photographs were digitized using a programmable light source (a computer controlled CRT scanner). The digitized data we...</p> <div class="credits"> <p class="dwt_author">R. L. Peters</p> <p class="dwt_publisher"></p> <p class="publishDate">1970-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">206</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/18866940"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> analysis of barometric pressure data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> of atmospheric pressure data, collected over a period of several years, were analysed to provide undergraduate students with educational examples of application of simple statistical methods of analysis. In addition to basic methods for the analysis of periodicities, a comparison of two forecast models, one based on autoregression algorithms, and the other making use of an artificial neural</p> <div class="credits"> <p class="dwt_author">Paola La Rocca; Daniele Riggi; Francesco Riggi</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">207</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/55137955"> <span id="translatedtitle">Detecting inhomogeneities in pan evaporation <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">There is increasingly growing demand for evaporation data for studies of surface water and energy fluxes, especially for studies which address the impacts of global warming. To serve this purpose, a homogeneous evaporation data are necessary. This paper describes the use of two tests for detecting and adjusting discontinuities in Class A pan evaporation <span class="hlt">time</span> <span class="hlt">series</span> for 28 stations across</p> <div class="credits"> <p class="dwt_author">D. G. C. Kirono</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">208</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009ASPC..411...49P"> <span id="translatedtitle">Event Discovery in Astronomical <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The discovery of events in astronomical <span class="hlt">time</span> <span class="hlt">series</span> data is a non-trival problem. Existing methods address the problem by requiring a fixed-sized sliding window which, given the varying lengths of events and sampling rates, could overlook important events. In this work, we develop probability models for finding the significance of an arbitrary-sized sliding window, and use these probabilities to find areas of significance. In addition, we present our analyses of major surveys archived at the <span class="hlt">Time</span> <span class="hlt">Series</span> Center, part of the Initiative in Innovative Computing at Harvard University. We applied our method to the <span class="hlt">time</span> <span class="hlt">series</span> data in order to discover events such as microlensing or any non-periodic events in the MACHO, OGLE and TAOS surveys. The analysis shows that the method is an effective tool for filtering out nearly 99% of noisy and uninteresting <span class="hlt">time</span> <span class="hlt">series</span> from a large set of data, but still provides full recovery of all known variable events (microlensing, blue star events, supernovae etc.). Furthermore, due to its efficiency, this method can be performed on-the-fly and will be used to analyze upcoming surveys, such as Pan-STARRS.</p> <div class="credits"> <p class="dwt_author">Preston, D.; Protopapas, P.; Brodley, C.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">209</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51128616"> <span id="translatedtitle">Event recognition based on <span class="hlt">time</span> <span class="hlt">series</span> characteristics</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Event recognition and temporal information analysis are important subtasks in information extraction (IE). In this paper, event recognition based on <span class="hlt">time</span> <span class="hlt">series</span> characteristics is proposed. In the pipeline of event recognition, trigger word table is extracted from training corpus and extended based on the field and thesaurus, which is regarded as a priori knowledge. Then event recognition is carried out</p> <div class="credits"> <p class="dwt_author">Fenghuan Li; Dequan Zheng; Tiejun Zhao</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">210</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=https://www.clevelandfed.org/research/workpaper/1984/wp8405.pdf"> <span id="translatedtitle">Velocity: a multivariate <span class="hlt">time-series</span> approach</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The Federal Reserve announces targets for the monetary aggregates that are implicitly conditioned on an assumption about future velocity for each of the monetary aggregates. In this paper we present explicit models of velocity for constructing rigorous tests to determine whether the behavior of velocity has changed from what was expected when the targets were chosen. We use <span class="hlt">time-series</span> methods</p> <div class="credits"> <p class="dwt_author">Michael L. Bagshaw; William T. Gavin</p> <p class="dwt_publisher"></p> <p class="publishDate">1984-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">211</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://oaspub.epa.gov/eims/eimsapi.dispdetail?deid=37224"> <span id="translatedtitle">SO2 EMISSIONS AND <span class="hlt">TIME</span> <span class="hlt">SERIES</span> MODELS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p class="result-summary">The paper describes a <span class="hlt">time</span> <span class="hlt">series</span> model that permits the estimation of the statistical properties of pounds of SO2 per million Btu in stack emissions. It uses measured values for this quantity provided by coal sampling and analysis (CSA), by a continuous emissions monitor (CEM), ...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">212</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/57644263"> <span id="translatedtitle">Modeling <span class="hlt">Time</span> <span class="hlt">Series</span> with Calendar Variation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The modeling of <span class="hlt">time</span> <span class="hlt">series</span> data that include calendar variation is considered. Autocorrelation, trends, and seasonality are modeled by ARIMA models. Trading day variation and Easter holiday variation are modeled by regression-type models. The overall model is a sum of ARIMA and regression models. Methods of identification, estimation, inference, and diagnostic checking are discussed. The ideas are illustrated through actual</p> <div class="credits"> <p class="dwt_author">W. R. Bell; S. C. Hillmer</p> <p class="dwt_publisher"></p> <p class="publishDate">1983-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">213</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/3424356"> <span id="translatedtitle">Multifractal geometry in stock market <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">It has been recently noticed that <span class="hlt">time</span> <span class="hlt">series</span> of returns in stock markets are of multifractal (multiscaling) character. In that context, multifractality has been always evidenced by its statistical signature (i.e., the scaling exponents associated to a related variable). However, a direct geometrical framework, much more revealing about the underlying dynamics, is possible. In this paper, we present the techniques</p> <div class="credits"> <p class="dwt_author">Antonio Turiel; Conrad J. Pérez-Vicente</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">214</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/207400"> <span id="translatedtitle">Assessing Nonstationary <span class="hlt">Time</span> <span class="hlt">Series</span> Using Wavelets</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The discrete wavelet transform has be used extensively in the field of Statistics, mostly in the area of "denoising signals" or nonparametric regression. This thesis provides a new application for the discrete wavelet transform, assessing nonstationary events in <span class="hlt">time</span> <span class="hlt">series</span> -- especially long memory processes. Long memory processes are those which exhibit substantial correlations between events separated by a long</p> <div class="credits"> <p class="dwt_author">Brandon J. Whitcher</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">215</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=ADA028591"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> Modeling of Urban Pollution Levels.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">Research was conducted to find enough <span class="hlt">time</span> <span class="hlt">series</span> data of various types of signals to display the versatility of the modeling technique called Autoregressive-Moving Average (ARMA) (p,q). This was done by obtaining several 24-hour average air pollutant mea...</p> <div class="credits"> <p class="dwt_author">T. S. Lee R. Bethke</p> <p class="dwt_publisher"></p> <p class="publishDate">1974-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">216</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=N9415968"> <span id="translatedtitle">Generation of Artificial Helioseismic <span class="hlt">Time-Series</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">We present an outline of an algorithm to generate artificial helioseismic <span class="hlt">time-series</span>, taking into account as much as possible of the knowledge we have on solar oscillations. The hope is that it will be possible to find the causes of some of the systemati...</p> <div class="credits"> <p class="dwt_author">J. Schou T. M. Brown</p> <p class="dwt_publisher"></p> <p class="publishDate">1993-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">217</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/53026877"> <span id="translatedtitle">Identification of Chaos In Rainfall <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Are point rainfall <span class="hlt">time</span> <span class="hlt">series</span> resulting from a stochastic or a deterministic chaotic pro- cess ? This question is still controversial, but important for the choice of the best suited rainfall simulation approach to generate realistic synthetic series. It will be firstly shown, on a simple theoretical example (the logistic model), that the efficiency of the non linear analysis tools</p> <div class="credits"> <p class="dwt_author">E. Gaume; M. Kolasinski</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">218</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/3709723"> <span id="translatedtitle">Scaling regimes of composite rainfall <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The scaling behaviour of rainfall is analysed both for a range of scales in time and for a given scale in intensity using the statistics of the Fourier transform and the cumulative probability distribution. The analyses are applied to sets of long <span class="hlt">time</span> <span class="hlt">series</span> of daily rainfall (26 (8) files of 45 (90) years at 13 European stations) and sets</p> <div class="credits"> <p class="dwt_author">Klaus Fraedrich; Chris Larnder</p> <p class="dwt_publisher"></p> <p class="publishDate">1993-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">219</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/g6g4746nx4m6u276.pdf"> <span id="translatedtitle">Regent developments in <span class="hlt">time</span> <span class="hlt">series</span> forecasting</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Summary <span class="hlt">Time</span> <span class="hlt">series</span> (extrapolative) forecasting procedures are widely used in business. Their importance has led to the development of new methods of forecasting and research into the evaluation of well-established methods. This paper presents an overview of the major methods of extrapolative forecasting. Secondly it considers the evidence on the relative accuracy of these methods, highlighting the unexpected conclusions arrived</p> <div class="credits"> <p class="dwt_author">R. Fildes</p> <p class="dwt_publisher"></p> <p class="publishDate">1988-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">220</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/52955463"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> Analysis by State Space Methods</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Providing analyses from both classical and Bayesian perspectives, this book presents a comprehensive treatment of the state space approach to <span class="hlt">time</span> <span class="hlt">series</span> analysis. The distinguishing feature of state space time models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that</p> <div class="credits"> <p class="dwt_author">James Durbin; Siem Jan Koopman</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_10");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a 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src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">221</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ars.usda.gov/research/publications/Publications.htm?seq_no_115=225477"> <span id="translatedtitle">Three Analysis Examples for <span class="hlt">Time</span> <span class="hlt">Series</span> Data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p class="result-summary">With improvements in instrumentation and the automation of data collection, plot level repeated measures and <span class="hlt">time</span> <span class="hlt">series</span> data are increasingly available to monitor and assess selected variables throughout the duration of an experiment or project. Records and metadata on variables of interest alone o...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">222</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/57955813"> <span id="translatedtitle">Uses of <span class="hlt">Time-Series</span> Designs for Formative Program Evaluation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Potential uses of <span class="hlt">time-series</span> designs for formative program evaluation are illustrated, and the relationship between single-case experiments and quasi-experimental <span class="hlt">time-series</span> designs is discussed. Four variations of <span class="hlt">time-series</span> design are presented: interrupted <span class="hlt">time-series</span> with follow-up, replicated <span class="hlt">time-series</span>, step-wise <span class="hlt">time-series</span>, and <span class="hlt">time-series</span> with reversal patterns. Advantages and limitations of each design are considered in relation to program evaluation, and attention is given</p> <div class="credits"> <p class="dwt_author">Tony Tripodi; Janice Harrington</p> <p class="dwt_publisher"></p> <p class="publishDate">1979-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">223</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012SPIE.8538E..09Z"> <span id="translatedtitle">Analysis of <span class="hlt">time</span> <span class="hlt">series</span> geospatial data for seismic precursors detection in Vrancea zone</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Rock microfracturing in the Earth's crust preceding a seismic rupture may cause local surface deformation fields, rock dislocations, charged particle generation and motion, electrical conductivity changes, gas emission, fluid diffusion, electrokinetic, piezomagnetic and piezoelectric effects. Space-time anomalies of Earth's emitted radiation (radon in underground water and soil , thermal infrared in spectral range measured from <span class="hlt">satellite</span> months to weeks before the occurrence of earthquakes etc.), ionospheric and electromagnetic anomalies are considered as pre-seismic signals. <span class="hlt">Satellite</span> remote sensing data provides a systematic, synoptic framework for advancing scientific knowledge of the Earth complex system of geophysical phenomena which often lead to seismic hazards. The GPS data provides exciting prospects in seismology including detecting, <span class="hlt">imaging</span> and analyzing signals in regions of seismo-active areas. This paper aims at investigating thermal seismic precursors for some major earthquakes in Romania in Vrancea area, occurred in 1977, 1986, 1990 and 2004, based on <span class="hlt">time</span> <span class="hlt">series</span> <span class="hlt">satellite</span> data provided by NOAA and MODIS. Quantitative analysis of land surface temperature (LST) and ongoing long wave radiation (OLR) data extracted from <span class="hlt">satellite</span> and in-situ monitoring available data recorded before and during the occurrence of earthquake events shows the consistent increasing in the air and land surface in the epicentral locations several days before earthquake, and at different distances of hypocenters function of registered earthquake moment magnitude.</p> <div class="credits"> <p class="dwt_author">Zoran, M. A.; Savastru, R. S.; Savastru, D. M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">224</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012SenIm..13..119R"> <span id="translatedtitle">Simultaneous Fusion and Denoising of Panchromatic and Multispectral <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">To identify objects in <span class="hlt">satellite</span> <span class="hlt">images</span>, multispectral (MS) <span class="hlt">images</span> with high spectral resolution and low spatial resolution, and panchromatic (Pan) <span class="hlt">images</span> with high spatial resolution and low spectral resolution need to be fused. Several fusion methods such as the intensity-hue-saturation (IHS), the discrete wavelet transform, the discrete wavelet frame transform (DWFT), and the principal component analysis have been proposed in recent years to obtain <span class="hlt">images</span> with both high spectral and spatial resolutions. In this paper, a hybrid fusion method for <span class="hlt">satellite</span> <span class="hlt">images</span> comprising both the IHS transform and the DWFT is proposed. This method tries to achieve the highest possible spectral and spatial resolutions with as small distortion in the fused <span class="hlt">image</span> as possible. A comparison study between the proposed hybrid method and the traditional methods is presented in this paper. Different MS and Pan <span class="hlt">images</span> from Landsat-5, Spot, Landsat-7, and IKONOS <span class="hlt">satellites</span> are used in this comparison. The effect of noise on the proposed hybrid fusion method as well as the traditional fusion methods is studied. Experimental results show the superiority of the proposed hybrid method to the traditional methods. The results show also that a wavelet denoising step is required when fusion is performed at low signal-to-noise ratios.</p> <div class="credits"> <p class="dwt_author">Ragheb, Amr M.; Osman, Heba; Abbas, Alaa M.; Elkaffas, Saleh M.; El-Tobely, Tarek A.; Khamis, S.; Elhalawany, Mohamed E.; Nasr, Mohamed E.; Dessouky, Moawad I.; Al-Nuaimy, Waleed; Abd El-Samie, Fathi E.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">225</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008SPIE.7104E...5L"> <span id="translatedtitle">Lake Chapala change detection using <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The Lake Chapala is the largest natural lake in Mexico. It presents a hydrological imbalance problem caused by diminishing intakes from the Lerma River, pollution from said volumes, native vegetation and solid waste. This article presents a study that allows us to determine with high precision the extent of the affectation in both extension and volume reduction of the Lake Chapala in the period going from 1990 to 2007. Through <span class="hlt">satellite</span> <span class="hlt">images</span> this above-mentioned period was monitored. <span class="hlt">Image</span> segmentation was achieved through a Markov Random Field model, extending the application towards edge detection. This allows adequately defining the lake's limits as well as determining new zones within the lake, both changes pertaining the Lake Chapala. Detected changes are related to a hydrological balance study based on measuring variables such as storage volumes, evapotranspiration and water balance. Results show that the changes in the Lake Chapala establish frail conditions which pose a future risk situation. Rehabilitation of the lake requires a hydrologic balance in its banks and aquifers.</p> <div class="credits"> <p class="dwt_author">López-Caloca, Alejandra; Tapia-Silva, Felipe-Omar; Escalante-Ramírez, Boris</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">226</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..15.4312L"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> of global photosynthetic activity and their recurrence properties</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We investigate the fraction of absorbed photosynthetically active radiation (fapar), an index based on multispectral reflectance properties which relates to the carbon uptake by plants. Fapar is available with global coverage from <span class="hlt">satellites</span>. We combine observations from two sensors, SeaWifs on board OrbView-2 and Meris on board Envisat, to produce <span class="hlt">time</span> <span class="hlt">series</span> with 10 days resolution for a period of 14 years (1998-2011) at a spatial resolution of 0.5° latitude x 0.5° longitude. After careful quality checking and gap-filling, more than 30000 individual <span class="hlt">time</span> <span class="hlt">series</span> are obtained covering all terrestrial ecosystems and climates apart from the arctic and major deserts. We augment the fapar dataset with the driving variables air temperature and precipitation at the same spatiotemporal resolution. To characterize the different dynamical behavior as a function of spatial location or distance, we employ Recurrence Quantification Analysis (RQA) and Recurrence Network Analysis (RNA). They deliver detailed information on the nonlinear dynamics in phase space through embedding. RQA and network variables are calculated either for individual <span class="hlt">time</span> <span class="hlt">series</span> using identical recurrence parameters, or bivariate by performing a joint recurrence analysis to quantify the synchronization between fapar and temperature or fapar and precipitation. Taken together, the recurrence analysis might lead to a new partitioning of the terrestrial biosphere which in turn can be compared to existing classifications based on climate and/or vegetation properties.</p> <div class="credits"> <p class="dwt_author">Lange, Holger; Boese, Sven</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">227</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.scipub.org/fulltext/ajes/ajes55599-604.pdf"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> Analysis Model for Rainfall Data in Jordan: Case Study for Using <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Problem statement: <span class="hlt">Time</span> <span class="hlt">series</span> analysis and forecasting has become a major tool in different applications in hydrology and environment al management fields. Among the most effective approaches for analyzing <span class="hlt">time</span> <span class="hlt">series</span> data is the mo del introduced by Box and Jenkins, ARIMA (Autoregressive Integrated Moving Average). Approach: In this study we used Box-Jenkins methodology to build ARIMA model for monthly</p> <div class="credits"> <p class="dwt_author">Naill M. Momani</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">228</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1778732"> <span id="translatedtitle"><span class="hlt">Time-series</span> Bitmaps: a Practical Visualization Tool for Working with Large <span class="hlt">Time</span> <span class="hlt">Series</span> Databases</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The increasing interest in <span class="hlt">time</span> <span class="hlt">series</span> data mining in the last decade has resulted in the introduction of a variety of similarity measures, representations and algorithms. Surprisingly, this massive research effort has had little impact on real world applications. Real world practitioners who work with <span class="hlt">time</span> <span class="hlt">series</span> on a daily basis rarely take advantage of the wealth of tools that</p> <div class="credits"> <p class="dwt_author">Nitin Kumar; Venkata Nishanth Lolla; Eamonn J. Keogh; Stefano Lonardi</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">229</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://earthshots.usgs.gov/tableofcontents"> <span id="translatedtitle">EarthShots: <span class="hlt">Satellite</span> <span class="hlt">Images</span> of Environmental Change</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">EarthShots is an e-book of <span class="hlt">images</span> (1972-present) showing recent environmental events through remotely sensed <span class="hlt">images</span> while also introducing remote sensing techniques. Place-specific case studies offer before-and-after <span class="hlt">satellite</span> imagery as well as descriptive text. Examples of case studies include agriculture along the Nile River Delta, urban development as it impacts the hydrology of the Imperial Valley in California, desertification in Southern Mauritania, the disastrous effects of the Mount St. Helens eruption in Washington, and glacial activity in Hubbard Glacier, Alaska. A world map allows users to access these instances of environmental change by geographic area. Information on remote sensing technology and an overview of the site is provided by a Garden City, Kansas case study. Each set of <span class="hlt">images</span> and text are accompanied by a political/topographic map of the area, detailed information pertaining to the source of the <span class="hlt">satellite</span> <span class="hlt">images</span> and maps, and relevant references.</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-12</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">230</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012SPIE.8320E..53C"> <span id="translatedtitle">GPU accelerated implementation of ultrasound radio-frequency <span class="hlt">time</span> <span class="hlt">series</span> analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The ultrasound radio-frequency (RF) <span class="hlt">time</span> <span class="hlt">series</span> method has been shown to be an effective approach for accurate tissue classification and cancer detection. Previous studies of the RF <span class="hlt">time</span> <span class="hlt">series</span> method were based on a serial MATLAB implementation of feature calculation that involved long running times. Clinical applications of the RF <span class="hlt">time</span> <span class="hlt">series</span> method require a fast and efficient implementation that enables realistic <span class="hlt">imaging</span> studies within a short time frame. In this paper, a parallel implementation of the RF <span class="hlt">time</span> <span class="hlt">series</span> method is developed to support clinical ultrasound <span class="hlt">imaging</span> studies. The parallel implementation uses a Graphics Processing Unit (GPU) to compute the tissue classification features of the RF <span class="hlt">time</span> <span class="hlt">series</span> method. Moreover, efficient graphical representations of the RF <span class="hlt">times</span> <span class="hlt">series</span> features are obtained using the Qt framework. Tread computing is used to concurrently compute and visualize the RF <span class="hlt">time</span> <span class="hlt">series</span> features. The parallel implementation of the RF <span class="hlt">time</span> <span class="hlt">series</span> is evaluated for various configurations of number of frames and number of scan lines per frame acquired in an <span class="hlt">imaging</span> study. Results demonstrate that the parallel implementation enables <span class="hlt">imaging</span> of tissue classification at interactive time. A typical RF <span class="hlt">time</span> <span class="hlt">series</span> of 128 frames and 128 scan lines per frame, the parallel implementation be processed in 0.8128 +/- 0.0420 sec.</p> <div class="credits"> <p class="dwt_author">Chung, Jonathan; Daoud, Mohammad I.; Imani, Farhad; Mousavi, Parvin; Abolmaesumi, Purang</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-02-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">231</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osei.noaa.gov/Events/Fires/US_Southwest/2000/FSMusNM138_N5.jpg"> <span id="translatedtitle">[<span class="hlt">Satellite</span> <span class="hlt">Image</span> of New Mexico Fires May 2000</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">In the aftermath of the New Mexico fires, several resources have been posted online. The first resource, from the National Oceanic and Atmospheric Administration (NOAA), is a color <span class="hlt">satellite</span> <span class="hlt">image</span> (.jpg format) of fires in New Mexico from May 17, including the Cerro Grande fire.</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">232</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/55689980"> <span id="translatedtitle">High-performance isotherm extraction for infrared <span class="hlt">satellite</span> cloud <span class="hlt">image</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The isotherm is an important feature of infrared <span class="hlt">satellite</span> cloud <span class="hlt">images</span> (ISCI), which can directly reveal substantial information of cloud systems. The isotherm extraction of ISCI can remove the redundant information and therefore helps to compress the information of ISCI. In this paper, an isotherm extraction method is presented. The main aggregate of clouds can be segmented based on mathematical</p> <div class="credits"> <p class="dwt_author">Zhengguang Liu; Bing Wu; Yong Liu; Yuan Liu</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">233</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4439239"> <span id="translatedtitle">Typhoon Locating and Reconstruction from the Infrared <span class="hlt">Satellite</span> Cloud <span class="hlt">Image</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Typhoon inflicts terrible damage due to thunderstorms, violent winds, torrential rain, floo ding and extreme high tides. Improving the early typhoon forecast capability is important for the disaster prevention . In recent years, many scholars have made efforts in typhoon center location, typhoon intensity estimation and moving path prediction from the <span class="hlt">satellite</span> <span class="hlt">images</span>. Moreover, it may be useful to transfer</p> <div class="credits"> <p class="dwt_author">Tsang-long Pao; Jun-heng Yeh</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">234</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50548629"> <span id="translatedtitle">Locating the Typhoon Center from the IR <span class="hlt">Satellite</span> Cloud <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The typhoon center location is important for weather forecast and typhoon analysis. However, the appearance of the typhoon center as viewed from the IR <span class="hlt">satellite</span> cloud <span class="hlt">image</span> will have different shape and size at different time. At the genesis stage, the center of a typhoon is quite ambiguous. When it reached to certain strength, there will be an eye appeared</p> <div class="credits"> <p class="dwt_author">Tsang-Long Pao; Jun-Heng Yeh; Min-Yen Liu; Yung-Chang Hsu</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">235</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/55989242"> <span id="translatedtitle">Improved stereo point matching in meteorological <span class="hlt">satellite</span> <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper a method for extracting objects from meteorological stereo <span class="hlt">satellite</span> <span class="hlt">images</span> and matching parts of them is presented. Great emphasis is put on the choice of the threshold value for object extraction. The matching method is based on a modal matching algorithm: the objects to be matched are sampled and ideally turned into elastic objects. A finite element</p> <div class="credits"> <p class="dwt_author">Stefano Dell'Acqua; Paolo Gamba</p> <p class="dwt_publisher"></p> <p class="publishDate">1999-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">236</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/42528225"> <span id="translatedtitle">Urban road extraction from high-resolution optical <span class="hlt">satellite</span> <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In recent years, many approaches have been exploited for automatic urban road extraction. Most of these approaches are based on edge and line detecting algorithms. In this paper, a new integrated system for automatic extraction of main roads in high-resolution optical <span class="hlt">satellite</span> <span class="hlt">images</span> is present. Firstly, a multi-scale greylevel morphological cleaning algorithm is proposed to reduce the grey deviation of</p> <div class="credits"> <p class="dwt_author">Hui Long; Zhongming Zhao</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">237</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://a-a-r-s.org/acrs/proceeding/ACRS2001/Papers/VHR2-06.pdf"> <span id="translatedtitle">IDENTIFICATION OF URBAN CHARACTERISTIC USING IKONOS HIGH RESOLUTION <span class="hlt">SATELLITE</span> <span class="hlt">IMAGE</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Land use patterns are fragile and sophisticated in Taiwan. In order to rapidly derive detail information of land use\\/land cover, it is necessary to employ remote sensing techniques because of its broad area coverage and fast data acquirement. The purposes of this research are to use high-resolution <span class="hlt">satellite</span> <span class="hlt">images</span>, such as IKONOS, to obtain urban land use information, and to</p> <div class="credits"> <p class="dwt_author">Ching-Yi Kuo; Tien-Yin Chou; Re-Yang Lee</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">238</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://publications.nr.no/Larsen_et_al._Mapping_Road_Traffic_Conditions.pdf"> <span id="translatedtitle">MAPPING ROAD TRAFFIC CONDITIONS USING HIGH RESOLUTION <span class="hlt">SATELLITE</span> <span class="hlt">IMAGES</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Construction, development and maintenance of the road network are central activities for several public authorities. In cooperation with the Norwegian road authorities, we have developed an approach for automated vehicle detection and generation of traffic statistics from QuickBird <span class="hlt">images</span>. <span class="hlt">Satellite</span> surveillance serves several obvious advantages over the methods that are being used today, which consist of expensive single-point measurements made</p> <div class="credits"> <p class="dwt_author">S. Ø. Larsen; H. Koren; R. Solberg</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">239</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/27039715"> <span id="translatedtitle"><span class="hlt">Satellite</span> <span class="hlt">Image</span> Analysis for Disaster and Crisis-Management Support</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper describes how multisource <span class="hlt">satellite</span> data and efficient <span class="hlt">image</span> analysis may successfully be used to conduct rapid-mapping tasks in the domain of disaster and crisis-management support. The German Aerospace Center (DLR) has set up a dedicated crosscutting service, which is the so-called \\</p> <div class="credits"> <p class="dwt_author">Stefan Voigt; Thomas Kemper; Torsten Riedlinger; Ralph Kiefl; Klaas Scholte; Harald Mehl</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">240</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..15..361G"> <span id="translatedtitle">Mulstiscale Stochastic Generator of Multivariate Met-Ocean <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The design of maritime structures requires information on sea state conditions that influence its behavior during its life cycle. In the last decades, there has been a increasing development of sea databases (buoys, reanalysis, <span class="hlt">satellite</span>) that allow an accurate description of the marine climate and its interaction with a given structure in terms of functionality and stability. However, these databases have a limited timelength, and its appliance entails an associated uncertainty. To avoid this limitation, engineers try to sample synthetically generated <span class="hlt">time</span> <span class="hlt">series</span>, statistically consistent, which allow the simulation of longer time periods. The present work proposes a hybrid methodology to deal with this issue. It is based in the combination of clustering algorithms (k-means) and an autoregressive logistic regression model (logit). Since the marine climate is directly related to the atmospheric conditions at a synoptic scale, the proposed methodology takes both systems into account; generating simultaneously circulation patterns (weather types) <span class="hlt">time</span> <span class="hlt">series</span> and the sea state <span class="hlt">time</span> <span class="hlt">series</span> related. The generation of these <span class="hlt">time</span> <span class="hlt">series</span> can be summarized in three steps: (1) By applying the clustering technique k-means the atmospheric conditions are classified into a representative number of synoptical patterns (2) Taking into account different covariates involved (such as seasonality, interannual variability, trends or autoregressive term) the autoregressive logistic model is adjusted (3) Once the model is able to simulate weather types <span class="hlt">time</span> <span class="hlt">series</span> the last step is to generate multivariate hourly metocean parameters related to these weather types. This is done by an autoregressive model (ARMA) for each variable, including cross-correlation between them. To show the goodness of the proposed method the following data has been used: Sea Level Pressure (SLP) databases from NCEP-NCAR and Global Ocean Wave (GOW) reanalysis from IH Cantabria. The synthetical met-ocean hourly <span class="hlt">time</span> <span class="hlt">series</span> obtained are statistically consistent (also in terms of extremes and persistence) and keep the temporal dependence structure of the initial stochastic process. This method constitutes a very useful tool in the designing phase of maritime structures or in other branches of coastal engineering.</p> <div class="credits"> <p class="dwt_author">Guanche, Yanira; Mínguez, Roberto; Méndez, Fernando J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_11");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" 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id="NextPageLink" onclick='return showDiv("page_14");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">241</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/42524166"> <span id="translatedtitle">A method for the mapping of the apparent ground brightness using visible <span class="hlt">images</span> from geostationary <span class="hlt">satellites</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper deals with a method for mapping the apparent ground brightness on a pixel basis. It makes use of geostationary <span class="hlt">satellite</span> visible data and generalizes the earlier work of Cano (1982). The detection of clouds larger than one pixel is performed in a <span class="hlt">time</span> <span class="hlt">series</span> by comparing the cloud-induced sensor response to the signal which would occur if the</p> <div class="credits"> <p class="dwt_author">G. Moussu; L. Diabate; D. Obrecht; L. Wald</p> <p class="dwt_publisher"></p> <p class="publishDate">1989-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">242</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..15.8391L"> <span id="translatedtitle">Stratospheric ozone <span class="hlt">time</span> <span class="hlt">series</span> analysis using dynamical linear models</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We describe a hierarchical statistical state space model for ozone profile <span class="hlt">time</span> <span class="hlt">series</span>. The <span class="hlt">time</span> <span class="hlt">series</span> are from <span class="hlt">satellite</span> measurements by the SAGE II and GOMOS instruments spanning years 1984-2012. The original data sets are combined and gridded monthly using 10 degree latitude bands, and covering 20-60 km with 1 km vertical spacing. Model components include level, trend, seasonal effect with solar activity, and quasi biennial oscillations as proxy variables. A typical feature of an atmospheric <span class="hlt">time</span> <span class="hlt">series</span> is that they are not stationary but exhibit both slowly varying and abrupt changes in the distributional properties. These are caused by external forcing such as changes in the solar activity or volcanic eruptions. Further, the data sampling is often nonuniform, there are data gaps, and the uncertainty of the observations can vary. When observations are combined from various sources there will be instrument and retrieval method related biases. The differences in sampling lead also to uncertainties. Standard classical ARIMA type of statistical <span class="hlt">time</span> <span class="hlt">series</span> methods are mostly useless for atmospheric data. A more general approach makes use of dynamical linear models and Kalman filter type of sequential algorithms. These state space models assume a linear relationship between the unknown state of the system and the observations and for the process evolution of the hidden states. They are still flexible enough to model both smooth trends and sudden changes. The above mentioned methodological challenges are discussed, together with analysis of change points in trends related to recovery of stratospheric ozone. This work is part of the ESA SPIN and ozone CCI projects.</p> <div class="credits"> <p class="dwt_author">Laine, Marko; Kyrölä, Erkki</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">243</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.cs.rochester.edu/u/taoli/workshop/program/tdm04_fu.pdf"> <span id="translatedtitle">Financial <span class="hlt">Time</span> <span class="hlt">Series</span> Indexing Based on Low Resolution Clustering</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">One of the major tasks in <span class="hlt">time</span> <span class="hlt">series</span> database application is <span class="hlt">time</span> <span class="hlt">series</span> query. <span class="hlt">Time</span> <span class="hlt">series</span> data is always exist in large data size and high dimensionality. However, different from traditional data, it is impossible to index the <span class="hlt">time</span> <span class="hlt">series</span> in traditional database system. Moreover, <span class="hlt">time</span> <span class="hlt">series</span> with different lengths always coexists in the same database. Therefore, development of a</p> <div class="credits"> <p class="dwt_author">Tak-chung Fu; Fu-lai Chung; Robert Luk; Chak-man Ng</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">244</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/servlets/purl/1093135"> <span id="translatedtitle">Evaluating fusion techniques for multi-sensor <span class="hlt">satellite</span> <span class="hlt">image</span> data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary"><span class="hlt">Satellite</span> <span class="hlt">image</span> data fusion is a topic of interest in many areas including environmental monitoring, emergency response, and defense. Typically any single <span class="hlt">satellite</span> sensor cannot provide all of the benefits offered by a combination of different sensors (e.g., high-spatial but low spectral resolution vs. low-spatial but high spectral, optical vs. SAR). Given the respective strengths and weaknesses of the different types of <span class="hlt">image</span> data, it is beneficial to fuse many types of <span class="hlt">image</span> data to extract as much information as possible from the data. Our work focuses on the fusion of multi-sensor <span class="hlt">image</span> data into a unified representation that incorporates the potential strengths of a sensor in order to minimize classification error. Of particular interest is the fusion of optical and synthetic aperture radar (SAR) <span class="hlt">images</span> into a single, multispectral <span class="hlt">image</span> of the best possible spatial resolution. We explore various methods to optimally fuse these <span class="hlt">images</span> and evaluate the quality of the <span class="hlt">image</span> fusion by using K-means clustering to categorize regions in the fused <span class="hlt">images</span> and comparing the accuracies of the resulting categorization maps.</p> <div class="credits"> <p class="dwt_author">Martin, Benjamin W [ORNL; Vatsavai, Raju [ORNL</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">245</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/22641699"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> Analysis Using Geometric Template Matching.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We present a novel framework for analysing univariate <span class="hlt">time</span> <span class="hlt">series</span> data. At the heart of the approach is a versatile algorithm for measuring the similarity of two segments of <span class="hlt">time</span> <span class="hlt">series</span> called geometric template matching (GeTeM). First, we use GeTeM to compute a similarity measure for clustering and nearest-neighbour classification. Next, we present a semi-supervised learning algorithm that uses the similarity measure with hierarchical clustering in order to improve classification performance when unlabelled training data is available. Finally, we present a boosting framework called TDEBOOST, which uses an ensemble of GeTeM classifiers. TDEBOOST augments the traditional boosting approach with an additional step, in which the features used as inputs to the classifier are adapted at each step to improve the training error. We empirically evaluate the proposed approaches on several datasets, such as accelerometer data collected from wearable sensors and ECG data. PMID:22641699</p> <div class="credits"> <p class="dwt_author">Frank, Jordan; Mannor, Shie; Pineau, Joelle; Precup, Doina</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-05-22</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">246</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/servlets/purl/10103636"> <span id="translatedtitle">Homogeneous global mean temperature <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">A multi-agency effort has been underway to create a homogeneous global baseline data set suitable for studying climate change. The joint release of the Global Historical Climatology Network (GHCN, Vose et al, 1992) version I in 1992 by the National Climatic Data Center/NOAA and the Carbon Dioxide Information Analysis Center/DOE gave the climate research community the largest monthly land surface global climate data set available to date with over 6,000 temperature stations, 39% of which have more than 50 years of data and 10% have more than 100 years of data (see Figure 1). Fifteen different global or regional data sets were merged to create GHCN version 1. Ten of these source data sets have temperature data but only two have been tested and adjusted for inhomogeneities in the station <span class="hlt">time</span> <span class="hlt">series</span>. The majority of the station temperature <span class="hlt">time</span> <span class="hlt">series</span> in GHCN have not been systematically examined for discontinuities.</p> <div class="credits"> <p class="dwt_author">Peterson, T.C.; Easterling, D.R. [National Climatic Data Center, Asheville, NC (United States). Global Climate Lab.; Vose, R.S. [Oak Ridge National Lab., TN (United States); Eischeid, J.K. [Colorado Univ., Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences</p> <p class="dwt_publisher"></p> <p class="publishDate">1993-11-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">247</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009PhRvL.103u4101V"> <span id="translatedtitle">Finding Stationary Subspaces in Multivariate <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Identifying temporally invariant components in complex multivariate <span class="hlt">time</span> <span class="hlt">series</span> is key to understanding the underlying dynamical system and predict its future behavior. In this Letter, we propose a novel technique, stationary subspace analysis (SSA), that decomposes a multivariate <span class="hlt">time</span> <span class="hlt">series</span> into its stationary and nonstationary part. The method is based on two assumptions: (a) the observed signals are linear superpositions of stationary and nonstationary sources; and (b) the nonstationarity is measurable in the first two moments. We characterize theoretical and practical properties of SSA and study it in simulations and cortical signals measured by electroencephalography. Here, SSA succeeds in finding stationary components that lead to a significantly improved prediction accuracy and meaningful topographic maps which contribute to a better understanding of the underlying nonstationary brain processes.</p> <div class="credits"> <p class="dwt_author">von Bünau, Paul; Meinecke, Frank C.; Király, Franz C.; Müller, Klaus-Robert</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-11-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">248</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/18377070"> <span id="translatedtitle">Forbidden patterns in financial <span class="hlt">time</span> <span class="hlt">series</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The existence of forbidden patterns, i.e., certain missing sequences in a given <span class="hlt">time</span> <span class="hlt">series</span>, is a recently proposed instrument of potential application in the study of <span class="hlt">time</span> <span class="hlt">series</span>. Forbidden patterns are related to the permutation entropy, which has the basic properties of classic chaos indicators, such as Lyapunov exponent or Kolmogorov entropy, thus allowing to separate deterministic (usually chaotic) from random series; however, it requires fewer values of the series to be calculated, and it is suitable for using with small datasets. In this paper, the appearance of forbidden patterns is studied in different economical indicators such as stock indices (Dow Jones Industrial Average and Nasdaq Composite), NYSE stocks (IBM and Boeing), and others (ten year Bond interest rate), to find evidence of deterministic behavior in their evolutions. Moreover, the rate of appearance of the forbidden patterns is calculated, and some considerations about the underlying dynamics are suggested. PMID:18377070</p> <div class="credits"> <p class="dwt_author">Zanin, Massimiliano</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">249</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008Chaos..18a3119Z"> <span id="translatedtitle">Forbidden patterns in financial <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The existence of forbidden patterns, i.e., certain missing sequences in a given <span class="hlt">time</span> <span class="hlt">series</span>, is a recently proposed instrument of potential application in the study of <span class="hlt">time</span> <span class="hlt">series</span>. Forbidden patterns are related to the permutation entropy, which has the basic properties of classic chaos indicators, such as Lyapunov exponent or Kolmogorov entropy, thus allowing to separate deterministic (usually chaotic) from random series; however, it requires fewer values of the series to be calculated, and it is suitable for using with small datasets. In this paper, the appearance of forbidden patterns is studied in different economical indicators such as stock indices (Dow Jones Industrial Average and Nasdaq Composite), NYSE stocks (IBM and Boeing), and others (ten year Bond interest rate), to find evidence of deterministic behavior in their evolutions. Moreover, the rate of appearance of the forbidden patterns is calculated, and some considerations about the underlying dynamics are suggested.</p> <div class="credits"> <p class="dwt_author">Zanin, Massimiliano</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-03-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">250</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010EGUGA..12..385K"> <span id="translatedtitle">Noise characteristics in GPS coordinate <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The aim of this paper is to assess the noise characteristics in weekly solutions <span class="hlt">time</span> <span class="hlt">series</span> of residual coordinates for 11 GPS stations, using the Allan variance analysis after a trend and periodic components have been removed by wavelet transform. The noise level is determined by the Allan deviation and the noise type by the slope of the Allan variance graph. The data used are the weekly solution of residual coordinate sets of GPS stations, provided by CODE Analysis Centre of the IGS using the BERNES Software and referred to ITRF2000. The selected stations are well distributed and represent good measurements without observation gaps. The application of wavelet transform on these <span class="hlt">time</span> <span class="hlt">series</span> permits to better assess their trends and periodic components. The three position components (north, east and vertical) are affected by a combination of white and flicker noise. Both white and flicker noise levels are smallest in the east component and the largest in the vertical component.</p> <div class="credits"> <p class="dwt_author">Khelifa, Sofiane; Kahlouche, Salem; Ghezali, Boualem</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">251</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/57081271"> <span id="translatedtitle">Causation Among Socioeconomic <span class="hlt">Time-Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Using annual U. S. <span class="hlt">time</span> <span class="hlt">series</span> data from 1950-1974, formal tests of causation are performed among three socioeconomic phenomena: women's labor force participation rates, fertility rates, and divorce rates. Box-Jenkins and other techniques are employed with Granger-Sims type definition of causation based on leads and lags. Women's labor force participation appears to be causally prior to both fertility and divorce;</p> <div class="credits"> <p class="dwt_author">Robert T. Michael</p> <p class="dwt_publisher"></p> <p class="publishDate">1978-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">252</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/55320696"> <span id="translatedtitle">Applications of nonlinear <span class="hlt">time-series</span> analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this work, new applications in chaos theory and nonlinear <span class="hlt">time-series</span> analysis are explored. Tools for attractor-based analysis are developed along with a complete description of invariant measures. The focus is on the computation of dimension and Lyapunov spectra from a single time-history for the purposes of system identification. The need for accurate attractor reconstruction is stressed as it may</p> <div class="credits"> <p class="dwt_author">Jonathan Michael Nichols</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">253</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/21180099"> <span id="translatedtitle">Turbulencelike Behavior of Seismic <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">We report on a stochastic analysis of Earth's vertical velocity <span class="hlt">time</span> <span class="hlt">series</span> by using methods originally developed for complex hierarchical systems and, in particular, for turbulent flows. Analysis of the fluctuations of the detrended increments of the series reveals a pronounced transition in their probability density function from Gaussian to non-Gaussian. The transition occurs 5-10 hours prior to a moderate or large earthquake, hence representing a new and reliable precursor for detecting such earthquakes.</p> <div class="credits"> <p class="dwt_author">Manshour, P.; Saberi, S. [Department of Physics, Sharif University of Technology, Tehran 11155-9161 (Iran, Islamic Republic of); Sahimi, Muhammad [Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, California 90089-1211 (United States); Peinke, J. [Institute of Physics, Carl von Ossietzky University, D-26111 Oldenburg (Germany); Pacheco, Amalio F. [Department of Theoretical Physics, University of Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza (Spain); Rahimi Tabar, M. Reza [Department of Physics, Sharif University of Technology, Tehran 11155-9161 (Iran, Islamic Republic of); Institute of Physics, Carl von Ossietzky University, D-26111 Oldenburg (Germany); CNRS UMR 6202, Observatoire de la Cote d'Azur, BP 4229, 06304 Nice Cedex 4 (France)</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-09</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">254</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/39899920"> <span id="translatedtitle">On Reynolds Averaging of Turbulence <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We show that validity of Reynolds averaging for estimating the (ensemble) mean of a turbulence <span class="hlt">time</span> <span class="hlt">series</span> requires that the\\u000a series values be both stationary and uncorrelated. In strict statistical terminology, these two conditions are jointly designated as independent identically distributed (i.i.d.). Moreover, we show that when the series values are correlated, knowledge of the correlation between the values is</p> <div class="credits"> <p class="dwt_author">George Treviño; Edgar L. Andreas</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">255</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/368211"> <span id="translatedtitle">Nonparametric Wavelet Methods for Nonstationary <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This article gives an overview on nonparametric modelling of nonstationary <span class="hlt">time</span> <span class="hlt">series</span> andestimation of their time-changing spectral content by modern denoising (smoothing) methods.For the modelling aspect localized decompositions such as various local Fourier (spectral)representations are discussed, among which wavelet and local cosine bases are most prominentones. For the estimation of the possibly time-varying coefficients of these local representationswavelet denoising algorithms</p> <div class="credits"> <p class="dwt_author">Rainer Von Sachs</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">256</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/59239536"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> modeling for terrain profiles</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This dissertation is devoted to build <span class="hlt">time</span> <span class="hlt">series</span> models for non-linear, non-Gaussian and non-stationary terrain profiles. Before this dissertation, most engineers usually assume the terrain profile data is linear, Gaussian and stationary, and then build an ARMA model for the terrain profile. In this dissertation, we use two sets of data collected from the terrain profiles. We proposed statistical tests</p> <div class="credits"> <p class="dwt_author">Jinfeng Wei</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">257</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50798040"> <span id="translatedtitle">Modeling of <span class="hlt">satellite</span> borne TDI CCD pitching <span class="hlt">imaging</span> <span class="hlt">image</span> motion velocity vector</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In order to obtain three-dimensional observation effect with single <span class="hlt">satellite</span> borne time delay and integrate charge coupled device (TDI-CCD), pitching <span class="hlt">imaging</span> is required. More accurate real-time <span class="hlt">image</span> motion velocity vector computational model of space camera is also necessary to make the <span class="hlt">imaging</span> perfect. <span class="hlt">Imaging</span> motion velocity vector computation model must be set up on <span class="hlt">image</span> plane at pitching <span class="hlt">imaging</span>. According</p> <div class="credits"> <p class="dwt_author">Liu Zhang; Shujun Li; Guang Jin; Xiubin Yang</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">258</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1994NPGeo...1..145V"> <span id="translatedtitle">Nonlinear <span class="hlt">time</span> <span class="hlt">series</span> analysis of geomagnetic pulsations</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A detailed nonlinear <span class="hlt">time</span> <span class="hlt">series</span> analysis has been made of two daytime geomagnetic pulsation events being recorded at L'Aquila (Italy, L ? 1.6) and Niemegk (Germany, L ? 2.3). Grassberger and Procaccia algorithm has been used to investigate the dimensionality of physical processes. Surrogate data test and self affinity (fractal) test have been used to exclude coloured noise with power law spectra. Largest Lyapunow exponents have been estimated using the methods of Wolf et al. The problems of embedding, stability of estimations, spurious correlations and nonlinear noise reduction have also been discussed. The main conclusions of this work, which include some new results on the geomagnetic pulsations, are (1) that the April 26, 1991 event, represented by two observatory <span class="hlt">time</span> <span class="hlt">series</span> LAQ1 and NGK1 is probably due to incoherent waves; no finite correlation dimension was found in this case, and (2) that the June 18, 1991 event represented by observatory <span class="hlt">time</span> <span class="hlt">series</span> LAQ2 and NGK2, is due to low dimensional nonlinear dynamics, which include deterministic chaos with correlation dimension D2(NGK2) = 2.25 ± 0.05 and D2(NDK2) = 2.02 ± 0.03, and with positive Lyapunov exponents ?max (LAQ2) = 0.055 ± 0.003 bits/s and ?max (NGK2) = 0.052 ± 0.003 bits/s; the predictability time in both cases is ? 13 s.</p> <div class="credits"> <p class="dwt_author">Vörös, Z.; Verö, J.; Kristek, J.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">259</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1995PhDT.......151C"> <span id="translatedtitle">Sliced Inverse Regression for <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">In this thesis, general nonlinear models for <span class="hlt">time</span> <span class="hlt">series</span> data are considered. A basic form is x _{t} = f(beta_sp{1} {T}X_{t-1},beta_sp {2}{T}X_{t-1},... , beta_sp{k}{T}X_ {t-1},varepsilon_{t}), where x_{t} is an observed <span class="hlt">time</span> <span class="hlt">series</span> data, X_{t } is the first d time lag vector, (x _{t},x_{t-1},... ,x _{t-d-1}), f is an unknown function, beta_{i}'s are unknown vectors, varepsilon_{t }'s are independent distributed. Special cases include AR and TAR models. We investigate the feasibility applying SIR/PHD (Li 1990, 1991) (the sliced inverse regression and principal Hessian methods) in estimating beta _{i}'s. PCA (Principal component analysis) is brought in to check one critical condition for SIR/PHD. Through simulation and a study on 3 well -known data sets of Canadian lynx, U.S. unemployment rate and sunspot numbers, we demonstrate how SIR/PHD can effectively retrieve the interesting low-dimension structures for <span class="hlt">time</span> <span class="hlt">series</span> data.</p> <div class="credits"> <p class="dwt_author">Chen, Li-Sue</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">260</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/6541267"> <span id="translatedtitle"><span class="hlt">Satellites</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">The present work is based on a conference: Natural <span class="hlt">Satellites</span>, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of <span class="hlt">satellites</span>, protosatellite swarms, the tectonics of icy <span class="hlt">satellites</span>, the physical characteristics of <span class="hlt">satellite</span> surfaces, and the interactions of planetary magnetospheres with icy <span class="hlt">satellite</span> surfaces. Other topics include the surface composition of natural <span class="hlt">satellites</span>, the cratering of planetary <span class="hlt">satellites</span>, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the <span class="hlt">satellites</span> of Saturn, small <span class="hlt">satellites</span>, <span class="hlt">satellites</span> of Uranus and Neptune, and the Pluto-Charon system.</p> <div class="credits"> <p class="dwt_author">Burns, J.A.; Matthews, M.S.</p> <p class="dwt_publisher"></p> <p class="publishDate">1986-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_12");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" 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showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_15");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">261</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/524328"> <span id="translatedtitle">Distance Measures for Effective Clustering of ARIMA <span class="hlt">Time-Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Many environmental and socioeconomic <span class="hlt">time-series</span> data can be adequately modeled using Auto-Regressive In- tegrated Moving Average (ARIMA) models. We call such <span class="hlt">time-series</span> ARIMA <span class="hlt">time-series</span>. We consider the problem of clustering ARIMA <span class="hlt">time-series</span>. We propose the use of the Linear Predictive Coding (LPC) cepstrum of <span class="hlt">time-series</span> for clustering ARIMA <span class="hlt">time-series</span>, by using the Euclidean dis- tance between the LPC cepstra of</p> <div class="credits"> <p class="dwt_author">Konstantinos Kalpakis; Dhiral Gada; Vasundhara Puttagunta</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">262</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1998SPIE.3356..608C"> <span id="translatedtitle">Improved Resolution and <span class="hlt">Image</span> Separation (IRIS) <span class="hlt">Satellite</span>: astronomical observations with a large occulting <span class="hlt">satellite</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Natural occultations have long been used to study sources on small angular scales, while coronographs have been used to study high contrast sources. We propose launching the Improved Resolution and <span class="hlt">Image</span> Selection (IRIS) <span class="hlt">Satellite</span>, a large steerable occulting <span class="hlt">satellite</span>. IRIS will have several advantages over standard occulting bodies. IRIS woudl block over 99.8 percent of the visible light from an occulted point source. Because the occultation occurs outside both the telescope and the atmosphere, seeing and optical imperfections do not degrade this performance. If placed in Earth orbit, integration times of 160-1600 s can be achieved from most major telescope sites for objects in over 90 percent of the sky. Alternately, IRIS could be combined with a 2-4 meter space telescope at the Earth-Sun L2 point to yield very long integration times. Applications for IRIS include direct <span class="hlt">imaging</span> of planets around nearby stars, and resolution of micro-lensed <span class="hlt">images</span> of LMC and Galactic bulge stars into distinct <span class="hlt">image</span> pairs. Resolution of microlensed stars would greatly improve our understanding of the massive compact halo objects comprising 20-90 percent of the mass of our galaxy. Direct <span class="hlt">imaging</span> of planets, would enhance our understanding of star formation, formation of planetary systems, and perhaps ultimately help evaluate the probability of extraterrestrial life.</p> <div class="credits"> <p class="dwt_author">Copi, Craig J.; Starkman, Glenn D.</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-08-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">263</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011amos.confE..44J"> <span id="translatedtitle">Interferometric <span class="hlt">Imaging</span> of Geostationary <span class="hlt">Satellites</span>: Signal-to-Noise Considerations</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Geostationary <span class="hlt">satellites</span> are generally too small to <span class="hlt">image</span> at high resolution with conventional single-dish telescopes. Obtaining many resolution elements across a typical geostationary <span class="hlt">satellite</span> body requires a single-dish telescope with a diameter of 10’s of m or more, with a good adaptive optics system. An alternative is to use an optical/infrared interferometer consisting of multiple smaller telescopes in an array configuration. In this paper and companion papers1, 2 we discuss the performance of a common-mount 30-element interferometer. The instrument design is presented by Mozurkewich et al.,1 and <span class="hlt">imaging</span> performance is presented by Schmitt et al.2 In this paper we discuss signal-to-noise ratio for both fringe-tracking and <span class="hlt">imaging</span>. We conclude that the common-mount interferometer is sufficiently sensitive to track fringes on the majority of geostationary <span class="hlt">satellites</span>. We also find that high-fidelity <span class="hlt">images</span> can be obtained after a short integration time of a few minutes to a few tens of minutes.</p> <div class="credits"> <p class="dwt_author">Jorgensen, A.; Schmitt, H.; Mozurkewich, D.; Armstrong, J.; Restaino, S.; Hindsley, R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">264</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFMNH13C1390C"> <span id="translatedtitle">Flood Identification from <span class="hlt">Satellite</span> <span class="hlt">Images</span> Using Artificial Neural Networks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Typhoons and storms hit Taiwan several times every year and they cause serious flood disasters. Because the rivers are short and steep, and their flows are relatively fast with floods lasting only few hours and usually less than one day. Flood identification can provide the flood disaster and extent information to disaster assistance and recovery centers. Due to the factors of the weather, it is not suitable for aircraft or traditional multispectral <span class="hlt">satellite</span>; hence, the most appropriate way for investigating flooding extent is to use Synthetic Aperture Radar (SAR) <span class="hlt">satellite</span>. In this study, back-propagation neural network (BPNN) model and multivariate linear regression (MLR) model are built to identify the flooding extent from SAR <span class="hlt">satellite</span> <span class="hlt">images</span>. The input variables of the BPNN model are Radar Cross Section (RCS) value and mean of the pixel, standard deviation, minimum and maximum of RCS values among its adjacent 3×3 pixels. The MLR model uses two <span class="hlt">images</span> of the non-flooding and flooding periods, and The inputs are the difference between the RCS values of two <span class="hlt">images</span> and the variances among its adjacent 3×3 pixels. The results show that the BPNN model can perform much better than the MLR model. The correct percentages are more than 80% and 73% in training and testing data, respectively. Many misidentified areas are very fragmented and unrelated. In order to reinforce the correct percentage, morphological <span class="hlt">image</span> analysis is used to modify the outputs of these identification models. Through morphological operations, most of the small, fragmented and misidentified areas can be correctly assigned to flooding or non-flooding areas. The final results show that the flood identification of <span class="hlt">satellite</span> <span class="hlt">images</span> has been improved a lot and the correct percentages increases up to more than 90%.</p> <div class="credits"> <p class="dwt_author">Chang, L.; Kao, I.; Shih, K.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">265</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/42528985"> <span id="translatedtitle">Partial unmixing as a tool for single surface class detection and <span class="hlt">time</span> <span class="hlt">series</span> analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper we present the results of <span class="hlt">time</span> <span class="hlt">series</span> analysis for a coal mining region based on partial unmixing. We test the method also known as mixture tuned matched filtering on an eight <span class="hlt">image</span> Landsat 5 TM and Landsat 7 ETM+ <span class="hlt">time</span> <span class="hlt">series</span> covering the period from 1987 to 2003. Common change detection methods often include the comparison of</p> <div class="credits"> <p class="dwt_author">C. Kuenzer; M. Bachmann; A. Mueller; L. Lieckfeld; W. Wagner</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">266</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010TCD.....4.2593B"> <span id="translatedtitle">Longest <span class="hlt">time</span> <span class="hlt">series</span> of glacier mass changes in the Himalaya based on stereo imagery</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Mass loss of Himalayan glaciers has wide-ranging consequences such as declining water resources, sea level rise and an increasing risk of glacial lake outburst floods (GLOFs). The assessment of the regional and global impact of glacier changes in the Himalaya is, however, hampered by a lack of mass balance data for most of the range. Multi-temporal digital terrain models (DTMs) allow glacier mass balance to be calculated since the availability of stereo imagery. Here we present the longest <span class="hlt">time</span> <span class="hlt">series</span> of mass changes in the Himalaya and show the high value of early stereo spy imagery such as Corona (years 1962 and 1970) aerial <span class="hlt">images</span> and recent high resolution <span class="hlt">satellite</span> data (Cartosat-1) to calculate a <span class="hlt">time</span> <span class="hlt">series</span> of glacier changes south of Mt. Everest, Nepal. We reveal that the glaciers are significantly losing mass with an increasing rate since at least ~1970, despite thick debris cover. The specific mass loss is 0.32 ± 0.08 m w.e. a-1, however, not higher than the global average. The spatial patterns of surface lowering can be explained by variations in debris-cover thickness, glacier velocity, and ice melt due to exposed ice cliffs and ponds.</p> <div class="credits"> <p class="dwt_author">Bolch, T.; Pieczonka, T.; Benn, D. I.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">267</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1998PhDT.......209W"> <span id="translatedtitle">Assessing nonstationary <span class="hlt">time</span> <span class="hlt">series</span> using wavelets</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The discrete wavelet transform has be used extensively in the field of Statistics, mostly in the area of "denoising signals" or nonparametric regression. This thesis provides a new application for the discrete wavelet transform, assessing nonstationary events in <span class="hlt">time</span> <span class="hlt">series</span>-especially long memory processes. Long memory processes are those which exhibit substantial correlations between events separated by a long period of time. Departures from stationarity in these heavily autocorrelated <span class="hlt">time</span> <span class="hlt">series</span>, such as an abrupt change in the variance at an unknown location or "bursts" of increased variability, can be detected and accurately located using discrete wavelet transforms-both orthogonal and overcomplete. A cumulative sum of squares method, utilizing a Kolomogorov-Smirnov-type test statistic is applied to this problem. By analyzing a <span class="hlt">time</span> <span class="hlt">series</span> on a scale by scale basis each scale corresponding to a range of frequencies, the ability to detect and locate a sudden change in the variance in the <span class="hlt">time</span> <span class="hlt">series</span> is introduced. Using this same procedure to detect a change in the long memory parameter, when the process variance remains constant, is also briefly investigated. Applications involve Nile River minimum water levels and vertical ocean shear measurements. In the atmospheric sciences, broadband features in the spectrum of recorded <span class="hlt">time</span> <span class="hlt">series</span> have been hypothesized to be nonstationary events; e.g., the Madden-Julian oscillation. The Madden-Julian oscillation is a result of large-scale circulation cells oriented in the equatorial plane from the Indian Ocean to the central Pacific. The oscillation has been noted to have higher frequencies during warm events in El Nino-Southern Oscillation (ENSO) years. The concepts of wavelet covariance and wavelet correlation are introduced and applied to this problem as an alternative to cross-spectrum analysis. The wavelet covariance is shown to decompose the covariance between two stationary processes on a scale by scale basis. Asymptotic normality of estimators of the wavelet covariance and correlation is shown in order to construct approximate confidence intervals. Both quantities are generalized into the wavelet cross-covariance and cross-correlation in order to investigate possible lead/lag relations in bivariate <span class="hlt">time</span> <span class="hlt">series</span> on a scale by scale basis. Atmospheric measurements (such as station pressure and zonal wind speeds) from a single station at Canton Island (2.8sp°S, 171.7sp°W) are put through a wavelet analysis of covariance and are shown to provide similar results to those found in Madden and Julian (1971) and multitaper spectral techniques. To investigate the possible interaction between ENSO activity and the Madden-Julian oscillation, a daily "Southern Oscillation Index" and station pressure series collected from Truk Island (7.4sp°N, 151.8sp°W) are analyzed. The wavelet cross-covariance nicely decomposes the usual cross-covariance into scales which are more easily associated with atmospheric phenomena. The time-varying wavelet variance and covariance are used to investigate possible seasonal effects and changes due to ENSO activity.</p> <div class="credits"> <p class="dwt_author">Whitcher, Brandon J.</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">268</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011PhRvE..83c6202P"> <span id="translatedtitle">Conditions of parameter identification from <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We study the problem of synchronization-based parameters identification of dynamical systems from <span class="hlt">time</span> <span class="hlt">series</span>. Through theoretical analysis and numerical examples, we show that some recent research reports on this issue are not perfect or even incorrect. Long-time full rank and finite-time full rank conditions of Gram matrix are pointed out, which are sufficient for parameters identification of dynamical systems. The influence of additive noise on the proposed parameter identifier is also investigated. The mean filter is used to suppress the estimation fluctuation caused by the noise.</p> <div class="credits"> <p class="dwt_author">Peng, Haipeng; Li, Lixiang; Yang, Yixian; Sun, Fei</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">269</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.bios.edu/research/bats.html"> <span id="translatedtitle">Bermuda Atlantic <span class="hlt">Time-series</span> Study</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">The Bermuda Atlantic <span class="hlt">Time-series</span> study (BATS) was initiated to collect oceanographic data over significantly long time periods. At this website, researchers will find BATS and hydrostation data dealing with hydrographic, chemical, and biological parameters throughout the water column for sites in the Sargasso Sea. Visitors can learn about the first BATS station, Hydrostation S, which was initiated in 1954 by Dr. Henry M. Stommel and has been visited biweekly almost continuously ever since. The website also features numerous questions that the group has proposed dealing with the ocean's physical, geochemical, and biological realms.</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate">2007-09-21</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">270</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009SPIE.7347E..20B"> <span id="translatedtitle">Optimized <span class="hlt">satellite</span> <span class="hlt">image</span> compression and reconstruction via evolution strategies</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper describes the automatic discovery, via an Evolution Strategy with Covariance Matrix Adaptation (CMA-ES), of vectors of real-valued coefficients representing matched forward and inverse transforms that outperform the 9/7 Cohen-Daubechies-Feauveau (CDF) discrete wavelet transform (DWT) for <span class="hlt">satellite</span> <span class="hlt">image</span> compression and reconstruction under conditions subject to quantization error. The best transform evolved during this study reduces the mean squared error (MSE) present in reconstructed <span class="hlt">satellite</span> <span class="hlt">images</span> by an average of 33.78% (1.79 dB), while maintaining the average information entropy (IE) of compressed <span class="hlt">images</span> at 99.57% in comparison to the wavelet. In addition, this evolved transform achieves 49.88% (3.00 dB) average MSE reduction when tested on 80 <span class="hlt">images</span> from the FBI fingerprint test set, and 42.35% (2.39 dB) average MSE reduction when tested on a set of 18 digital photographs, while achieving average IE of 104.36% and 100.08%, respectively. These results indicate that our evolved transform greatly improves the quality of reconstructed <span class="hlt">images</span> without substantial loss of compression capability over a broad range of <span class="hlt">image</span> classes.</p> <div class="credits"> <p class="dwt_author">Babb, Brendan; Moore, Frank; Peterson, Michael</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">271</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/56929479"> <span id="translatedtitle"><span class="hlt">Satellite</span> cloud <span class="hlt">image</span> texture feature extraction based on Gabor wavelet</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In recent years, multi-resolution, multi-channel texture analysis algorithm get extensive attention, and become the important development direction of the texture analysis. According to the <span class="hlt">satellite</span> cloud <span class="hlt">images</span>, this paper put forward the cloud classification method based on texture feature of 2D-Gabor wavelet. Experiments show that the 2D-Gabor wavelet texture features can achieve better classification of clouds, take this method compared</p> <div class="credits"> <p class="dwt_author">Desheng Fu; Lijuan Xu</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">272</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/297068"> <span id="translatedtitle">Structure and Nonrigid Motion Analysis of <span class="hlt">Satellite</span> Cloud <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper proposes a new method for recoveringnonrigid motion and structure of clouds under affineconstraints using time-varying cloud <span class="hlt">images</span> obtainedfrom meteorological <span class="hlt">satellites</span>. This problem is challengingnot only due to the correspondence problembut also due to the lack of depth cues in the 2D cloudimages (scaled orthographic projection). In this paper,affine motion is chosen as a suitable model forsmall local cloud</p> <div class="credits"> <p class="dwt_author">Lin Zhou; Chandra Kambhamettu</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">273</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50817666"> <span id="translatedtitle">Non-Linear Prediction Algorithm of <span class="hlt">Satellite</span> Cloud <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In order to solve the problem of low prediction accuracy of conventional prediction algorithm of <span class="hlt">satellite</span> cloud <span class="hlt">images</span>. The spectrum-space reconstruction and phase-space prediction algorithm are proposed, the algorithm takes full account of that the cloud moves, grows and dissipates in the non-linear and nonstationary process, the mathematical principles of the algorithm and the process of numerical realization is given.</p> <div class="credits"> <p class="dwt_author">Jiang Zhuhui</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">274</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/400560"> <span id="translatedtitle">An Active Testing Model for Tracking Roads in <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We present a new approach for tracking roads from <span class="hlt">satellite</span> <span class="hlt">images</span>, and therebyillustrate a general computational strategy ("active testing") for tracking 1D structuresand other recognition tasks in computer vision. Our approach is related to recent workin active vision on "where to look next" and motivated by the "divide-and-conquer"strategy of parlor games such as "Twenty Questions." We choose "tests" (matchedfilters for</p> <div class="credits"> <p class="dwt_author">Donald Geman; Bruno Jedynak</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">275</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50349569"> <span id="translatedtitle">Potentials for high-resolution <span class="hlt">imaging</span> with small <span class="hlt">satellites</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In the field of space-borne topographic mapping instruments the trend to smaller ground sample distances (GSD) can be observed, making use of the best technology available at the given time. From the 80 m GSD of ERTS (later renamed Landsat-1), the first <span class="hlt">satellite</span> dedicated to civil space-borne Earth surface <span class="hlt">imaging</span> launched in 1972, the GSD now approaches 1 m. Mass</p> <div class="credits"> <p class="dwt_author">Rainer Sandau</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">276</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFM.B12A..07S"> <span id="translatedtitle">Mapping Vineyard Areas Using WORLDVIEW-2 <span class="hlt">Satellite</span> <span class="hlt">Images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The observation of Earth surface from the space has lead to new research possibilities in many fields like agriculture, hydrology, geology, geodesy etc. Different <span class="hlt">satellite</span> <span class="hlt">image</span> data have been used for agricultural monitoring for different scales namely local, regional and global. It is important to monitor agricultural field in local scale to determine the crop yield, diseases, and to provide Farmer Registries. Worldview-2 is a new <span class="hlt">satellite</span> system that could be used for agricultural applications especially in local scale. It is the first high resolution 8-band multispectral commercial <span class="hlt">satellite</span> launched in October 2009. The <span class="hlt">satellite</span> has an altitude of 770 kilometers and its spatial resolution for panchromatic mode and multispectral mode are 46 cm and 1.85 meter, respectively. In addition to red (630 - 690 nm), blue (450 - 510 nm), Green (510 - 580 nm) and Near Infrared (770 - 895 nm) bands, Worldview-2 has four new spectral bands lying on beginning of blue (400 - 450 nm), yellow (585 - 625 nm), red edge (705 - 745 nm) and Near Infrared (860 - 1040 nm) regions of the electromagnetic spectrum. Since Worldview-2 data are comparatively new, there have not been many studies in the literature about the usage of these new data for different applications. In this research, Worldview-2 data were used to delineate the vineyard areas and identify different grape types in Sarkoy, Turkey. Phenological observations of grape fields have been conducted for the last three years over a huge test area owned by the Government Viniculture Institute. Based on the phenological observations, it was found that July and August period is the best data acquisition time for <span class="hlt">satellite</span> data since leaf area index is really higher. In August 2011, Worldview-2 data of the region were acquired and spectral measurements were collected in the field for different grape types using a spectroradiometer. <span class="hlt">Satellite</span> <span class="hlt">image</span> data and spectral measurements were correlated and <span class="hlt">satellite</span> <span class="hlt">image</span> data were classified to determine the location, extent and type of vineyards within the study region. A Digital Elevation Model generated from 1/25.000 scaled topographic maps was used to create slope and aspect map of the research area. These maps and vineyard parcels obtained from remote sensing techniques were integrated into a Geographic Information System. Spatial analyses were conducted in GIS to evaluate the appropriateness of vineyard areas for grape growth. Possible suitable vineyard sites for new plantation were selected through spatial queries to provide useful information to governmental authorities and farmers.</p> <div class="credits"> <p class="dwt_author">Sertel, E.; Ozelkan, E.; Yay, I.; Seker, D. Z.; Ormeci, C.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">277</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/53021434"> <span id="translatedtitle">Automatic Tracking Of Remote Sensing Precipitation Data Using Genetic Algorithm <span class="hlt">Image</span> Registration Based Automatic Morphing: September 1999 Storm Floyd Case Study</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">U Due to the poor temporal sampling by <span class="hlt">satellites</span>, data gaps exist in <span class="hlt">satellite</span> derived <span class="hlt">time</span> <span class="hlt">series</span> of precipitation. This poses a challenge for assimilating rain- fall data into forecast models. To yield a continuous <span class="hlt">time</span> <span class="hlt">series</span>, the classic <span class="hlt">image</span> processing technique of digital <span class="hlt">image</span> morphing has been used. However, the digital morphing technique was applied manually and that is</p> <div class="credits"> <p class="dwt_author">L. Chiu; J. Vongsaard; T. El-Ghazawi; J. Weinman; R. Yang; M. Kafatos</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">278</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009AGUFMIN33D1076A"> <span id="translatedtitle">An Operational Geodatabase Service for Disseminating Raster <span class="hlt">Time</span> <span class="hlt">Series</span> Data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The volume of raster <span class="hlt">time</span> <span class="hlt">series</span> data available for earth science applications is rapidly expanding with improvements in spatial and temporal resolution of earth <span class="hlt">imaging</span> from remote sensing missions. Current dissemination systems are typically designed for mission efficiency rather than supporting the various needs of diverse user communities. This promotes the building of multiple archives of the same dataset by end users who acquire the skills needed to establish and maintain their own data streams. Such processing often becomes a barrier to the adoption of new datasets. This presentation describes the development of an operational geodatabase service for the dissemination of raster <span class="hlt">time</span> <span class="hlt">series</span>. The service combines innovative geocoding schemes with traditional database and geospatial capabilities to facilitate direct access to raster <span class="hlt">time</span> <span class="hlt">series</span>. It includes functionality such as search and retrieval, data segmentation, trend analysis and direct integration into third-party applications using predefined data schemas. The service allows end users to interact with data using simple web-based tools without the need for complex data processing skills. A live implementation of the service is demonstrated using sample global environmental datasets.</p> <div class="credits"> <p class="dwt_author">Asante, K. O.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">279</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50579645"> <span id="translatedtitle">The Research and Application of Content-Based <span class="hlt">Satellite</span> Cloud <span class="hlt">Image</span> Retrieval</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Content-based <span class="hlt">satellite</span> cloud <span class="hlt">image</span> retrieval is a very important problem in <span class="hlt">image</span> processing and analysis field. Traditional <span class="hlt">image</span> retrieval method has some limitation, for realized <span class="hlt">image</span> retrieval accurately and quickly, the CBIR method is an adaptive method. For achieved good retrieval result, some of the pretreatment method of the <span class="hlt">satellite</span> cloud <span class="hlt">image</span> was used, and the experiment effect was shown.</p> <div class="credits"> <p class="dwt_author">Wei ShangGuan; YanLing Hao; YanHong Tang; Yi Zhu</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">280</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2002EGSGA..27.2722G"> <span id="translatedtitle">Identification of Chaos In Rainfall <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Are point rainfall <span class="hlt">time</span> <span class="hlt">series</span> resulting from a stochastic or a deterministic chaotic pro- cess ? This question is still controversial, but important for the choice of the best suited rainfall simulation approach to generate realistic synthetic series. It will be firstly shown, on a simple theoretical example (the logistic model), that the efficiency of the non linear analysis tools dedicated to the identification of chaotic behaviors, espe- cially the correlation dimension method (CDM) , is drastically reduced if the data are disrupted by noise. The results of a CDM based analysis of a eight year point rainfall record with a time resolution of one minute will then be presented. They show actu- ally no clear evidence of a chaotic behavior. They differ from the CDM analysis results obtained with synthetic rainfall <span class="hlt">time</span> <span class="hlt">series</span> produced by a stochastic model generat- ing independent and identically distributed values. These differences are nevertheless more likely due to dependencies between the successive values in the recorded series than to chaos.</p> <div class="credits"> <p class="dwt_author">Gaume, E.; Kolasinski, M.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_13");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a 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showDiv("page_16");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">281</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2426554"> <span id="translatedtitle">Financial <span class="hlt">Time</span> <span class="hlt">Series</span> Segmentation based on Specialized Binary Tree Representation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Segmentation is one of the fundamental components in <span class="hlt">time</span> <span class="hlt">series</span> data mining. One of the uses of the <span class="hlt">time</span> <span class="hlt">series</span> segmentation is trend analysis - to segment the <span class="hlt">time</span> <span class="hlt">series</span> into primitive trends like uptrend and downtrend. In this paper, a <span class="hlt">time</span> <span class="hlt">series</span> segmentation method based on a specialized binary tree representation scheme is proposed; this representation scheme is customized</p> <div class="credits"> <p class="dwt_author">Tak-chung Fu; Fu-lai Chung; Ng Chak-man</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">282</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://dx.doi.org/10.1029/2000GL012698"> <span id="translatedtitle">Singular spectrum analysis for <span class="hlt">time</span> <span class="hlt">series</span> with missing data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">Geophysical <span class="hlt">time</span> <span class="hlt">series</span> often contain missing data, which prevents analysis with many signal processing and multivariate tools. A modification of singular spectrum analysis for <span class="hlt">time</span> <span class="hlt">series</span> with missing data is developed and successfully tested with synthetic and actual incomplete <span class="hlt">time</span> <span class="hlt">series</span> of suspended-sediment concentration from San Francisco Bay. This method also can be used to low pass filter incomplete <span class="hlt">time</span> <span class="hlt">series</span>.</p> <div class="credits"> <p class="dwt_author">Schoellhamer, D. H.</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">283</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/59021393"> <span id="translatedtitle">Investigation of stationarity of hydrologic and climatic <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The principle of stationarity plays an important role in <span class="hlt">time</span> <span class="hlt">series</span> analysis. A key assumption in classical <span class="hlt">time</span> <span class="hlt">series</span> theory is stationarity, that is, the <span class="hlt">time</span> <span class="hlt">series</span> properties do not change with time. Nonstationary <span class="hlt">time</span> <span class="hlt">series</span> can, however, be adequately modeled if the type of nonstationarity can be identified and isolated. Several methods are proposed for the detection of non-stationarity</p> <div class="credits"> <p class="dwt_author">Khaled H Hamed</p> <p class="dwt_publisher"></p> <p class="publishDate">1997-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">284</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1989smsa.proc.....H"> <span id="translatedtitle">High quality <span class="hlt">image</span> compression for rockets and <span class="hlt">satellites</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Installed communication systems for the more recent imagery rockets and <span class="hlt">satellites</span> generally do not have sufficient data link bandwidth to allow imagery transmission. High quality <span class="hlt">image</span> compression can alleviate this problem since 5 to 10 times more <span class="hlt">image</span> data can be transmitted over existing communication systems. Researchers at Utah State University have developed a high quality <span class="hlt">image</span> compression algorithm which has been denoted as statistically lossless. This algorithm combines the good features of the well known vector quantization (VQ) compression and lossless compression. Results are presented in this paper in which different scientific imagery collection systems have been processed using the algorithm. In order to implement this algorithm, a CMOS VLSI chip has been produced which allows a VQ compression system to process 512 x 512 pixel <span class="hlt">images</span> at a rate of 30 frames per second.</p> <div class="credits"> <p class="dwt_author">Harris, Richard W.; Budge, Scott E.; Israelson, Paul D.; Sojka, Jan J.; Roark, William</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">285</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009SPIE.7477E..46P"> <span id="translatedtitle">Iceberg detection using Cosmo-SkyMed <span class="hlt">satellite</span> constellation <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The new constellation of COSMO -SkyMed (CSK) <span class="hlt">satellites</span>, which carry on board a SAR-X instrument, offers a unique opportunity for the study of sea ice distribution in polar regions and for the detection of drifting icebergs. To exploit this new class of SAR <span class="hlt">images</span>, a specific processing scheme, consisting of 4 sequential blocks, was developed. The 4 blocks perform: i) ingestion of the raw <span class="hlt">image</span> into a commercial software for precise geo-location; ii) extraction from the full scene of <span class="hlt">image</span> subsets containing iceberg infested areas; iii) speckle filtering; iv) segmentation by different algorithms taken from a "free and open source software" (FOSS) library. The results of the application of this processing scheme to a CSK <span class="hlt">image</span> of Antarctica containing icebergs are presented and discussed.</p> <div class="credits"> <p class="dwt_author">Parmiggiani, F.; Moctezuma, M.; Morales, D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">286</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013MNRAS.tmp.2546R"> <span id="translatedtitle">Weighted statistical parameters for irregularly sampled <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Unevenly spaced <span class="hlt">time</span> <span class="hlt">series</span> are common in astronomy because of the day-night cycle, weather conditions, dependence on the source position in the sky, allocated telescope time and corrupt measurements, for example, or inherent to the scanning law of <span class="hlt">satellites</span> like Hipparcos and the forthcoming Gaia. Irregular sampling often causes clumps of measurements and gaps with no data which can severely disrupt the values of estimators. This paper aims at improving the accuracy of common statistical parameters when linear interpolation (in time or phase) can be considered an acceptable approximation of a deterministic signal. A pragmatic solution is formulated in terms of a simple weighting scheme, adapting to the sampling density and noise level, applicable to large data volumes at minimal computational cost. Tests on <span class="hlt">time</span> <span class="hlt">series</span> from the Hipparcos periodic catalogue led to significant improvements in the overall accuracy and precision of the estimators with respect to the unweighted counterparts and those weighted by inverse-squared uncertainties. Automated classification procedures employing statistical parameters weighted by the suggested scheme confirmed the benefits of the improved input attributes. The classification of eclipsing binaries, Mira, RR Lyrae, Delta Cephei and Alpha2 Canum Venaticorum stars employing exclusively weighted descriptive statistics achieved an overall accuracy of 92 per cent, about 6 per cent higher than with unweighted estimators.</p> <div class="credits"> <p class="dwt_author">Rimoldini, Lorenzo</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-10-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">287</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013SoPh..tmp..231W"> <span id="translatedtitle"><span class="hlt">Time-Series</span> Analysis of Supergranule Characteristics at Solar Minimum</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Sixty days of Doppler <span class="hlt">images</span> from the Solar and Heliospheric Observatory (SOHO) / Michelson Doppler <span class="hlt">Imager</span> (MDI) investigation during the 1996 and 2008 solar minima have been analyzed to show that certain supergranule characteristics (size, size range, and horizontal velocity) exhibit fluctuations of three to five days. Cross-correlating parameters showed a good, positive correlation between supergranulation size and size range, and a moderate, negative correlation between size range and velocity. The size and velocity do exhibit a moderate, negative correlation, but with a small time lag (less than 12 hours). Supergranule sizes during five days of co-temporal data from MDI and the Solar Dynamics Observatory (SDO) / Helioseismic Magnetic <span class="hlt">Imager</span> (HMI) exhibit similar fluctuations with a high level of correlation between them. This verifies the solar origin of the fluctuations, which cannot be caused by instrumental artifacts according to these observations. Similar fluctuations are also observed in data simulations that model the evolution of the MDI Doppler pattern over a 60-day period. Correlations between the supergranule size and size range <span class="hlt">time-series</span> derived from the simulated data are similar to those seen in MDI data. A simple toy-model using cumulative, uncorrelated exponential growth and decay patterns at random emergence times produces a <span class="hlt">time-series</span> similar to the data simulations. The qualitative similarities between the simulated and the observed <span class="hlt">time-series</span> suggest that the fluctuations arise from stochastic processes occurring within the solar convection zone. This behavior, propagating to surface manifestations of supergranulation, may assist our understanding of magnetic-field-line advection, evolution, and interaction.</p> <div class="credits"> <p class="dwt_author">Williams, Peter E.; Pesnell, W. Dean</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">288</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2006JCoAM.191..206M"> <span id="translatedtitle">Managing distribution changes in <span class="hlt">time</span> <span class="hlt">series</span> prediction</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">When a problem is modeled statistically, a single distribution model is usually postulated that is assumed to be valid for the entire space. Nonetheless, this practice may be somewhat unrealistic in certain application areas, in which the conditions of the process that generates the data may change; as far as we are aware, however, no techniques have been developed to tackle this problem.This article proposes a technique for modeling and predicting this change in <span class="hlt">time</span> <span class="hlt">series</span> with a view to improving estimates and predictions. The technique is applied, among other models, to the hypernormal distribution recently proposed. When tested on real data from a range of stock market indices the technique produces better results that when a single distribution model is assumed to be valid for the entire period of time studied.Moreover, when a global model is postulated, it is highly recommended to select the hypernormal distribution parameter in the same likelihood maximization process.</p> <div class="credits"> <p class="dwt_author">Matias, J. M.; Gonzalez-Manteiga, W.; Taboada, J.; Ordonez, C.</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">289</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008BoLMe.128..303T"> <span id="translatedtitle">On Reynolds Averaging of Turbulence <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We show that validity of Reynolds averaging for estimating the (ensemble) mean of a turbulence <span class="hlt">time</span> <span class="hlt">series</span> requires that the series values be both stationary and uncorrelated. In strict statistical terminology, these two conditions are jointly designated as independent identically distributed ( i. i. d.). Moreover, we show that when the series values are correlated, knowledge of the correlation between the values is needed to obtain a reliable estimate of the mean. Last, we contend that a viable averaging algorithm must be Reynolds number ( Re) dependent, requiring one version for low Re (Gaussian) turbulence and another for high Re (non-Gaussian) turbulence. Alternatively the median (as opposed to the mean) is recommended as a measure of the central tendency of the turbulence probability density function.</p> <div class="credits"> <p class="dwt_author">Treviño, George; Andreas, Edgar L.</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">290</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/21583207"> <span id="translatedtitle">OPTIMAL <span class="hlt">TIME-SERIES</span> SELECTION OF QUASARS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">We present a novel method for the optimal selection of quasars using <span class="hlt">time-series</span> observations in a single photometric bandpass. Utilizing the damped random walk model of Kelly et al., we parameterize the ensemble quasar structure function in Sloan Stripe 82 as a function of observed brightness. The ensemble model fit can then be evaluated rigorously for and calibrated with individual light curves with no parameter fitting. This yields a classification in two statistics-one describing the fit confidence and the other describing the probability of a false alarm-which can be tuned, a priori, to achieve high quasar detection fractions (99% completeness with default cuts), given an acceptable rate of false alarms. We establish the typical rate of false alarms due to known variable stars as {approx}<3% (high purity). Applying the classification, we increase the sample of potential quasars relative to those known in Stripe 82 by as much as 29%, and by nearly a factor of two in the redshift range 2.5 < z < 3, where selection by color is extremely inefficient. This represents 1875 new quasars in a 290 deg{sup 2} field. The observed rates of both quasars and stars agree well with the model predictions, with >99% of quasars exhibiting the expected variability profile. We discuss the utility of the method at high redshift and in the regime of noisy and sparse data. Our <span class="hlt">time-series</span> selection complements well-independent selection based on quasar colors and has strong potential for identifying high-redshift quasars for Baryon Acoustic Oscillations and other cosmology studies in the LSST era.</p> <div class="credits"> <p class="dwt_author">Butler, Nathaniel R.; Bloom, Joshua S. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States)</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-03-15</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">291</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AJ....141...93B"> <span id="translatedtitle">Optimal <span class="hlt">Time-series</span> Selection of Quasars</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We present a novel method for the optimal selection of quasars using <span class="hlt">time-series</span> observations in a single photometric bandpass. Utilizing the damped random walk model of Kelly et al., we parameterize the ensemble quasar structure function in Sloan Stripe 82 as a function of observed brightness. The ensemble model fit can then be evaluated rigorously for and calibrated with individual light curves with no parameter fitting. This yields a classification in two statistics—one describing the fit confidence and the other describing the probability of a false alarm—which can be tuned, a priori, to achieve high quasar detection fractions (99% completeness with default cuts), given an acceptable rate of false alarms. We establish the typical rate of false alarms due to known variable stars as lsim3% (high purity). Applying the classification, we increase the sample of potential quasars relative to those known in Stripe 82 by as much as 29%, and by nearly a factor of two in the redshift range 2.5 < z < 3, where selection by color is extremely inefficient. This represents 1875 new quasars in a 290 deg2 field. The observed rates of both quasars and stars agree well with the model predictions, with >99% of quasars exhibiting the expected variability profile. We discuss the utility of the method at high redshift and in the regime of noisy and sparse data. Our <span class="hlt">time-series</span> selection complements well-independent selection based on quasar colors and has strong potential for identifying high-redshift quasars for Baryon Acoustic Oscillations and other cosmology studies in the LSST era.</p> <div class="credits"> <p class="dwt_author">Butler, Nathaniel R.; Bloom, Joshua S.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-03-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">292</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007WRR....43.9419S"> <span id="translatedtitle">Spatiotemporal topological kriging of runoff <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper proposes a geostatistical method for estimating runoff <span class="hlt">time</span> <span class="hlt">series</span> in ungauged catchments. The method conceptualizes catchments as space-time filters and exploits the space-time correlations of runoff along the stream network topology. We hence term the method topological kriging or top kriging. It accounts for hydrodynamic and geomorphologic dispersion as well as routing and estimates runoff as a weighted average of the observed runoff in neighboring catchments. Top kriging is tested by cross validation on 10 years of hourly runoff data from 376 catchments in Austria and separately for a subset of these data, the Innviertel region. The median Nash-Sutcliffe efficiency of hourly runoff in the Innviertel region is 0.87 but decreases to 0.75 for the entire data set. For a subset of 208 catchments, the median efficiency of daily runoff estimated by top kriging is 0.87 as compared to 0.67 for estimates of a deterministic runoff model that uses regionalized model parameters. The much better performance of top kriging is because it avoids rainfall data errors and avoids the parameter identifiability issues of traditional runoff models. The analyses indicate that the kriging variance can be used for identifying catchments with potentially poor estimates. The Innviertel region is used to examine the kriging weights for nested and nonnested catchments and to compare various variants of top kriging. The spatial kriging variant generally performs better than the more complex spatiotemporal kriging and spatiotemporal cokriging variants. It is argued that top kriging may be preferable to deterministic runoff models for estimating runoff <span class="hlt">time</span> <span class="hlt">series</span> in ungauged catchments, provided stream gauge density is high and there is no need to account for causal rainfall-runoff processes. Potential applications include the estimation of flow duration curves in a region and near-real time mapping of runoff.</p> <div class="credits"> <p class="dwt_author">SkøIen, Jon Olav; BlöSchl, Günter</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-09-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">293</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1984PhDT........25V"> <span id="translatedtitle">Use of Geostationary <span class="hlt">Satellite</span> <span class="hlt">Images</span> for Interactive Meteorological Analysis.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The southern oceans are data-sparse regions and this is especially true for the middle-latitude and sub -Antarctic zones. To obtain a better meteorological data coverage full use must be made of available geostationary <span class="hlt">satellite</span> data. Data received from Meteosat II, which views the Atlantic Ocean has been available since June 1981 and is available for analysis of the charts of the tropical and middle latitude zones of this ocean. The Man Computer Interactive Data Access System (MCIDAS) provides the means to display and manipulate Meteosat II <span class="hlt">images</span>. This motivated the development of the Bogus Using Meteosat MCIDAS System (BUMMS). The BUMMS is capable of displaying a meteorological field superimposed over a Meteosat II <span class="hlt">image</span>, both being transformed to polar stereographic coordinates. Bogus (pseudo) data are entered via the video display, followed by execution of a revised 1000-300 mb thickness analysis and the corresponding field of omega values obtained from a two-level omega equation model. The 1000-300 mb thickness field is interactively modified by the BUMMS until agreement is obtained with the cloud features displayed by the <span class="hlt">satellite</span> <span class="hlt">image</span>. Omega equation vertical velocities are used to verify the fit between the thickness field and the cloud features. The BUMMS operate well within the time constraints imposed by the operational procedure. Modifications to the thickness field are introduced by applying <span class="hlt">Satellite</span> <span class="hlt">Image</span> Analysis Rules (SIAR) consisting of 10 guidelines based on sound meteorological theory. Seven case studies are discussed. In each case the thickness field is modified using the SIAR. The modified thickness field forms the basis of a new 10-level analysis which becomes the input to a Primitive Equation Nested Model (PENEST). Prognostic 36-hour output from this model is compared with a verification analysis as well as the original prognoses. Results indicate positive improvement in the prognoses using the BUMMS procedure and the SIAR. Full operational implementation of the BUMMS can be recommended.</p> <div class="credits"> <p class="dwt_author">van Heerden, Johan</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">294</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009amos.confE..75J"> <span id="translatedtitle">Simulations of Non-resolved, Infrared <span class="hlt">Imaging</span> of <span class="hlt">Satellites</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Simulations of near-infrared, non-resolved <span class="hlt">imaging</span> of earth-orbiting <span class="hlt">satellites</span> during nighttime and daytime were created to consider the feasibility of such observations. By using the atmospheric radiative transfer code MODTRAN (MODerate resolution atmospheric TRANsmission), we incorporate site-specific mean weather conditions for several possible locations. In general, the dominant effect to be modeled is the sky radiance, which has a strong dependence upon the solar angle and the nature of the distribution of aerosols. Other significant effects included in the model are telescope design, camera design, and detector selection. The simulations are used in turn to predict the signal to noise ratio (SNR) in standard astronomical filter bands for several test cases of <span class="hlt">satellite</span>-sun-observer geometries. The SNR model is then used to devise a method to design an optimal filter band for these observations.</p> <div class="credits"> <p class="dwt_author">Jim, K.; Kuluhiwa, K.; Scott, B. Knox, R.; Frith, J.; Gibson, B.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">295</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/40916658"> <span id="translatedtitle">Forecasting tree mortality using change metrics derived from MODIS <span class="hlt">satellite</span> data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Insect-induced tree mortality can cause substantial timber and carbon losses in many regions of the world. There is a critical need to forecast tree mortality to guide forest management decisions. Moderate Resolution <span class="hlt">Imaging</span> Spectroradiometer (MODIS) <span class="hlt">satellite</span> imagery provides inexpensive and frequent coverage over large areas, facilitating forest health monitoring. This study examined <span class="hlt">time</span> <span class="hlt">series</span> of MODIS <span class="hlt">satellite</span> <span class="hlt">images</span> to forecast</p> <div class="credits"> <p class="dwt_author">Jan Verbesselt; Andrew Robinson; Christine Stone; Darius Culvenor</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">296</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50742178"> <span id="translatedtitle">Achieving EMC in high frequency and high power switching environment on Radar <span class="hlt">Imaging</span> <span class="hlt">Satellite</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Satellite</span> deck provides a challenging electro magnetic (EM) environment as the overall volume available is limited and a number of DC-DC converters and clocks are present. Add to this high frequency and high power switching the electro magnetic interference (EMI) scenario couldn't be worse. Radar <span class="hlt">imaging</span> <span class="hlt">satellite</span> (RISAT) India's first <span class="hlt">satellite</span> with day night <span class="hlt">imaging</span> capability, slated for launch by</p> <div class="credits"> <p class="dwt_author">G. V. C. Rajan; V. B. Pramod</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">297</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50581124"> <span id="translatedtitle">The Research of <span class="hlt">Satellite</span> Cloud <span class="hlt">Image</span> Recognition Base on Variational Method and Texture Feature Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Recently, the development of <span class="hlt">satellite</span> cloud <span class="hlt">image</span> processing technology has become very quick; the research aspects concentrate on judge the cloud type and classify the cloud mainly. These <span class="hlt">image</span> processing methods relate to the subject category like <span class="hlt">image</span> processing and pattern recognition etc; it has become one of the fields of most quickly development in the research of <span class="hlt">satellite</span> <span class="hlt">image</span></p> <div class="credits"> <p class="dwt_author">Wei Shangguan; Yanling Hao; Zhizhong Lu; Peng Wu</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">298</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/48448322"> <span id="translatedtitle">Mapping Cropping Practices Using MODIS <span class="hlt">Time</span> <span class="hlt">Series</span>: Harnessing the Data Explosion</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The MODIS (Moderate Resolution <span class="hlt">Imaging</span> Spectroradiometer) 250m EVI dataset provides a valuable ongoing means of characterising\\u000a and monitoring changes in land use and resource condition. However the multiple factors that influence a <span class="hlt">time</span> <span class="hlt">series</span> of greenness\\u000a data make the data difficult to analyse and interpret. Without prior knowledge, underlying models for <span class="hlt">time</span> <span class="hlt">series</span> in a given\\u000a remote sensing <span class="hlt">image</span> are</p> <div class="credits"> <p class="dwt_author">Peter Tan; Leo Lymburner; Medhavy Thankappan; Adam Lewis</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">299</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..1413278M"> <span id="translatedtitle">Spatial Data Exploring by <span class="hlt">Satellite</span> <span class="hlt">Image</span> Distributed Processing</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. <span class="hlt">Satellite</span> <span class="hlt">images</span> 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 <span class="hlt">satellite</span> <span class="hlt">image</span> 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 <span class="hlt">satellite</span> <span class="hlt">image</span> 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 <span class="hlt">image</span> 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. Also this Web application does not require any kind of install for what the house-hold user is concerned. It is a remote application which may be accessed over the Internet. Currently the GreenLand application is available through the BSC-OS Portal provided by the enviroGRIDS FP7 project [3]. This presentation aims to highlight the challenges and issues of flexible description of the Grid based processing of <span class="hlt">satellite</span> <span class="hlt">images</span>, interoperability with other software platforms available in the portal, as well as the particular requirements of the Black Sea related use cases.</p> <div class="credits"> <p class="dwt_author">Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">300</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007AcAau..60..622D"> <span id="translatedtitle">NNIC—neural network <span class="hlt">image</span> compressor for <span class="hlt">satellite</span> positioning system</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We have developed an algorithm, based on novel techniques of data compression and neural networks for the optimal positioning of a <span class="hlt">satellite</span>. The algorithm is described in detail, and examples of its application are given. The heart of this algorithm is the program NNIC—neural network <span class="hlt">image</span> compressor. This program was developed for compression color and grayscale <span class="hlt">images</span> with artificial neural networks (ANNs). NNIC applies three different methods for compression. Two of them are based on neural networks architectures—multilayer perceptron and kohonen network. The third is based on a widely used method of discrete cosine transform, the basis for the JPEG standard. The program also serves as a tool for determining numerical and visual quality parameters of compression and comparison between different methods. A number of advantages and disadvantages of the compression using ANNs were discovered in the course of the present research, some of them presented in this report. The thrust of the report is the discussion of ANNs implementation problems for modern platforms, such as a <span class="hlt">satellite</span> positioning system that include intensive <span class="hlt">image</span> flowing and processing.</p> <div class="credits"> <p class="dwt_author">Danchenko, Pavel; Lifshits, Feodor; Orion, Itzhak; Koren, Sion; Solomon, Alan D.; Mark, Shlomo</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-04-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_14");' href="#" title="Previous Page"> <img 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showDiv("page_5");' href="#">5</a> <a onClick='return showDiv("page_6");' href="#">6</a> <a onClick='return showDiv("page_7");' href="#">7</a> <a onClick='return showDiv("page_8");' href="#">8</a> <a onClick='return showDiv("page_9");' href="#">9</a> <a onClick='return showDiv("page_10");' href="#">10</a> <a onClick='return showDiv("page_11");' href="#">11</a> <a onClick='return showDiv("page_12");' href="#">12</a> <a onClick='return showDiv("page_13");' href="#">13</a> <a onClick='return showDiv("page_14");' href="#">14</a> <a onClick='return showDiv("page_15");' href="#">15</a> <a style="font-weight: bold;">16</a> <a onClick='return showDiv("page_17");' href="#">17</a> <a onClick='return showDiv("page_18");' href="#">18</a> <a onClick='return showDiv("page_19");' href="#">19</a> <a onClick='return showDiv("page_20");' href="#">20</a> <a onClick='return showDiv("page_21");' href="#">21</a> <a onClick='return showDiv("page_22");' href="#">22</a> <a onClick='return showDiv("page_23");' href="#">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_17");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">301</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=149370"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> modeling for syndromic surveillance</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">Background Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED) visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. Methods Using <span class="hlt">time-series</span> methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA) residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. Results Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. Conclusions <span class="hlt">Time</span> <span class="hlt">series</span> methods applied to historical ED utilization data are an important tool for syndromic surveillance. Accurate forecasting of emergency department total utilization as well as the rates of particular syndromes is possible. The multiple models in the system account for both long-term and recent trends, and an integrated alarms strategy combining these two perspectives may provide a more complete picture to public health authorities. The systematic methodology described here can be generalized to other healthcare settings to develop automated surveillance systems capable of detecting anomalies in disease patterns and healthcare utilization.</p> <div class="credits"> <p class="dwt_author">Reis, Ben Y; Mandl, Kenneth D</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">302</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=N7910672"> <span id="translatedtitle">The Benefits of Using Short Interval <span class="hlt">Satellite</span> <span class="hlt">Images</span> to Derive Winds for Tropical Cyclones.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">During the 1975, 1976, and 1977, NOAA's National Environmental <span class="hlt">Satellite</span> Service and NASA's Goddard Space Flight Center conducted a cooperative program to determine the optimum resolution and frequency of <span class="hlt">satellite</span> <span class="hlt">images</span> for deriving winds to study and f...</p> <div class="credits"> <p class="dwt_author">E. Rodgers R. C. Gentry W. E. Shenk V. Oliver</p> <p class="dwt_publisher"></p> <p class="publishDate">1978-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">303</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009AIPC.1159..217A"> <span id="translatedtitle">Comparative Analysis on <span class="hlt">Time</span> <span class="hlt">Series</span> with Included Structural Break</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The <span class="hlt">time</span> <span class="hlt">series</span> analysis (ARIMA models) is a good approach for identification of <span class="hlt">time</span> <span class="hlt">series</span>. But, if we have structural break in the <span class="hlt">time</span> <span class="hlt">series</span>, we cannot create only one model of <span class="hlt">time</span> <span class="hlt">series</span>. Further more, if we don't have enough data between two structural breaks, it's impossible to create valid <span class="hlt">time</span> <span class="hlt">series</span> models for identification of the <span class="hlt">time</span> <span class="hlt">series</span>. This paper explores the possibility of identification of the inflation process dynamics via of the system-theoretic, by means of both Box-Jenkins ARIMA methodologies and artificial neural networks.</p> <div class="credits"> <p class="dwt_author">Andreeski, Cvetko J.; Vasant, Pandian</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-08-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">304</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007PhyA..375..633W"> <span id="translatedtitle">Phase correlation of foreign exchange <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Correlation of foreign exchange rates in currency markets is investigated based on the empirical data of USD/DEM and USD/JPY exchange rates for a period from February 1 1986 to December 31 1996. The return of exchange <span class="hlt">time</span> <span class="hlt">series</span> is first decomposed into a number of intrinsic mode functions (IMFs) by the empirical mode decomposition method. The instantaneous phases of the resultant IMFs calculated by the Hilbert transform are then used to characterize the behaviors of pricing transmissions, and the correlation is probed by measuring the phase differences between two IMFs in the same order. From the distribution of phase differences, our results show explicitly that the correlations are stronger in daily time scale than in longer time scales. The demonstration for the correlations in periods of 1986 1989 and 1990 1993 indicates two exchange rates in the former period were more correlated than in the latter period. The result is consistent with the observations from the cross-correlation calculation.</p> <div class="credits"> <p class="dwt_author">Wu, Ming-Chya</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">305</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012PhRvE..86a1114P"> <span id="translatedtitle">Extraction of stochastic dynamics from <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We present a method for the reconstruction of the dynamics of processes with discrete time. The <span class="hlt">time</span> <span class="hlt">series</span> from such a system is described by a stochastic recurrence equation, the continuous form of which is known as the Langevin equation. The deterministic f and stochastic g components of the stochastic equation are directly extracted from the measurement data with the assumption that the noise has finite moments and has a zero mean and a unit variance. No other information about the noise distribution is needed. This is contrary to the usual Langevin description, in which the additional assumption that the noise is Gaussian (?-correlated) distributed as necessary. We test the method using one dimensional deterministic systems (the tent and logistic maps) with Gaussian and with Gumbel noise. In addition, results for human heart rate variability are presented as an example of the application of our method to real data. The differences between cardiological cases can be observed in the properties of the deterministic part f and of the reconstructed noise distribution.</p> <div class="credits"> <p class="dwt_author">Petelczyc, M.; ?ebrowski, J. J.; Gac, J. M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-07-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">306</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23005375"> <span id="translatedtitle">Extraction of stochastic dynamics from <span class="hlt">time</span> <span class="hlt">series</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We present a method for the reconstruction of the dynamics of processes with discrete time. The <span class="hlt">time</span> <span class="hlt">series</span> from such a system is described by a stochastic recurrence equation, the continuous form of which is known as the Langevin equation. The deterministic f and stochastic g components of the stochastic equation are directly extracted from the measurement data with the assumption that the noise has finite moments and has a zero mean and a unit variance. No other information about the noise distribution is needed. This is contrary to the usual Langevin description, in which the additional assumption that the noise is Gaussian (?-correlated) distributed as necessary. We test the method using one dimensional deterministic systems (the tent and logistic maps) with Gaussian and with Gumbel noise. In addition, results for human heart rate variability are presented as an example of the application of our method to real data. The differences between cardiological cases can be observed in the properties of the deterministic part f and of the reconstructed noise distribution. PMID:23005375</p> <div class="credits"> <p class="dwt_author">Petelczyc, M; ?ebrowski, J J; Gac, J M</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-07-11</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">307</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013SolE....4...23R"> <span id="translatedtitle">Reprocessed height <span class="hlt">time</span> <span class="hlt">series</span> for GPS stations</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Precise weekly positions of 403 Global Positioning System (GPS) stations located worldwide are obtained by reprocessing GPS data of these stations for the time span from 4 January 1998 until 29 December 2007. The processing algorithms and models used as well as the solution and results obtained are presented. Vertical velocities of 266 GPS stations having a tracking history longer than 2.5 yr are computed; 107 of them are GPS stations located at tide gauges (TIGA observing stations). The vertical velocities calculated in this study are compared with the estimates from the co-located tide gauges and other GPS solutions. The formal errors of the estimated vertical velocities are 0.01-0.80 mm yr-1. The vertical velocities of our solution agree within 1 mm yr-1 with those of the recent solutions (ULR5 and ULR3) of the Université de La Rochelle for about 67-75 per cent of the common stations. Examples of typical behaviour of station height changes are given and interpreted. The derived height <span class="hlt">time</span> <span class="hlt">series</span> and vertical motions of continuous GPS at tide gauges stations can be used for correcting the vertical land motion in tide gauge records of sea level changes.</p> <div class="credits"> <p class="dwt_author">Rudenko, S.; Schön, N.; Uhlemann, M.; Gendt, G.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">308</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/292224"> <span id="translatedtitle">Nonparametric <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis, a selectiv review with examples</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Nonlinear <span class="hlt">time</span> <span class="hlt">series</span> analysis has drawn much attention recently and has shown to be the appropriate tool in many fields, in particular in financial <span class="hlt">time</span> <span class="hlt">series</span> analysis. Following the principle of \\</p> <div class="credits"> <p class="dwt_author">W. HARDLE; Rong Chen</p> <p class="dwt_publisher"></p> <p class="publishDate">1995-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">309</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1640310"> <span id="translatedtitle">Multitaper spectrum estimation for <span class="hlt">time</span> <span class="hlt">series</span> with gaps</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Gaps in <span class="hlt">time</span> <span class="hlt">series</span> can produce spurious features in power spectrum estimates. These artifacts can be suppressed by averaging spectrum estimates obtained by first windowing the <span class="hlt">time</span> <span class="hlt">series</span> with a collection of orthogonal tapers. Such \\</p> <div class="credits"> <p class="dwt_author">Imola K. Fodor; Philip B. Stark</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">310</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011SPIE.8044E..18C"> <span id="translatedtitle">A low cost thermal infrared hyperspectral <span class="hlt">imager</span> for small <span class="hlt">satellites</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The traditional model for space-based earth observations involves long mission times, high cost, and long development time. Because of the significant time and monetary investment required, riskier instrument development missions or those with very specific scientific goals are unlikely to successfully obtain funding. However, a niche for earth observations exploiting new technologies in focused, short lifetime missions is opening with the growth of the small <span class="hlt">satellite</span> market and launch opportunities for these <span class="hlt">satellites</span>. These low-cost, short-lived missions provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off the shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCOR), to demonstrate the ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power efficient thermal hyperspectral <span class="hlt">imager</span> with electronics contained in a pressure vessel to enable the use of COTS electronics, and will be compatible with small <span class="hlt">satellite</span> platforms. The sensor, called Thermal Hyperspectral <span class="hlt">Imager</span> (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230-meter pixels with 20 wavenumber spectral resolution from a 400-km orbit.</p> <div class="credits"> <p class="dwt_author">Crites, S. T.; Lucey, P. G.; Wright, R.; Garbeil, H.; Horton, K. A.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">311</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/17335120"> <span id="translatedtitle">Automated <span class="hlt">time</span> <span class="hlt">series</span> forecasting for biosurveillance.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">For robust detection performance, traditional control chart monitoring for biosurveillance is based on input data free of trends, day-of-week effects, and other systematic behaviour. <span class="hlt">Time</span> <span class="hlt">series</span> forecasting methods may be used to remove this behaviour by subtracting forecasts from observations to form residuals for algorithmic input. We describe three forecast methods and compare their predictive accuracy on each of 16 authentic syndromic data streams. The methods are (1) a non-adaptive regression model using a long historical baseline, (2) an adaptive regression model with a shorter, sliding baseline, and (3) the Holt-Winters method for generalized exponential smoothing. Criteria for comparing the forecasts were the root-mean-square error, the median absolute per cent error (MedAPE), and the median absolute deviation. The median-based criteria showed best overall performance for the Holt-Winters method. The MedAPE measures over the 16 test series averaged 16.5, 11.6, and 9.7 for the non-adaptive regression, adaptive regression, and Holt-Winters methods, respectively. The non-adaptive regression forecasts were degraded by changes in the data behaviour in the fixed baseline period used to compute model coefficients. The mean-based criterion was less conclusive because of the effects of poor forecasts on a small number of calendar holidays. The Holt-Winters method was also most effective at removing serial autocorrelation, with most 1-day-lag autocorrelation coefficients below 0.15. The forecast methods were compared without tuning them to the behaviour of individual series. We achieved improved predictions with such tuning of the Holt-Winters method, but practical use of such improvements for routine surveillance will require reliable data classification methods. PMID:17335120</p> <div class="credits"> <p class="dwt_author">Burkom, Howard S; Murphy, Sean Patrick; Shmueli, Galit</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-09-30</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">312</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/42733988"> <span id="translatedtitle">Interrupted <span class="hlt">Time-Series</span> Designs for Evaluating Health Communication Campaigns</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Interrupted <span class="hlt">time</span> <span class="hlt">series</span> (ITS) constitute a class of powerful quasi-experimental designs for evaluating health communication campaigns. This article: 1) describes the basic elements of <span class="hlt">time-series</span> designs in general and interrupted <span class="hlt">time-series</span> designs in particular; 2) discusses briefly some of the more widely recognized ITS designs in order of increasing methodological rigor; 3) introduces the two major types of <span class="hlt">time-series</span> statistical</p> <div class="credits"> <p class="dwt_author">Philip Palmgreen</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">313</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/12637529"> <span id="translatedtitle">Estimating measurement noise in a <span class="hlt">time</span> <span class="hlt">series</span> by exploiting nonstationarity</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A measured <span class="hlt">time</span> <span class="hlt">series</span> is always corrupted by noise to some degree. Even a rough estimation of the level of noise contained in an experimental <span class="hlt">time</span> <span class="hlt">series</span> is valuable. This is so, for example, when one wishes to apply techniques from nonlinear dynamics theory to analyze a <span class="hlt">time</span> <span class="hlt">series</span>. However, this is a very difficult problem. It becomes even harder</p> <div class="credits"> <p class="dwt_author">J. Hu; J. B. Gao; K. D. White</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">314</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1659229"> <span id="translatedtitle">An evolutionary approach to pattern-based <span class="hlt">time</span> <span class="hlt">series</span> segmentation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> data, due to their numerical and continuous nature, are difficult to process, analyze, and mine. However, these tasks become easier when the data can be transformed into meaningful symbols. Most recent works on <span class="hlt">time</span> <span class="hlt">series</span> only address how to identify a given pattern from a <span class="hlt">time</span> <span class="hlt">series</span> and do not consider the problem of identifying a suitable set</p> <div class="credits"> <p class="dwt_author">Fu-lai Chung; Tak-chung Fu; Vincent T. Y. Ng; Robert W. P. Luk</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">315</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/13330775"> <span id="translatedtitle">Representing financial <span class="hlt">time</span> <span class="hlt">series</span> based on data point importance</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Recently, the increasing use of <span class="hlt">time</span> <span class="hlt">series</span> data has initiated various research and development attempts in the field of data and knowledge management. <span class="hlt">Time</span> <span class="hlt">series</span> data is characterized as large in data size, high dimensionality and update continuously. Moreover, the <span class="hlt">time</span> <span class="hlt">series</span> data is always considered as a whole instead of individual numerical fields. Indeed, a large set of time</p> <div class="credits"> <p class="dwt_author">Tak-Chung Fu; Korris Fu-Lai Chung; Robert Wing Pong Luk; Chak-man Ng</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">316</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/524387"> <span id="translatedtitle">Evolutionary <span class="hlt">Time</span> <span class="hlt">Series</span> Segmentation for Stock Data Mining</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Stock data in the form of multiple <span class="hlt">time</span> <span class="hlt">series</span> are difficult to process, analyze and mine. However, when they can be transformed into meaningful symbols like technical patterns, it becomes easier. Most recent work on <span class="hlt">time</span> <span class="hlt">series</span> queries concentrates only on how to identify a given pattern from a <span class="hlt">time</span> <span class="hlt">series</span>. Researchers do not consider the problem of identifying a</p> <div class="credits"> <p class="dwt_author">Korris Fu-lai Chung; Tak-chung Fu; Robert W. P. Luk; Vincent T. Y. Ng</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">317</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50780796"> <span id="translatedtitle">Level change detection in <span class="hlt">time</span> <span class="hlt">series</span> using higher order statistics</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Changes in the level of a <span class="hlt">time</span> <span class="hlt">series</span> are usually attributed to an intervention that interrupts its evolution. The resulting <span class="hlt">time</span> <span class="hlt">series</span> are referred to as interrupted <span class="hlt">time</span> <span class="hlt">series</span> and they are studied in order to measure, e.g. the impact of new laws or medical treatments. In the present paper a heuristic method for level change detection in non-stationary time</p> <div class="credits"> <p class="dwt_author">C. S. Hilas; I. T. Rekanos; S. K. Goudos; P. A. Mastorocostas; J. N. Sahalos</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">318</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2522482"> <span id="translatedtitle">Causal Wiener filter banks for periodically correlated <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A causal filter bank implementation of the cyclic Wiener filter for periodically correlated (PC) <span class="hlt">time</span> <span class="hlt">series</span> is developed. By converting a PC <span class="hlt">time</span> <span class="hlt">series</span> into a vector-valued wide-sense stationary (WSS) <span class="hlt">time</span> <span class="hlt">series</span>, the existing literature on factorization of spectral density matrices may be utilized. However, because PC analytic and equivalent baseband signals are generally complex improper, spectral factorization algorithms must</p> <div class="credits"> <p class="dwt_author">Mark S. Spurbeck; Peter J. Schreier</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">319</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50306144"> <span id="translatedtitle">Trend <span class="hlt">time</span> <span class="hlt">series</span> modeling and forecasting with neural networks</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Despite its great importance, there has been no general consensus on how to model the trends in <span class="hlt">time</span> <span class="hlt">series</span> data. Compared to traditional approaches, neural networks have shown some promise in <span class="hlt">time</span> <span class="hlt">series</span> forecasting. This paper investigates how to best model trend <span class="hlt">time</span> <span class="hlt">series</span> using neural networks. Four strategies (raw data, raw data with time index, detrending, and differencing) are</p> <div class="credits"> <p class="dwt_author">Min Qi; G. Peter Zhang</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">320</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2490314"> <span id="translatedtitle">Hybrid neural network models for hydrologic <span class="hlt">time</span> <span class="hlt">series</span> forecasting</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The need for increased accuracies in <span class="hlt">time</span> <span class="hlt">series</span> forecasting has motivated the researchers to develop innovative models. In this paper, a new hybrid <span class="hlt">time</span> <span class="hlt">series</span> neural network model is proposed that is capable of exploiting the strengths of traditional <span class="hlt">time</span> <span class="hlt">series</span> approaches and artificial neural networks (ANNs). The proposed approach consists of an overall modelling framework, which is a combination</p> <div class="credits"> <p class="dwt_author">Ashu Jain; Avadhnam Madhav Kumar</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_15");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' 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showDiv("page_18");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">321</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/41107664"> <span id="translatedtitle">Combining neural network model with seasonal <span class="hlt">time</span> <span class="hlt">series</span> ARIMA model</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper proposes a hybrid forecasting model, which combines the seasonal <span class="hlt">time</span> <span class="hlt">series</span> ARIMA (SARIMA) and the neural network back propagation (BP) models, known as SARIMABP. This model was used to forecast two seasonal <span class="hlt">time</span> <span class="hlt">series</span> data of total production value for Taiwan machinery industry and the soft drink <span class="hlt">time</span> <span class="hlt">series</span>. The forecasting performance was compared among four models, i.e.,</p> <div class="credits"> <p class="dwt_author">Fang-Mei Tseng; Hsiao-Cheng Yu; Gwo-Hsiung Tzeng</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">322</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/55523379"> <span id="translatedtitle">Nonlinear <span class="hlt">time</span> <span class="hlt">series</span> analysis of solar and stellar data</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Nonlinear <span class="hlt">time</span> <span class="hlt">series</span> analysis was developed to study chaotic systems. Its utility was investigated for the study of solar and stellar data <span class="hlt">time</span> <span class="hlt">series</span>. Sunspot data are the longest astronomical <span class="hlt">time</span> <span class="hlt">series</span>, and it reflects the long-term variation of the solar magnetic field. Due to periods of low solar activity, such as the Maunder minimum, and the solar cycle's quasiperiodicity,</p> <div class="credits"> <p class="dwt_author">Nada Jevtic</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">323</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=https://tspace.library.utoronto.ca/bitstream/1807/9144/1/st05036.pdf"> <span id="translatedtitle">Daily air pollution <span class="hlt">time</span> <span class="hlt">series</span> analysis of Isfahan City</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Different <span class="hlt">time</span> <span class="hlt">series</span> analysis of daily air pollution of Isfahan city were performed in this study. Descriptive analysis showed different long-term variation of daily air pollution. High persistence in daily air pollution <span class="hlt">time</span> <span class="hlt">series</span> were identified using autocorrelation function except for SO2 which seemed to be short memory. Standardized air pollution index (SAPI) <span class="hlt">time</span> <span class="hlt">series</span> were also calculated to compare</p> <div class="credits"> <p class="dwt_author">R. Modarres; A. Khosravi Dehkordi</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">324</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.bde.es/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/00/Fic/dt0012e.pdf"> <span id="translatedtitle">Notes on <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis, ARIMA Models and Signal Extraction</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Present practice in applied <span class="hlt">time</span> <span class="hlt">series</span> work, mostly at economic policy or data producing agencies, relies heavily on using moving average filters to estimate unobserved components in <span class="hlt">time</span> <span class="hlt">series</span>, such as the seasonally adjusted series, the trend, or the cycle. The purpose of the present paper is to provide an informal introduction to the <span class="hlt">time</span> <span class="hlt">series</span> analysis tools and concepts</p> <div class="credits"> <p class="dwt_author">Regina Kaiser; Agustín Maravall</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">325</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4768674"> <span id="translatedtitle">Clustering of biological <span class="hlt">time</span> <span class="hlt">series</span> by cepstral coefficients based distances</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Clustering of stationary <span class="hlt">time</span> <span class="hlt">series</span> has become an important tool in many scientific applications, like medicine, finance, etc. <span class="hlt">Time</span> <span class="hlt">series</span> clustering methods are based on the calculation of suitable similarity measures which identify the distance between two or more <span class="hlt">time</span> <span class="hlt">series</span>. These measures are either computed in the time domain or in the spectral domain. Since the computation of time</p> <div class="credits"> <p class="dwt_author">Alexios Savvides; Vassilis J. Promponas; Konstantinos Fokianos</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">326</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/5097882"> <span id="translatedtitle">T3: On Mapping Text To <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We investigate if the mapping between text and <span class="hlt">time</span> <span class="hlt">series</span> data is feasible such that relevant data mining problems in text can find their counterparts in <span class="hlt">time</span> <span class="hlt">series</span> (and vice versa). As a preliminary work, we present the T3 (Text To <span class="hlt">Time</span> <span class="hlt">series</span>) framework that utilizes dierent</p> <div class="credits"> <p class="dwt_author">Tao Yang; Dongwon Lee</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">327</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.vldb.org/pvldb/2/vldb09-793.pdf"> <span id="translatedtitle">Anticipatory DTW for Efficient Similarity Search in <span class="hlt">Time</span> <span class="hlt">Series</span> Databases</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Time</span> <span class="hlt">series</span> arise in many dierent applications in the form of sensor data, stocks data, videos, and other time-related information. Analysis of this data typically requires search- ing for similar <span class="hlt">time</span> <span class="hlt">series</span> in a database. Dynamic Time Warping (DTW) is a widely used high-quality distance mea- sure for <span class="hlt">time</span> <span class="hlt">series</span>. As DTW is computationally expensive, ecient algorithms for fast computation</p> <div class="credits"> <p class="dwt_author">Ira Assent; Marc Wichterich; Ralph Krieger; Hardy Kremer; Thomas Seidl</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">328</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/57685460"> <span id="translatedtitle">Temporal disaggregation and restricted forecasting of multiple population <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This article presents some applications of <span class="hlt">time-series</span> procedures to solve two typical problems that arise when analyzing demographic information in developing countries: (1) unavailability of annual <span class="hlt">time</span> <span class="hlt">series</span> of population growth rates (PGRs) and their corresponding population <span class="hlt">time</span> <span class="hlt">series</span> and (2) inappropriately defined population growth goals in official population programs. These problems are considered as situations that require combining information</p> <div class="credits"> <p class="dwt_author">E. Silva; V. M. Guerrero; D. Peña</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">329</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/54478449"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span>, neural networks and the future of the Sun</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The prediction of <span class="hlt">time</span> <span class="hlt">series</span> is discussed in general, with particular attention given to the use of feed forward neural networks in predicting solar-terrestrial <span class="hlt">time</span> <span class="hlt">series</span>. Firstly, a variety of methods of describing and predicting <span class="hlt">time</span> <span class="hlt">series</span> are reviewed, and in so doing are placed in mutual context. Feed forward neural networks, which have received so much attention in recent</p> <div class="credits"> <p class="dwt_author">A. J. Conway</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">330</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/v565034w5p67hklr.pdf"> <span id="translatedtitle">PRTSM: Pattern recognition-based <span class="hlt">time</span> <span class="hlt">series</span> modeler</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, a new approach using pattern recognition techniques is suggested for <span class="hlt">time</span> <span class="hlt">series</span> modeling which means identification of a <span class="hlt">time</span> <span class="hlt">series</span> into one of autoregressive moving-average models. Its main recipe is that pattern is derived from a <span class="hlt">time</span> <span class="hlt">series</span> and classified into a suitable model via a notion of pattern matching. The pattern is obtained from extended sample</p> <div class="credits"> <p class="dwt_author">Kun Chang Lee; Sung Joo Park</p> <p class="dwt_publisher"></p> <p class="publishDate">1989-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">331</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010AGUFM.G22B..02M"> <span id="translatedtitle">Eyjafjallajökull Magma Monitoring From <span class="hlt">Time</span> <span class="hlt">Series</span> Data of TerraSAR-X</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The 2010 eruption of Eyjafjallajökull volcano and the resulting ash cloud highlights the need for research on Icelandic volcanoes. While most of the interest was sparked by the closure of air space over much of Europe, the potentially life-threatening consequences for the people living in the area directly beneath the volcano alone are incentive enough to better understand volcanic processes. Katla volcano is directly adjacent to Eyjafjallajökull volcano, and historically has been more active and produced larger eruptions. The consequences of an eruption at Katla could therefore be much more severe than those witnessed this spring at Eyjafjallajökull. Timely prediction of an impending eruption would greatly reduce the severity of these consequences, which is one of the ultimate goals of volcanic research. After a period of quiescence since a sill intrusion in 1999-2000, a subtle deformation signal was again detected at Eyjafjallajökull, beginning in the summer of 2009, at a continuous GPS station on the southern flank. We immediately began tasking the TerraSAR-X <span class="hlt">satellite</span> to acquire SAR <span class="hlt">images</span> every 11 days, giving a <span class="hlt">time</span> <span class="hlt">series</span> of SAR <span class="hlt">images</span> prior to the eruption with unprecedented temporal sampling (although interrupted by snow during the winter). Here we present the results of InSAR <span class="hlt">time</span> <span class="hlt">series</span> analysis of this data set. After correcting for DEM errors and reduction of atmospheric signal we find a number of signals that we tentatively interpret as a combination of magma movement, elastic response to snow melting and landsliding.. The mean velocities from June 2009 to February 2010 show a subsidence pattern in the southeastern part of the volcano flanks and uplift in the southwest. However, such a different deformation signal between two areas so close could also imply atmospheric, topographic or phase unwrapping errors. To assess the contribution to the deformation signal from these possible error sources, we examined <span class="hlt">time</span> <span class="hlt">series</span> of displacements during this period for various areas. The results show a largely linear behavior between nearby areas from 18th June 2009 to 04 February 2010, followed by an excursion in the deformation signal during 17th October 2009. Significantly, the signal is smooth in time, implying that it is not due to atmospheric contamination. The deformation seems consistent with the continuous GPS station THEY, and can indeed indicate magma migration. However, further work is required to reliably separate out the deformation signals that are not related to volcanic processes.</p> <div class="credits"> <p class="dwt_author">Martins, J. C.; Spaans, K.; Hooper, A. J.; Sigmundsson, F.; Feigl, K.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">332</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/1897905"> <span id="translatedtitle">Automatic tracking and characterization of multiple moving clouds in <span class="hlt">satellite</span> <span class="hlt">images</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Investigating the characteristics of mesoscale convective clouds based on <span class="hlt">satellite</span> infrared <span class="hlt">images</span> is very important for strong precipitation forecast. This paper proposes a new method for cloud identification, tracking and characterization using time-varying <span class="hlt">satellite</span> infrared cloud <span class="hlt">image</span> sequences. After clouds are identified using <span class="hlt">image</span> processing techniques, a couple of features are extracted as their representations, based on which feature correspondences</p> <div class="credits"> <p class="dwt_author">Yubin Yang; Hui Lin; Zhongyang Guo; Zhaobao Fang; Jixi Jiang</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">333</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://profhorn.aos.wisc.edu/wxwise/satir/IRThick.html"> <span id="translatedtitle">Cloud Thickness and <span class="hlt">Satellite</span> <span class="hlt">Images</span> (title provided or enhanced by cataloger)</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://nsdl.org/nsdl_dds/services/ddsws1-1/service_explorer.jsp">NSDL National Science Digital Library</a></p> <p class="result-summary">This applet explores how the thickness of a cloud changes the way it looks from a <span class="hlt">satellite</span>. The <span class="hlt">image</span> is in the visible part of the spectrum, and the radiant energy is a function of not just temperature, as in the case of infrared <span class="hlt">images</span>. The cloud thickness, its effective brightness, and the surface temperature can be modified while observing the <span class="hlt">satellite</span> <span class="hlt">image</span>.</p> <div class="credits"> <p class="dwt_author">Whittaker, Tom; Ackerman, Steve</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">334</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012SPIE.8393E..16B"> <span id="translatedtitle">Exploratory joint and separate tracking of geographically related <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Target tracking techniques have usually been applied to physical systems via radar, sonar or <span class="hlt">imaging</span> modalities. But the same techniques - filtering, association, classification, track management - can be applied to nontraditional data such as one might find in other fields such as economics, business and national defense. In this paper we explore a particular data set. The measurements are <span class="hlt">time</span> <span class="hlt">series</span> collected at various sites; but other than that little is known about it. We shall refer to as the data as representing the Megawatt hour (MWH) output of various power plants located in Afghanistan. We pose such questions as: 1. Which power plants seem to have a common model? 2. Do any power plants change their models with time? 3. Can power plant behavior be predicted, and if so, how far to the future? 4. Are some of the power plants stochastically linked? That is, do we observed a lack of power demand at one power plant as implying a surfeit of demand elsewhere? The observations seem well modeled as hidden Markov. This HMM modeling is compared to other approaches; and tests are continued to other (albeit self-generated) data sets with similar characteristics. Keywords: <span class="hlt">Time-series</span> analysis, hidden Markov models, statistical similarity, clustering weighted</p> <div class="credits"> <p class="dwt_author">Balasingam, Balakumar; Willett, Peter; Levchuk, Georgiy; Freeman, Jared</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">335</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/20824156"> <span id="translatedtitle">Hydroxyl <span class="hlt">time</span> <span class="hlt">series</span> and recirculation in turbulent nonpremixed swirling flames</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary"><span class="hlt">Time-series</span> measurements of OH, as related to accompanying flow structures, are reported using picosecond time-resolved laser-induced fluorescence (PITLIF) and particle-<span class="hlt">imaging</span> velocimetry (PIV) for turbulent, swirling, nonpremixed methane-air flames. The [OH] data portray a primary reaction zone surrounding the internal recirculation zone, with residual OH in the recirculation zone approaching chemical equilibrium. Modeling of the OH electronic quenching environment, when compared to fluorescence lifetime measurements, offers additional evidence that the reaction zone burns as a partially premixed flame. A <span class="hlt">time-series</span> analysis affirms the presence of thin flamelet-like regions based on the relation between swirl-induced turbulence and fluctuations of [OH] in the reaction and recirculation zones. The OH integral time-scales are found to correspond qualitatively to local mean velocities. Furthermore, quantitative dependencies can be established with respect to axial position, Reynolds number, and global equivalence ratio. Given these relationships, the OH time-scales, and thus the primary reaction zone, appear to be dominated by convection-driven fluctuations. Surprisingly, the OH time-scales for these nominally swirling flames demonstrate significant similarities to previous PITLIF results in nonpremixed jet flames. (author)</p> <div class="credits"> <p class="dwt_author">Guttenfelder, Walter A.; Laurendeau, Normand M.; Ji, Jun; King, Galen B.; Gore, Jay P. [School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907-1288 (United States); Renfro, Michael W. [Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269-3139 (United States)</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-10-15</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">336</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.5431V"> <span id="translatedtitle">A 45-year <span class="hlt">time</span> <span class="hlt">series</span> of Saharan dune mobility from remote sensing</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Decadal trends in the aeolian dust record of the Sahara affect the global climate system and the nutrient budget of the Atlantic Ocean. One proposed cause of these trends are changes in the frequency and intensity of dust storms, which have hitherto been hard to quantify. Because sand flux scales with the cube of wind speed, dune migration rates can be used as a proxy for storminess. Relative changes in the storminess of the Sahara can thus be monitored by tracking the migration rates of individual sand dunes over time. The Bodélé Depression of northern Chad was selected as a target area for this method, because it is the most important point-source of aeolian dust on the planet and features the largest and fastest dunes on Earth. A collection of co-registered Landsat, SPOT, and ASTER scenes, combined with declassified American spy <span class="hlt">satellite</span> <span class="hlt">images</span> was used to construct a 45 year record of dune migration in the Bodélé Depression. One unexpected outcome of the study was the observation of binary dune interactions in the imagery sequence, which reveals that when two barchan dunes collide, a transfer of mass occurs so that one dune appears to travel through the other unscathed, like a solitary wave. This confirms a controversial numerical model prediction and settles a decade-old debate in aeolian geomorphology. The COSI-Corr change detection method was used to measure the dune migration rates from 1984 until 1987, 1990, 1996, 2000, 2003, 2005, 2007, 2008, 2009, and 2010. An algorithm was developed to automatically warp the resulting displacement fields back to a common point in time. Thus, individual <span class="hlt">image</span> pixels of a dune field were tracked over time, allowing the extraction of a <span class="hlt">time</span> <span class="hlt">series</span> from the co-registered <span class="hlt">satellite</span> <span class="hlt">images</span> without further human intervention. The automated analysis was extended further back into the past by comparison of the 1984 <span class="hlt">image</span> with declassified American spy <span class="hlt">satellite</span> (Corona) <span class="hlt">images</span> from 1965 and 1970. Due to the presence of specks of dust as well as <span class="hlt">image</span> distortions caused by shrinking of the photographic film, it was not possible to automatically measure the dune displacements of these scenes with COSI-Corr. Instead, the <span class="hlt">image</span> was georeferenced and coregistered to the 1984 Landsat imagery by third order polynomial fits to 531 tie points, and the displacements of ten large barchan dunes were measured by hand. Thanks to the 19-year time lapse between the two <span class="hlt">images</span> used for these 'analog' measurements, their precision is better than 5%, which is comparable with that of the automated COSI-Corr analysis. The resulting dune celerities are identical to the automated measurements, which themselves show little or no temporal variability over the subsequent 26 years. The lack of any trend in the <span class="hlt">time</span> <span class="hlt">series</span> of dune celerity paints a picture of remarkably stable dune mobility over the past 45 years. None of the distributions fall outside the overall average of 25m/yr. The constant dune migration rates resulting from our study indicate that there has been no change in the storminess of the Sahara over the past 45 years. The observed dust trends are therefore caused by changes in vegetation cover, which in turn reflect changes in precipitation and land usage. This work highlights the importance of the hyper-arid Bodélé Depression, which provides a steady but finite supply of aeolian dust to the atmosphere without which nutrient fluxes and terrestrial albedo would be more variable than they are today.</p> <div class="credits"> <p class="dwt_author">Vermeesch, P.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">337</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1998DSRI...45..433G"> <span id="translatedtitle">Carbon <span class="hlt">time</span> <span class="hlt">series</span> in the Norwegian sea</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Depth profiles of carbon parameters were obtained monthly from 1991 to 1994 as the first <span class="hlt">time</span> <span class="hlt">series</span> from the weathership station M located in the Norwegian Sea at 66°N 2°E. CO 2 was extracted from acidified seawater by a flushing procedure, with nitrogen as the carrier gas. The pure CO 2 gas was measured using a manometric technique, and the gas was further used for 13C and 14C measurements. The precision of the dissolved inorganic carbon (DIC) was better than ±6‰. Satisfactory agreement was obtained with standard seawater from Scripps Institution of Oceanography. The partial pressure of CO 2 (pCO 2) was measured in the atmosphere and surface water, beginning in October 1991. The most visible seasonal variation in DIC, 13C and pCO 2 was due to the plankton bloom in the upper 50-100 m. Typical values for surface water in the winter were: 2.140±0.012 mmol kg -1 for DIC, 1.00±0.04‰ for ? 13C and 357±15 ?atm for pCO 2, and the corresponding values in the summer were as low as 2.04 mmol kg -1, greater than 2.1‰, and as low as 270-300 ?atm. The values for deep water are more constant during the year, with DIC values of about 2.17±0.01 mmol kg -1, and ? 13C values between 0.97 and 1.14‰. A simple one-dimensional biological model was applied in order to investigate possible short-term variability in DIC caused by the phytoplankton growth and depth variations of the wind-mixed layer. The simulated seasonal pattern was in reasonable agreement with the observed data, but there were significant temporal variations with shorter time interval than the monthly measurements. As a supplement to the measurements at station M, some representative profiles of DIC, ? 13C, ? 14C, salinity and temperature from other locations in the Nordic Seas and the North Atlantic Ocean are also presented. The results are also compared with some data obtained ( ? 14C) by the TTO expedition in 1981 and the GEOSECS expedition in 1972. The carbon profiles reflect the stable deep water in the Greenland and Norwegian Basins, and the relatively young bottom water just south of Iceland.</p> <div class="credits"> <p class="dwt_author">Gislefoss, Jorunn S.; Nydal, Reidar; Slagstad, Dag; Sonninen, Eloni; Holmén, Kim</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-02-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">338</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFM.P41F..07P"> <span id="translatedtitle">Crater Relaxation and Stereo <span class="hlt">Imaging</span> of Icy <span class="hlt">Satellites</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Over billions of years, crater depths relax at a rate that is dependent on the internal properties of the target body. Thus, measuring the depth of craters can give insight into the thermal history and subsurface structure of terrestrial bodies and icy <span class="hlt">satellites</span> (Dombard and McKinnon, 2006). The extensive surface <span class="hlt">imaging</span> coverage provided by Cassini (and more modest coverage from Galileo), in combination with the development of new automated stereo <span class="hlt">imaging</span> programs, now allows for detailed measurements of crater depths on the moons of Saturn and Jupiter, and thus more accurate estimates of crater relaxation. We utilize these resources to create digital elevation models (DEMs) of large craters (D>70km) on icy <span class="hlt">satellites</span>, beginning with Rhea and Dione. We extract crater profiles from our DEMs to determine current crater depths. An estimate of initial crater depth requires extrapolations from a crater assumed to be unrelaxed, either scaled up in size if on the same body, or scaled by gravity if on another <span class="hlt">satellite</span>; initial and current crater depths are combined to yield a measured relaxation percentage for different crater diameter size bins. Our topographic measurements are compared with the results of a coupled thermal evolution-viscoelastic relaxation code, allowing us to investigate the thermal history of each <span class="hlt">satellite</span>. Our model predicts the expected degree of crater relaxation for craters of different sizes and ages based on assumptions about the initial thermal state of the <span class="hlt">satellite</span> and its subsurface structure. So far, in the case of Rhea, our numerical simulations under-predict the amount of crater relaxation we observe, suggesting that Rhea is warmer than we initially modeled; in fact, it appears that internal temperatures must approach the melting point of ice in order to achieve the amount of relaxation we observe. Our numerical model has been benchmarked against standard analytical solutions (Robuchon et al., 2011), and thus we believe that the code itself is not in error and that Rhea experienced more heating early in its history than previously thought. We also find that for 100 km diameter craters on Rhea, other factors in addition to viscous relaxation are important in determining their final depth. We have completed our measurements for all large craters on Rhea that are captured, to date, in Cassini ISS stereo pairs, and are currently working to produce topographic profiles of all available large craters on Dione. We will present results from our Dione crater profiles and numerical modeling of Dione's thermal history, and will compare our results for degree of crater relaxation and subsurface thermal profile with those previously determined for Rhea. Since Rhea and Dione have similar compositions and surface gravities, craters of equivalent diameters on their surfaces likely had similar initial depths. Thus, our comparisons of final crater depths on these two <span class="hlt">satellites</span> will help us understand the details of any similarities or differences in their relaxation histories. Dombard, A. J., and McKinnon W. B. (2006), JGR, 111 E01001; Robuchon, G., et al. (2011), Icarus 214, 82-90</p> <div class="credits"> <p class="dwt_author">Phillips, C. B.; Hammond, N. P.; Nimmo, F.; robuchon, G.; Beyer, R. A.; Roberts, J. H.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">339</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009APS..OSF.P1015V"> <span id="translatedtitle">Approximate Entropies for Stochastic <span class="hlt">Time</span> <span class="hlt">Series</span> and EKG <span class="hlt">Time</span> <span class="hlt">Series</span> of Patients with Epilepsy and Pseudoseizures</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A wide range of heart rate irregularities have been reported in small studies of patients with temporal lobe epilepsy [TLE]. We hypothesize that patients with TLE display cardiac dysautonomia in either a subclinical or clinical manner. In a small study, we have retrospectively identified (2003-8) two groups of patients from the epilepsy monitoring unit [EMU] at the Cleveland Clinic. No patients were diagnosed with cardiovascular morbidities. The control group consisted of patients with confirmed pseudoseizures and the experimental group had confirmed right temporal lobe epilepsy through a seizure free outcome after temporal lobectomy. We quantified the heart rate variability using the approximate entropy [ApEn]. We found similar values of the ApEn in all three states of consciousness (awake, sleep, and proceeding seizure onset). In the TLE group, there is some evidence for greater variability in the awake than in either the sleep or proceeding seizure onset. Here we present results for mathematically-generated <span class="hlt">time</span> <span class="hlt">series</span>: the heart rate fluctuations ? follow the ? statistics i.e., p(?)=?-1(k) ?^k exp(-?). This probability function has well-known properties and its Shannon entropy can be expressed in terms of the ?-function. The parameter k allows us to generate a family of heart rate <span class="hlt">time</span> <span class="hlt">series</span> with different statistics. The ApEn calculated for the generated <span class="hlt">time</span> <span class="hlt">series</span> for different values of k mimic the properties found for the TLE and pseudoseizure group. Our results suggest that the ApEn is an effective tool to probe differences in statistics of heart rate fluctuations.</p> <div class="credits"> <p class="dwt_author">Vyhnalek, Brian; Zurcher, Ulrich; O'Dwyer, Rebecca; Kaufman, Miron</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">340</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/servlets/purl/383556"> <span id="translatedtitle">Advanced <span class="hlt">satellite</span> sensors: Low Energy Neutral Atom (LENA) <span class="hlt">imager</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). <span class="hlt">Imaging</span> of low energy neutral atoms (LENDs) created by electron capture by magnetospheric plasma ions from interactions with cold geocoronal neutrals promises to be a revolutionary technique for providing unprecedented information about the global structure and dynamics of the terrestrial magnetosphere. This has significant implications in space weather forecasting, weather-induced <span class="hlt">satellite</span> upset diagnostics, and revolutionary insights into global magnetospheric physics. The Los Alamos Space and Atmospheric Sciences Group has completed extensive neutral atom simulations and detailed instrument definition, and we designed a proof-of-concept demonstration prototype and have obtained externally- funded programs for full instrument development</p> <div class="credits"> <p class="dwt_author">Funsten, H.O.; McComas, D.J.</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-09-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_16");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" 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<a onClick='return showDiv("page_6");' href="#">6</a> <a onClick='return showDiv("page_7");' href="#">7</a> <a onClick='return showDiv("page_8");' href="#">8</a> <a onClick='return showDiv("page_9");' href="#">9</a> <a onClick='return showDiv("page_10");' href="#">10</a> <a onClick='return showDiv("page_11");' href="#">11</a> <a onClick='return showDiv("page_12");' href="#">12</a> <a onClick='return showDiv("page_13");' href="#">13</a> <a onClick='return showDiv("page_14");' href="#">14</a> <a onClick='return showDiv("page_15");' href="#">15</a> <a onClick='return showDiv("page_16");' href="#">16</a> <a onClick='return showDiv("page_17");' href="#">17</a> <a style="font-weight: bold;">18</a> <a onClick='return showDiv("page_19");' href="#">19</a> <a onClick='return showDiv("page_20");' href="#">20</a> <a onClick='return showDiv("page_21");' href="#">21</a> <a onClick='return showDiv("page_22");' href="#">22</a> <a onClick='return showDiv("page_23");' href="#">23</a> <a onClick='return showDiv("page_24");' href="#">24</a> <a onClick='return showDiv("page_25");' href="#">25</a> </span> </span> <a id="NextPageLink" onclick='return showDiv("page_19");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">341</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://dx.doi.org/10.1126/science.274.5286.377"> <span id="translatedtitle">Galileo's first <span class="hlt">images</span> of Jupiter and the Galilean <span class="hlt">satellites</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">The first <span class="hlt">images</span> 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 <span class="hlt">satellites</span>. 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.</p> <div class="credits"> <p class="dwt_author">Belton, M. J. S.; Head, III, 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.</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">342</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011AGUFM.B54C..06W"> <span id="translatedtitle">Local to Global Scale <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis of US Dryland Degradation Using Landsat, AVHRR, and MODIS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Drylands cover 41% of the terrestrial land surface and annually generate $1 trillion in ecosystem goods and services for 38% of the global population, yet estimates of the global extent of Dryland degradation is uncertain with a range of 10 - 80%. It is currently understood that Drylands exhibit topological complexity including self-organization of parameters of different levels-of-organization, e.g., ecosystem and landscape parameters such as soil and vegetation pattern and structure, that gradually or discontinuously shift to multiple basins of attraction in response to herbivory, fire, and climatic drivers at multiple spatial and temporal scales. Our research has shown that at large geographic scales, contemporaneous <span class="hlt">time</span> <span class="hlt">series</span> of 10 to 20 years for response and driving variables across two or more spatial scales is required to replicate and differentiate between the impact of climate and land use activities such as commercial grazing. For example, the Pacific Decadal Oscillation (PDO) is a major driver of Dryland net primary productivity (NPP), biodiversity, and ecological resilience with a 10-year return interval, thus 20 years of data are required to replicate its impact. Degradation is defined here as a change in physiognomic composition contrary to management goals, a persistent reduction in vegetation response, e.g., NPP, accelerated soil erosion, a decline in soil quality, and changes in landscape configuration and structure that lead to a loss of ecosystem function. Freely available Landsat, Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution <span class="hlt">Imaging</span> Spectroradimeter (MODIS) archives of <span class="hlt">satellite</span> imagery exist that provide local to global spatial coverage and <span class="hlt">time</span> <span class="hlt">series</span> between 1972 to the present from which proxies of land degradation can be derived. This paper presents <span class="hlt">time</span> <span class="hlt">series</span> assessments between 1972 and 2011 of US Dryland degradation including early detection of dynamic regime shifts in the Mojave and landscape pattern and erosion state changes in the Intermountain region in response to the "Great North American Drought" in 1988, PDO and El Niño Southern Oscillation (ENSO) and commercial grazing. Additionally, we will show the discoveries in the last 10-years that US Drylands are "greening" despite the severe Southwestern drought and that commercial livestock are a driver of this response with an annual appropriation of some 58% of NPP.</p> <div class="credits"> <p class="dwt_author">Washington-Allen, R. A.; Ramsey, R. D.; West, N. E.; Kulawardhana, W.; Reeves, M. C.; Mitchell, J. E.; Van Niel, T. G.</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">343</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012IAUS..285...17K"> <span id="translatedtitle">Kepler, CoRoT and MOST: <span class="hlt">Time-Series</span> Photometry from Space</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">During the last 10 years we have seen a revolution in the quality and quantity of data for <span class="hlt">time-series</span> photometry. The two <span class="hlt">satellites</span> MOST and WIRE were the precursors for dedicated <span class="hlt">time-series</span> missions. CoRoT (launched in 2006) has now observed more than 100,000 targets for exoplanet studies and a few hundred stars for asteroseismology, while Kepler (launched in 2009) is producing extended <span class="hlt">time-series</span> data for years, aiming to discover Earth-size planets in or near the habitable zone. We discuss the accuracy of some of the parameters one may extract from the high-quality data from such photometric space missions, including the prospects for detecting oscillation-period changes due to real-time stellar evolution.</p> <div class="credits"> <p class="dwt_author">Kjeldsen, Hans; Bedding, Timothy R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">344</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008AGUSMSP53B..01B"> <span id="translatedtitle">The Mount Wilson CaK Plage Index <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The Mount Wilson solar photographic archive digitization project makes available to the scientific community in digital form a selection of the solar <span class="hlt">images</span> in the archives of the Carnegie Observatories. This archive contains over 150,000 <span class="hlt">images</span> of the Sun which were acquired over a time span in excess of 100 years. The <span class="hlt">images</span> include broad-band <span class="hlt">images</span> called White Light Directs, ionized CaK line spectroheliograms and Hydrogen Balmer alpha spectroheliograms. This project will digitize essentially all of the CaK and broad-band direct <span class="hlt">images</span> out of the archive with 12 bits of significant precision and up to 3000 by 3000 spatial pixels. The analysis of this data set will permit a variety of retrospective analyzes of the state of the solar magnetism and provide a temporal baseline of about 100 years for many solar properties. We have already completed the digitization of the CaK series and we are currently working on the broad-band direct <span class="hlt">images</span>. Solar <span class="hlt">images</span> have been extracted and identified with original logbook parameters of observation time and scan format, and they are available from the project web site at www.astro.ucla.edu/~ulrich/MW_SPADP. We present preliminary results on a CaK plage index <span class="hlt">time</span> <span class="hlt">series</span> derived from the analysis of 70 years of CaK observations, from 1915 to 1985. One of the main problem we encountered during the calibration process of these <span class="hlt">images</span> is the presence of a vignetting function. This function is linked to the relative position between the pupil and the grating. As a result of this effect the intensity and its gradient are highly variable from one <span class="hlt">image</span> to another. We currently remove this effect by using a running median filter to determine the background of the <span class="hlt">image</span> and divide the <span class="hlt">image</span> by this background to obtain a flat <span class="hlt">image</span>. A plage index value is then computed from the intensity distribution of this flat <span class="hlt">image</span>. We show that the temporal variability of our CaK plage index agrees very well with the behavior of the international sunspot number series.</p> <div class="credits"> <p class="dwt_author">Bertello, L.; Ulrich, R. K.; Boyden, J. E.; Javaraiah, J.</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">345</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/42418173"> <span id="translatedtitle">Automated Hazard Assessment Techniques Using <span class="hlt">Satellite</span> <span class="hlt">Images</span> Following the 2008 Sichuan China Earthquake</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Rapid seismic hazard assessment is crucial for accurate damage estimation right after earthquakes. New technologies provide faster damage detection compared to the traditional, manual assessments. One of the new technologies includes using <span class="hlt">satellite</span> <span class="hlt">images</span>. Pre- and post-earthquake <span class="hlt">satellite</span> <span class="hlt">images</span> can be used to identify damage patterns. One of the recent disastrous earthquakes occurred in Sichuan (Mw = 7.9) on May 12,</p> <div class="credits"> <p class="dwt_author">K. Armagan Korkmaz; M. Emin Kutay</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">346</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50865992"> <span id="translatedtitle"><span class="hlt">Satellite</span> Cloud <span class="hlt">Image</span> Segmentation Based on the Improved Normalized Cuts Model</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We propose a novel approach for <span class="hlt">satellite</span> cloud <span class="hlt">image</span> segmentation based on the improved Normalized Cuts Model. We extracted three important features from the multi-channel grayscale information and the texture features of <span class="hlt">satellite</span> <span class="hlt">image</span>, by the statistical analyses of the surface observation. Having set up the weight matrix by those features, we use the spectral graph theoretic framework of normalized</p> <div class="credits"> <p class="dwt_author">Fei Wenlong; Lv Hong; Wei Zhihui</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">347</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EPJST.222..587S"> <span id="translatedtitle">Segmentation and classification of <span class="hlt">time</span> <span class="hlt">series</span> using ordinal pattern distributions</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The distribution of ordinal patterns in <span class="hlt">time</span> <span class="hlt">series</span> has been found to reflect important qualitative features of the underlying system dynamics. Abrupt changes in the dynamics typically result in clearly visible differences between the distributions before and after the break. Recurring dynamical regimes can be discovered by classifying the distributions in different parts of the <span class="hlt">time</span> <span class="hlt">series</span>. This paper discusses two algorithms which exploit the relation between ordinal pattern distributions and system dynamics for the segmentation and classification of <span class="hlt">time</span> <span class="hlt">series</span>. The first algorithm employs a kernel-based statistic, the Maximum Mean Discrepancy of ordinal pattern distributions, to detect and locate change points in the <span class="hlt">time</span> <span class="hlt">series</span>. The second algorithm uses clustering of the ordinal pattern distributions to classify <span class="hlt">time</span> <span class="hlt">series</span> segments with similar dynamics. The methodology is applied to various real-life <span class="hlt">time</span> <span class="hlt">series</span> from physiology and economics.</p> <div class="credits"> <p class="dwt_author">Sinn, M.; Keller, K.; Chen, B.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-06-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">348</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/1998SPIE.3337..108L"> <span id="translatedtitle">Automated analysis of brachial ultrasound <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Atherosclerosis begins in childhood with the accumulation of lipid in the intima of arteries to form fatty streaks, advances through adult life when occlusive vascular disease may result in coronary heart disease, stroke and peripheral vascular disease. Non-invasive B-mode ultrasound has been found useful in studying risk factors in the symptom-free population. Large amount of data is acquired from continuous <span class="hlt">imaging</span> of the vessels in a large study population. A high quality brachial vessel diameter measurement method is necessary such that accurate diameters can be measured consistently in all frames in a sequence, across different observers. Though human expert has the advantage over automated computer methods in recognizing noise during diameter measurement, manual measurement suffers from inter- and intra-observer variability. It is also time-consuming. An automated measurement method is presented in this paper which utilizes quality assurance approaches to adapt to specific <span class="hlt">image</span> features, to recognize and minimize the noise effect. Experimental results showed the method's potential for clinical usage in the epidemiological studies.</p> <div class="credits"> <p class="dwt_author">Liang, Weidong; Browning, Roger L.; Lauer, Ronald M.; Sonka, Milan</p> <p class="dwt_publisher"></p> <p class="publishDate">1998-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">349</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009fpc..book..267C"> <span id="translatedtitle">Efficient Algorithms for Segmentation of Item-Set <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We propose a special type of <span class="hlt">time</span> <span class="hlt">series</span>, which we call an item-set <span class="hlt">time</span> <span class="hlt">series</span>, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set <span class="hlt">time</span> <span class="hlt">series</span>, each observed data value is a set of discrete items. We formalize the concept of an item-set <span class="hlt">time</span> <span class="hlt">series</span> and present efficient algorithms for segmenting a given item-set <span class="hlt">time</span> <span class="hlt">series</span>. Segmentation of a <span class="hlt">time</span> <span class="hlt">series</span> partitions the <span class="hlt">time</span> <span class="hlt">series</span> into a sequence of segments where each segment is constructed by combining consecutive time points of the <span class="hlt">time</span> <span class="hlt">series</span>. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the <span class="hlt">time</span> <span class="hlt">series</span>. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set <span class="hlt">time</span> <span class="hlt">series</span>. We use the item-set <span class="hlt">time</span> <span class="hlt">series</span> segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set <span class="hlt">time</span> <span class="hlt">series</span> data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.</p> <div class="credits"> <p class="dwt_author">Chundi, Parvathi; Rosenkrantz, Daniel J.</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">350</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51117522"> <span id="translatedtitle"><span class="hlt">Time-series</span> analysis of rainforest clearing in Sabah, Borneo using Landsat imagery</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">T ropical forests are being cleared at alarming rates. The release of the Landsat <span class="hlt">image</span> archive represents an opportunity to assess rainforest clearing over time through <span class="hlt">time-series</span> analysis. The objective was to map the extent of rainforest clearing and assess land cover trends at the object level within a selected study area in Sabah, Borneo using Landsat <span class="hlt">images</span> from 1991,</p> <div class="credits"> <p class="dwt_author">Kasper Johansen</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">351</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008SPIE.6978E..16W"> <span id="translatedtitle">Scene context dependency of pattern constancy of <span class="hlt">time</span> <span class="hlt">series</span> imagery</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">A fundamental element of future generic pattern recognition technology is the ability to extract similar patterns for the same scene despite wide ranging extraneous variables, including lighting, turbidity, sensor exposure variations, and signal noise. In the process of demonstrating pattern constancy of this kind for retinex/visual servo (RVS) <span class="hlt">image</span> enhancement processing, we found that the pattern constancy performance depended somewhat on scene content. Most notably, the scene topography and, in particular, the scale and extent of the topography in an <span class="hlt">image</span>, affects the pattern constancy the most. This paper will explore these effects in more depth and present experimental data from several <span class="hlt">time</span> <span class="hlt">series</span> tests. These results further quantify the impact of topography on pattern constancy. Despite this residual inconstancy, the results of overall pattern constancy testing support the idea that RVS <span class="hlt">image</span> processing can be a universal front-end for generic visual pattern recognition. While the effects on pattern constancy were significant, the RVS processing still does achieve a high degree of pattern constancy over a wide spectrum of scene content diversity, and wide ranging extraneousness variations in lighting, turbidity, and sensor exposure.</p> <div class="credits"> <p class="dwt_author">Woodell, Glenn; Jobson, Daniel J.; Rahman, Zia-ur</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-05-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">352</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2010AGUFM.G21C..08L"> <span id="translatedtitle">Using the SSA method to analyze VLBI <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The Singular Spectrum Analysis (SSA) is a method widely use, especially in climatology. Its purpose is to spectrally decompose <span class="hlt">time</span> <span class="hlt">series</span> at different levels of frequency. This tool is applied to VLBI geodetic data in this study. But the challenge with VLBI <span class="hlt">time</span> <span class="hlt">series</span> is the lack of regularity: the observations are not done continuously, leading to non-regular <span class="hlt">time</span> <span class="hlt">series</span>. SSA offers a solution to this problem, filling the gaps by taking into account the temporal correlation of the <span class="hlt">time</span> <span class="hlt">series</span>. Different comparisons with the Principal Component Analysis are done as well as noise analysis with the Alan variance to show the strength of the SSA.</p> <div class="credits"> <p class="dwt_author">Le Bail, K.; Nilsson, E.; Gipson, J. M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">353</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23813096"> <span id="translatedtitle">Mapping afforestation and deforestation from 1974 to 2012 using Landsat <span class="hlt">time-series</span> stacks in Yulin District, a key region of the Three-North Shelter region, China.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The Three-North Shelter Forest Program is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land use and land cover change, but it is still challenging to accurately quantify the change in forest extent from <span class="hlt">time-series</span> <span class="hlt">satellite</span> <span class="hlt">images</span>. In this paper, 30 Landsat MSS/TM/ETM+ epochs from 1974 to 2012 were collected, and the high-quality ground surface reflectance (GSR) <span class="hlt">time-series</span> <span class="hlt">images</span> were processed by integrating the 6S atmosphere transfer model and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the <span class="hlt">time-series</span> Landsat GSR <span class="hlt">images</span> based on the integrated forest z-score (IFZ) model by Huang et al. (2009a), which was improved by multi-phenological IFZ models and the smoothing processing of IFZ data for afforestation mapping. The mapping result showed a large increase in the extent of forest, from 380,394 ha (14.8 % of total district area) in 1974 to 1,128,380 ha (43.9 %) in 2010. Finally, the land cover and forest change map was validated with an overall accuracy of 89.1 % and a kappa coefficient of 0.858. The forest change time was also successfully retrieved, with 22.2 % and 86.5 % of the change pixels attributed to the correct epoch and within three epochs, respectively. The results confirmed a great achievement of the ecological revegetation projects in Yulin district over the last 40 years and also illustrated the potential of the <span class="hlt">time-series</span> of Landsat <span class="hlt">images</span> for detecting forest changes and estimating tree age for the artificial forest in a semi-arid zone strongly influenced by human activities. PMID:23813096</p> <div class="credits"> <p class="dwt_author">Liu, Liangyun; Tang, Huan; Caccetta, Peter; Lehmann, Eric A; Hu, Yong; Wu, Xiaoliang</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-06-28</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">354</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/servlets/purl/1036840"> <span id="translatedtitle">High Resolution <span class="hlt">Imaging</span> of <span class="hlt">Satellites</span> with Ground-Based 10-m Astronomical Telescopes</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">High resolution <span class="hlt">imaging</span> of artificial <span class="hlt">satellites</span> can play an important role in current and future space endeavors. One such use is acquiring detailed <span class="hlt">images</span> that can be used to identify or confirm damage and aid repair plans. It is shown that a 10-m astronomical telescope equipped with an adaptive optics system (AO) to correct for atmospheric turbulence using a natural guide star can acquire high resolution <span class="hlt">images</span> of <span class="hlt">satellites</span> in low-orbits using a fast shutter and a near-infrared camera even if the telescope is not capable of tracking <span class="hlt">satellites</span>. With the telescope pointing towards the <span class="hlt">satellite</span> projected orbit and less than 30 arcsec away from a guide star, multiple <span class="hlt">images</span> of the <span class="hlt">satellite</span> are acquired on the detector using the fast shutter. <span class="hlt">Images</span> can then be shifted and coadded by post processing to increase the <span class="hlt">satellite</span> signal to noise ratio. Using the Keck telescope typical Strehl ratio and anisoplanatism angle as well as a simple diffusion/reflection model for a <span class="hlt">satellite</span> 400 km away observed near Zenith at sunset or sunrise, it is expected that such system will produced > 10{sigma} K-band <span class="hlt">images</span> at a resolution of 10 cm inside a 60 arcsec diameter field of view. If implemented, such camera could deliver the highest resolution <span class="hlt">satellite</span> <span class="hlt">images</span> ever acquired from the ground.</p> <div class="credits"> <p class="dwt_author">Marois, C</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-04</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">355</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2006DPS....38.3109F"> <span id="translatedtitle">Ground-based <span class="hlt">Imaging</span> Of Pluto's <span class="hlt">Satellites</span>, Hydra And Nix.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We report astrometric and photometric observations of Hydra and Nix, the small <span class="hlt">satellites</span> of Pluto recently discovered with the HST/ACS (Weaver et al. 2005). We observed the Pluto system on UT 2006 June 27, UT 2006 June 28 and UT 2006 July 5 with the Inamori Magellan Areal Camera (IMACS) on the 6.5-m Magellan Baade telescope and on UT 2006 July 23 with the Raymond and Beverly Sackler Magellan Instant Camera (MagIC) on the 6.5-m Magellan Clay telescope. We obtained roughly 1800 sec of integration on each of the four nights in a series of exposures that were short enough to avoid saturating Pluto (10 sec to 2 minutes, depending upon the instrument and observing conditions). The typical FWHM of the PSF on each of these nights was 0.45 arcsec, 0.5 arcsec, 1.0 arcsec and 0.7 arcsec, respectively. To identify Hydra and Nyx, we used the IRAF/DAOPHOT routines (Stetson 1992) to determine the stellar PSF on each <span class="hlt">image</span> and then subtract the flux from Pluto and Charon, at their measured positions, as well as the flux from nearby stars. We shifted the subtracted <span class="hlt">images</span> in software to compensate for the apparent motion of the Pluto system and then averaged the resulting <span class="hlt">images</span>. We detected Hydra and Nix on most of these nights. We believe these are the first reported ground-based detections of these moons. These observations open the opportunity for regular, repeated measurements, with the goal of detecting the mutual interactions between Hydra and Nix in order to solve for their individual masses, as recently suggested by Lee et al. (2006).</p> <div class="credits"> <p class="dwt_author">Fuentes, Cesar; Holman, M. J.; Gaudi, B. S.; Barranco, J. A.; Trilling, D. E.</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">356</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2008AGUFM.G33B0692K"> <span id="translatedtitle">Seasonal signals in the reprocessed GPS coordinate <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The global (IGS) and regional (EPN) CGPS <span class="hlt">time</span> <span class="hlt">series</span> have already been studied in detail by several authors to analyze the periodic signals and noise present in the long term displacement series. The comparisons indicated that the amplitude and phase of the CGPS derived seasonal signals mostly disagree with the surface mass redistribution models. The CGPS results are highly overestimating the seasonal term, only about 40% of the observed annual amplitude can be explained with the joint contribution of the geophysical models (Dong et al. 2002). Additionally the estimated amplitudes or phases are poorly coherent with the models, especially at sites close to coastal areas (van Dam et al, 2007). The conclusion of the studies was that the GPS results are distorted by analysis artifacts (e.g. ocean tide loading, aliasing of unmodeled short periodic tidal signals, antenna PCV models), monument thermal effects and multipath. Additionally, the GPS series available so far are inhomogeneous in terms of processing strategy, applied models and reference frames. The introduction of the absolute phase center variation (PCV) models for the <span class="hlt">satellite</span> and ground antennae in 2006 and the related reprocessing of the GPS precise orbits made a perfect ground and strong argument for the complete re-analysis of the GPS observations from global to local level of networks. This enormous work is in progress within the IGS and a pilot analysis was already done for the complete EPN observations from 1996 to 2007 by the MUT group (Military University of Warsaw). The quick analysis of the results proved the expectations and the superiority of the reprocessed data. The noise level (weekly coordinate repeatability) was highly reduced making ground for the later analysis on the daily solution level. We also observed the significant decrease of the seasonal term in the residual coordinate <span class="hlt">time</span> <span class="hlt">series</span>, which called our attention to perform a repeated comparison of the GPS derived annual periodicity and the surface mass redistribution models. We expect that using the reprocessed EPN data we can exclude several analysis related artifacts and we get a more clear view on the real physical information content of the data. In this paper we present a general overview and results of the EPN reprocessing and we show the detailed results of the harmonic analysis.</p> <div class="credits"> <p class="dwt_author">Kenyeres, A.; van Dam, T.; Figurski, M.; Szafranek, K.</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-12-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">357</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013SPIE.8866E..0QW"> <span id="translatedtitle">Monitoring NPP VIIRS on-orbit radiometric performance from TOA reflectance <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The recently launched (October 28, 2011) Suomi NPP (National Polar-orbiting Partnership) <span class="hlt">satellite</span> has been operating nominally to daily collect global data. The Visible Infrared <span class="hlt">Imaging</span> Radiometer Suite (VIIRS) is a key NPP sensor onboard the spacecraft. Similar to the heritage sensor MODIS, VIIRS has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the reflective solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view (SV) port for background. This study examines VIIRS reflective solar bands (RSB) calibration stability and performance using observed top-of-atmosphere (TOA) reflectance <span class="hlt">time</span> <span class="hlt">series</span> collected from two approaches. The first is from comparison with a well-calibrated Aqua MODIS and the second is from overpasses over the widely used Liby-4 desert site. The VIIRS and MODIS comparison data is obtained from simultaneous nadir overpasses (SNO) for their spectrally matched bands. The reflectance trends over the Libya-4 site are extracted from 16-day repeatable orbits so each data point has the same viewing geometry relative to the site. The impact due to the band spectral differences between the two instruments is corrected based on MODTRAN5 simulations. Results of this study provide useful information on NPP VIIRS post-launch calibration assessment and preliminary analysis of its calibration stability and consistency for the first 1.5 years.</p> <div class="credits"> <p class="dwt_author">Wu, A.; Xiong, X.; Cao, C.; Sun, C.</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">358</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012EGUGA..14.6480C"> <span id="translatedtitle">Correlation and Coherence Analysis of Paired <span class="hlt">Time-Series</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Changes in radon and other soil-gas concentrations, and other parameters, before and after earthquakes have been widely reported. However, in the majority of such radon cases, changes in magnitude in single <span class="hlt">time-series</span> have been reported, often large changes recorded using integrating detectors, and the majority of radon <span class="hlt">time-series</span> analysis is reported for single <span class="hlt">time-series</span>. With a single <span class="hlt">time-series</span>, recorded at a single location, there is no measure of the spatial extent of any anomaly and, to a great extent, only anomalies in magnitude can be investigated. With two (or more) <span class="hlt">time-series</span> from different locations, it is possible to investigate the spatial extent of anomalies and also investigate anomalies in time, i.e. frequency and phase components, as well as anomalies in magnitude. Techniques for investigating paired <span class="hlt">time-series</span> for simultaneous similar anomalous features, developed and adapted from techniques more familiar in the field of signal analysis, will be presented. A paired radon <span class="hlt">time-series</span> dataset is used to illuminate these techniques. This is not a restriction to radon <span class="hlt">time-series</span>: it is simply that the investigation at the University of Northampton has been conducted on radon datasets. The particular <span class="hlt">time-series</span> are characterised by weak, intermittent, out-of-phase 24-hour cycles. The correlation analysis (Crockett et al., 2006) reveals two anomalous short periods where the <span class="hlt">time-series</span> correlate, these periods temporally corresponding to UK earthquakes. The coherence analysis (Crockett, 2012) reveals anomalous short periods where the <span class="hlt">time-series</span> cohere at 24-hour and 12-hour cycles: two of these periods confirm the periods revealed by the correlation analysis but there is a third period which also temporally corresponds to a UK earthquake.</p> <div class="credits"> <p class="dwt_author">Crockett, R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">359</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2006AGUFM.G11B..04F"> <span id="translatedtitle">The new EIGEN-GRACE05S Gravity Field <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">GFZ as part of the GRACE Science Data System has just recently reprocessed GRACE mission data based on improved background models and processing standards. The background model improvements cover an updated static gravity field (EIGEN-GL04C), better non-tidal atmospheric and oceanic short-term mass variations and a-priori annual and semi-annual gravity variations derived from the precursor EIGEN-GRACE04S <span class="hlt">time</span> <span class="hlt">series</span>. The processing standards take into account IERS2003 standards for background models and reference frames, among them improved relativistic corrections of <span class="hlt">satellite</span> accelerations (Lense Thirring and de Sitter). Additionally, azimuth- and elevation-dependent GPS masks have been applied for both GRACE <span class="hlt">satellites</span>. The presentation will focus on the improvements compared to the gravity field <span class="hlt">time</span> <span class="hlt">series</span> publicly available since May 2006.</p> <div class="credits"> <p class="dwt_author">Flechtner, F.; Schmidt, R.; Meyer, U.; Neumayer, K. H.; Koenig, R.; Rothacher, M.</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">360</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009SPIE.7495E.111L"> <span id="translatedtitle">Retrieving and recognizing aircraft targets staying at the airport from the <span class="hlt">satellite</span> <span class="hlt">image</span> database</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The paper studies the problem of how to recognize aircraft targets staying at the airport from <span class="hlt">satellite</span> <span class="hlt">image</span> database of huge amount in an acceptable processing speed. Without adopting the current method recognizing the target picture by picture from the <span class="hlt">image</span> database, the paper combines <span class="hlt">image</span> retrieval with target recognition, and firstly uses <span class="hlt">image</span> retrieval technology to pick out those <span class="hlt">images</span> containing airport target from the <span class="hlt">satellite</span> <span class="hlt">image</span> database, then utilizes target recognition technology to recognize the aircraft targets staying at the airport from those <span class="hlt">images</span>. Some new methods or thoughts have been put forward about the airport <span class="hlt">image</span> retrieval, segmentation and recognition for aircraft targets, and a retrieval and recognition system for aircraft targets staying at the airport in the database of <span class="hlt">satellite</span> <span class="hlt">images</span> has been studied and designed. Finally many experiments has been designed and carried out, and the experimental results demonstrate that these methods are feasible and effective.</p> <div class="credits"> <p class="dwt_author">Lu, Yu; Wang, Jingen; Wang, Yanfei; Xu, Jingtao</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-10-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_17");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span 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id="NextPageLink" onclick='return showDiv("page_20");' href="#" title="Next Page"> <img id="NextPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.next.18x20.png" alt="Next Page" /></a> <a id="LastPageLink" onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">361</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009AGUFM.B31A0315H"> <span id="translatedtitle">Biomass Accumulation Rates of Amazonian Secondary Forest and Biomass of Old-Growth Forests from Landsat <span class="hlt">Time</span> <span class="hlt">Series</span> and GLAS</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">We estimate the age of humid lowland tropical forests in Rondônia, Brazil, from a somewhat densely spaced <span class="hlt">time</span> <span class="hlt">series</span> of Landsat <span class="hlt">images</span> (1975-2003) with an automated procedure, the Threshold Age Mapping Algorithm (TAMA), first described here. We then estimate a landscape-level rate of aboveground woody biomass accumulation of secondary forest by combining forest age mapping with biomass estimates from the Geoscience Laser Altimeter System (GLAS). Though highly variable, the estimated average biomass accumulation rate of 8.4 Mg ha-1 yr-1 agrees well with ground-based studies for young secondary forests in the region. In isolating the lowland forests, we map land cover and general types of old-growth forests with decision tree classification of Landsat imagery and elevation data. We then estimate aboveground live biomass for seven classes of old-growth forest. TAMA is simple, fast, and self-calibrating. By not using between-date band or index differences or trends, it requires neither <span class="hlt">image</span> normalization nor atmospheric correction. In addition, it uses an approach to map forest cover for the self-calibrations that is novel to forest mapping with <span class="hlt">satellite</span> imagery; it maps humid secondary forest that is difficult to distinguish from old-growth forest in single-date imagery; it does not assume that forest age equals time since disturbance; and it incorporates Landsat Multispectral Scanner (MSS) imagery. Variations on the work that we present here can be applied to other forested landscapes. Applications that use <span class="hlt">image</span> <span class="hlt">time</span> <span class="hlt">series</span> will be helped by the free distribution of coregistered Landsat imagery, which began in December 2008, and of the Ice Cloud and land Elevation <span class="hlt">Satellite</span> (ICESat) Vegetation Product, which simplifies the use of GLAS data. Finally, we demonstrate here for the first time how the optical imagery of fine spatial resolution that is viewable on Google Earth provides a new source of reference data for remote sensing applications related to land cover. Reference: Helmer, E. H., M. A. Lefsky and D. A. Roberts. 2009. Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat <span class="hlt">time</span> <span class="hlt">series</span> and the Geoscience Laser Altimeter System. Journal of Applied Remote Sensing 3:033505.</p> <div class="credits"> <p class="dwt_author">Helmer, E.; Lefsky, M. A.; Roberts, D.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-12-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">362</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013JARS....7.3515Z"> <span id="translatedtitle">Using long <span class="hlt">time</span> <span class="hlt">series</span> of Landsat data to monitor impervious surface dynamics: a case study in the Zhoushan Islands</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Islands are an important part of the marine ecosystem. Increasing impervious surfaces in the Zhoushan Islands due to new development and increased population have an ecological impact on the runoff and water quality. Based on <span class="hlt">time-series</span> classification and the complement of vegetation fraction in urban regions, Landsat thematic mapper and other high-resolution <span class="hlt">satellite</span> <span class="hlt">images</span> were applied to monitor the dynamics of impervious surface area (ISA) in the Zhoushan Islands from 1986 to 2011. Landsat-derived ISA results were validated by the high-resolution Worldview-2 and aerial photographs. The validation shows that mean relative errors of these ISA maps are <15 %. The results reveal that the ISA in the Zhoushan Islands increased from 19.2 km2 in 1986 to 86.5 km2 in 2011, and the period from 2006 to 2011 had the fastest expansion rate of 5.59 km2 per year. The major land conversions to high densities of ISA were from the tidal zone and arable lands. The expansions of ISA were unevenly distributed and most of them were located along the periphery of these islands. <span class="hlt">Time-series</span> maps revealed that ISA expansions happened continuously over the last 25 years. Our analysis indicated that the policy and the topography were the dominant factors controlling the spatial patterns of ISA and its expansions in the Zhoushan Islands. With continuous urbanization processes, the rapid ISA expansions may not be stopped in the near feature.</p> <div class="credits"> <p class="dwt_author">Zhang, Xiaoping; Pan, Delu; Chen, Jianyu; Zhan, Yuanzeng; Mao, Zhihua</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">363</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..15.1865Y"> <span id="translatedtitle">Estimate Landslide Volume with Genetic Algorithms and <span class="hlt">Image</span> Similarity Method from Single <span class="hlt">Satellite</span> <span class="hlt">Image</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">It is important to acquire the volume of landslide in short period of time. For hazard mitigation and also emergency response purpose, the traditional method takes much longer time than expected. Due to the weather limit, traffic accessibility and many regulations of law, it take months to handle these process before the actual carry out of filed work. Remote sensing imagery can get the data as long as the visibility allowed, which happened only few day after the event. While traditional photometry requires a stereo pairs <span class="hlt">images</span> to produce the post event DEM for calculating the change of volume. Usually have to wait weeks or even months for gathering such data, LiDAR or ground GPS measurement might take even longer period of time with much higher cost. In this study we use one post event <span class="hlt">satellite</span> <span class="hlt">image</span> and pre-event DTM to compare the similarity between these by alter the DTM with genetic algorithms. The outcome of smartest guess from GAs shall remove or add exact values of height at each location, which been converted into shadow relief viewgraph to compare with <span class="hlt">satellite</span> <span class="hlt">image</span>. Once the similarity threshold been make then the guessing work stop. It takes only few hours to finish the entire task, the computed accuracy is around 70% by comparing to the high resolution LiDAR survey at a landslide, southern Taiwan. With extra GCPs, the estimate accuracy can improve to 85% and also within few hours after the receiving of <span class="hlt">satellite</span> <span class="hlt">image</span>. Data of this demonstration case is a 5 m DTM at 2005, 2M resolution FormoSat optical <span class="hlt">image</span> at 2009 and 5M LiDAR at 2010. The GAs and <span class="hlt">image</span> similarity code is developed on Matlab at windows PC.</p> <div class="credits"> <p class="dwt_author">Yu, Ting-To</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">364</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2040299"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> Model Specification in the Presence of Outliers</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Outliers are commonplace in data analysis. <span class="hlt">Time</span> <span class="hlt">series</span> analysis is no exception. Noting that the effect of outliers on model identification statistics could be serious, this article is concerned with the problem of <span class="hlt">time</span> <span class="hlt">series</span> model specification in the presence of outliers. An iterative procedure is proposed to identify the outliers, to remove their effects, and to specify a tentative</p> <div class="credits"> <p class="dwt_author">Ruey S. Tsay</p> <p class="dwt_publisher"></p> <p class="publishDate">1986-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">365</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/54650902"> <span id="translatedtitle">Wavelet analysis and scaling properties of <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We propose a wavelet based method for the characterization of the scaling behavior of nonstationary <span class="hlt">time</span> <span class="hlt">series</span>. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal <span class="hlt">time</span> <span class="hlt">series</span></p> <div class="credits"> <p class="dwt_author">P. Manimaran; Prasanta K. Panigrahi; Jitendra C. Parikh</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">366</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.wessa.net/download/tutorial1.pdf"> <span id="translatedtitle">A Compendium of Reproducible Research about <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This document can be used as an introductory, interactive case study about <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis based on decomposition, multiple regression and exponential smoothing (including the Holt-Winters model). Section 2 describes the problem and section 3 introduces theoretical concepts that are of importance in applied analysis. Section 4 treats the problem of decomposing a <span class="hlt">time</span> <span class="hlt">series</span> into its underlying components (trend,</p> <div class="credits"> <p class="dwt_author">Patrick Wessa</p> <p class="dwt_publisher"></p> <p class="publishDate">2008-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">367</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/17699921"> <span id="translatedtitle">Learning to transform <span class="hlt">time</span> <span class="hlt">series</span> with a few examples.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We describe a semi-supervised regression algorithm that learns to transform one <span class="hlt">time</span> <span class="hlt">series</span> into another <span class="hlt">time</span> <span class="hlt">series</span> given examples of the transformation. This algorithm is applied to tracking, where a <span class="hlt">time</span> <span class="hlt">series</span> of observations from sensors is transformed to a <span class="hlt">time</span> <span class="hlt">series</span> describing the pose of a target. Instead of defining and implementing such transformations for each tracking task separately, our algorithm learns a memoryless transformation of <span class="hlt">time</span> <span class="hlt">series</span> from a few example input-output mappings. The algorithm searches for a smooth function that fits the training examples and, when applied to the input <span class="hlt">time</span> <span class="hlt">series</span>, produces a <span class="hlt">time</span> <span class="hlt">series</span> that evolves according to assumed dynamics. The learning procedure is fast and lends itself to a closed-form solution. It is closely related to nonlinear system identification and manifold learning techniques. We demonstrate our algorithm on the tasks of tracking RFID tags from signal strength measurements, recovering the pose of rigid objects, deformable bodies, and articulated bodies from video sequences. For these tasks, this algorithm requires significantly fewer examples compared to fully-supervised regression algorithms or semi-supervised learning algorithms that do not take the dynamics of the output <span class="hlt">time</span> <span class="hlt">series</span> into account. PMID:17699921</p> <div class="credits"> <p class="dwt_author">Rahimi, Ali; Recht, Ben; Darrell, Trevor</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-10-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">368</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://benchoi.info/Bens/Research/Publication/Ben%20Choi%202009%20on%20Artificial%20Intelligene%20and%20Applications.pdf"> <span id="translatedtitle">APPLYING MACHINE LEARNING METHODS FOR <span class="hlt">TIME</span> <span class="hlt">SERIES</span> FORECASTING</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper describes a strategy on learning from <span class="hlt">time</span> <span class="hlt">series</span> data and on using learned model for forecasting. <span class="hlt">Time</span> <span class="hlt">series</span> forecasting, which analyzes and predicts a variable changing over time, has received much attention due to its use for forecasting stock prices, but it can also be used for pattern recognition and data mining. Our method for learning from time</p> <div class="credits"> <p class="dwt_author">Ben Choi; Raj Chukkapalli</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">369</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://homepage.univie.ac.at/~kunstr3/plymlinz.pdf"> <span id="translatedtitle">Decision Maps for Bivariate <span class="hlt">Time</span> <span class="hlt">Series</span> with Potential Thrshold Cointegration</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Bivariate <span class="hlt">time</span> <span class="hlt">series</span> data often show strong relationships between the two components, while both individual variables can be approximated by random walks in the short run andare obviously bounded in the long run. Three model classes are considered for a <span class="hlt">time-series</span> model selection problem: stable vector autoregressions, cointegrated models, and globally stable threshold models. It is demonstrated how simulated decision</p> <div class="credits"> <p class="dwt_author">Robert M. Kunst</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">370</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://fmwww.bc.edu/ec-p/wp598.pdf"> <span id="translatedtitle">Stata: The language of choice for <span class="hlt">time</span> <span class="hlt">series</span> analysis?</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper discusses the use of Stata for the analysis of <span class="hlt">time</span> <span class="hlt">series</span> and panel data. The evolution of <span class="hlt">time-series</span> capabilities in Stata is reviewed. Facilities for data management, graphics, and econometric analysis from both official Stata and the user community are discussed. A new routine to provide moving-window regression estimatesrollregis described, and its use illustrated.</p> <div class="credits"> <p class="dwt_author">Christopher F. Baum</p> <p class="dwt_publisher"></p> <p class="publishDate">2004-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">371</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/487056"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> Forecasting by Finite-State Automata</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We have developed automata to address the problem of <span class="hlt">time</span> <span class="hlt">series</span> forecasting. After turning the <span class="hlt">time</span> <span class="hlt">series</span> into sequences of letters, Mohri's algorithm constructs an automaton indexing this text that, once a given word is read, can be used to obtain the set of its positions. By using the automaton to determine what letter usually follows the last sequence of</p> <div class="credits"> <p class="dwt_author">Romuald Boné; Christophe Daguin; Antoine Georgevail; Denis Maurel</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">372</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://page.mi.fu-berlin.de/horenko/download/SISC-071596_v2.pdf"> <span id="translatedtitle">Finite Element Approach to Clustering of Multidimensional <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We present a new approach to clustering of <span class="hlt">time</span> <span class="hlt">series</span> based on a minimization of the averaged clus- tering functional. The proposed functional describes the mean distance between observation data and its representation in terms of K abstract models of a certain predefined class (not necessarily given by some probability distribution). For a fixed <span class="hlt">time</span> <span class="hlt">series</span> x(t) this functional depends</p> <div class="credits"> <p class="dwt_author">Illia Horenko</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">373</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/35563216"> <span id="translatedtitle">Mean shifts, unit roots and forecasting seasonal <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Examples of descriptive models for changing seasonal patterns in economic <span class="hlt">time</span> <span class="hlt">series</span> are autoregressive models with seasonal unit roots or with deterministic seasonal mean shifts. In this paper we show through a forecasting comparison for three macroeconomic <span class="hlt">time</span> <span class="hlt">series</span> (for which tests indicate the presence of seasonal unit roots) that allowing for possible seasonal mean shifts can improve forecast performance.</p> <div class="credits"> <p class="dwt_author">Richard Paap; Philip Hans Franses; Henk Hoek</p> <p class="dwt_publisher"></p> <p class="publishDate">1997-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">374</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/27089824"> <span id="translatedtitle">The <span class="hlt">Time</span> <span class="hlt">Series</span> Approach to Short Term Load Forecasting</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The application of <span class="hlt">time</span> <span class="hlt">series</span> analysis methods to load forecasting is reviewed. It is shown than Box and Jenkins <span class="hlt">time</span> <span class="hlt">series</span> models, in particular, are well suited to this application. The logical and organized procedures for model development using the autocorrelation function and the partial autocorrelation function make these models particularly attractive. One of the drawbacks of these models is</p> <div class="credits"> <p class="dwt_author">Martin T. Hagan; Suzanne M. Behr</p> <p class="dwt_publisher"></p> <p class="publishDate">1987-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">375</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/54958018"> <span id="translatedtitle">Complex network approach to geophysical <span class="hlt">time</span> <span class="hlt">series</span> analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We present a new way to analysing the structural properties of <span class="hlt">time</span> <span class="hlt">series</span> representing the dynamics of certain real-world complex systems. For this purpose, the recurrence of certain values or dynamical patterns in a <span class="hlt">time</span> <span class="hlt">series</span> is described by a recurrence network, which links different points in time if the evolution of the considered observable is very similar. The transformation</p> <div class="credits"> <p class="dwt_author">R. Donner</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">376</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50855903"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> analysis mmethods of the groundwater level prediction</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Theory and methodology provided by <span class="hlt">time</span> <span class="hlt">series</span> analysis is one of the tools which is used for those studies focusing on highly complicated and synthetic projects. Its technology of anticipation and evaluation is more developed than others, and its forecasting circumstance is specific, too. Many scholars have yielded a rich harvest on <span class="hlt">time</span> <span class="hlt">series</span> in recent years, some others have</p> <div class="credits"> <p class="dwt_author">Changjun Zhu; Sha Li; Liping Wu</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">377</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4404640"> <span id="translatedtitle">Pattern identification in dynamical systems via symbolic <span class="hlt">time</span> <span class="hlt">series</span> analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper presents symbolic <span class="hlt">time</span> <span class="hlt">series</span> analysis (STSA) of multi-dimensional measurement data for pattern identification in dynamical systems. The proposed methodology is built upon concepts derived from Information Theory and Automata Theory. The objective is not merely to classify the <span class="hlt">time</span> <span class="hlt">series</span> patterns but also to identify the variations therein. To achieve this goal, a symbol alphabet is constructed from</p> <div class="credits"> <p class="dwt_author">Venkatesh Rajagopalan; Asok Ray; Rohan Samsi; Jeffrey Mayer</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">378</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/58094285"> <span id="translatedtitle">Linear Combination of Information in <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">An important tool in <span class="hlt">time</span> <span class="hlt">series</span> analysis is that of combining information in an optimal manner. Here we establish a basic combining rule of linear estimators and exemplify its use with several different problems faced by a <span class="hlt">time</span> <span class="hlt">series</span> analyst. A compatibility test statistic is also provided as a companion of the combining rule. This statistic plays a fundamental role</p> <div class="credits"> <p class="dwt_author">Victor M. Guerrero; Daniel Peña</p> <p class="dwt_publisher"></p> <p class="publishDate">1995-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">379</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.agu.org/journals/wr/v011/i005/WR011i005p00657/WR011i005p00657.pdf"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> analysis of a watershed response variable</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Daily discharge flows are transformed by a recession equation into a dimensionless <span class="hlt">time</span> <span class="hlt">series</span> which reflects the storage characteristics of a watershed and also indicates the direct response of a watershed to precipitation. Spectral techniques of <span class="hlt">time</span> <span class="hlt">series</span> analysis are employed as an exploratory tool for suggesting different models describing a watershed's response.</p> <div class="credits"> <p class="dwt_author">K. Adamowski; M. Oosterveld</p> <p class="dwt_publisher"></p> <p class="publishDate">1975-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">380</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/49963062"> <span id="translatedtitle">Adaptive modelling of biological <span class="hlt">time</span> <span class="hlt">series</span> for artifact detection</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The authors propose a method for artifact detection based on linear modelling of biological <span class="hlt">time</span> <span class="hlt">series</span>. An artifact, coming from a different “source”, generally does not fit in the model and can be detected. Biological <span class="hlt">time</span> <span class="hlt">series</span> are not stationary, so that adaptive filtering is used for model estimation. Real time constraints warrant the use of predictive models only past</p> <div class="credits"> <p class="dwt_author">M. Varanini; A. Taddei; R. Balocchi; M. Macerata; F. Conforti; M. Emdin; C. Carpeggiani; C. Marchesi</p> <p class="dwt_publisher"></p> <p class="publishDate">1993-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_18");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' 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onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">381</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=N9410906"> <span id="translatedtitle">Detecting Non-Linearities in Stationary <span class="hlt">Time</span> <span class="hlt">Series</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">The results concerning the question of how to decide whether a given stationary <span class="hlt">time</span> <span class="hlt">series</span> is adequately described by a linear stochastic model or contains non linearities are surveyed . In particular, it is considered whether a given <span class="hlt">time</span> <span class="hlt">series</span> shows a...</p> <div class="credits"> <p class="dwt_author">F. Takens</p> <p class="dwt_publisher"></p> <p class="publishDate">1992-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">382</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/d574161617k60423.pdf"> <span id="translatedtitle">Wavelet Enhanced Analytical and Evolutionary Approaches to <span class="hlt">Time</span> <span class="hlt">Series</span> Forecasting</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This paper provides two methodologies for forecasting <span class="hlt">time</span> <span class="hlt">series</span>. One of them is based on the Wavelet Analysis and the other\\u000a one on the Genetic Programming. Two examples from finance domain are used to illustrate how given methodologies perform in\\u000a real-life applications. Additionally application to specific classes of <span class="hlt">time</span> <span class="hlt">series</span>, seasonal, is discussed.</p> <div class="credits"> <p class="dwt_author">Bartosz Kozlowski</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">383</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.springerlink.com/index/c3nueqxjftc7fcl2.pdf"> <span id="translatedtitle">Change Detection in <span class="hlt">Time</span> <span class="hlt">Series</span> Data Using Wavelet Footprints</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Detecting changes in <span class="hlt">time</span> <span class="hlt">series</span> data is an important data analysis task with application in various scientific domains. In this paper, we propose a novel approach to address the problem of change detection in <span class="hlt">time</span> <span class="hlt">series</span> data, which can find both the amplitude and degree of changes. Our ap- proach is based on wavelet footprints proposed originally by the signal</p> <div class="credits"> <p class="dwt_author">Mehdi Sharifzadeh; Farnaz Azmoodeh; Cyrus Shahabi</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">384</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2195242"> <span id="translatedtitle">Optimal multi-scale patterns in <span class="hlt">time</span> <span class="hlt">series</span> streams</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">We introduce a method to discover optimal local patterns, which concisely describe the main trends in a <span class="hlt">time</span> <span class="hlt">series</span>. Our approach examines the <span class="hlt">time</span> <span class="hlt">series</span> at multiple time scales (i.e., window sizes) and efficiently discovers the key patterns in each. We also introduce a criterion to select the best window sizes, which most concisely capture the key oscillatory as well</p> <div class="credits"> <p class="dwt_author">Spiros Papadimitriou; Philip S. Yu</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">385</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50952194"> <span id="translatedtitle">Improvements in accurate GPS positioning using <span class="hlt">time</span> <span class="hlt">series</span> analysis</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Although the Global Positioning System (GPS) is used widely in car navigation systems, cell phones, surveying, and other areas, several issues still exist. We focus on the continuous data received in public use of GPS, and propose a new positioning algorithm that uses <span class="hlt">time</span> <span class="hlt">series</span> analysis. By fitting an autoregressive model to the <span class="hlt">time</span> <span class="hlt">series</span> model of the pseudorange, we</p> <div class="credits"> <p class="dwt_author">Yuichiro Koyama; Toshiyuki Tanaka</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">386</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/89427"> <span id="translatedtitle">Aligning gene expression <span class="hlt">time</span> <span class="hlt">series</span> with time warping algorithms</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Motivation: Increasingly, biological processes are being studied through <span class="hlt">time</span> <span class="hlt">series</span> of RNA expression data col- lected for large numbers of genes. Because common pro- cesses may unfold at varying rates in different experiments or individuals, methods are needed that will allow corre- sponding expression states in different <span class="hlt">time</span> <span class="hlt">series</span> to be mapped to one another. Results: We present implementations of</p> <div class="credits"> <p class="dwt_author">John Aach; George M. Church</p> <p class="dwt_publisher"></p> <p class="publishDate">2001-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">387</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://eric.ed.gov/?q=variance+AND+sensitivity+AND+analysis&pg=2&id=EJ966292"> <span id="translatedtitle">Small Sample Properties of Bayesian Multivariate Autoregressive <span class="hlt">Time</span> <span class="hlt">Series</span> Models</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p class="result-summary">|The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) <span class="hlt">time</span> <span class="hlt">series</span> model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive <span class="hlt">time</span> <span class="hlt">series</span> vectors of varying…</p> <div class="credits"> <p class="dwt_author">Price, Larry R.</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">388</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ars.usda.gov/research/publications/Publications.htm?seq_no_115=208402"> <span id="translatedtitle">Spectral Procedures Enhance the Analysis of Three Agricultural <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ars.usda.gov/services/TekTran.htm">Technology Transfer Automated Retrieval System (TEKTRAN)</a></p> <p class="result-summary">Many agricultural and environmental variables are influenced by cyclic processes that occur naturally. Consequently their <span class="hlt">time</span> <span class="hlt">series</span> often have cyclic behavior. This study developed <span class="hlt">times</span> <span class="hlt">series</span> models for three different phenomenon: (1) a 60 year-long state average crop yield record, (2) a four ...</p> <div class="credits"> <p class="dwt_author"></p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">389</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/49193442"> <span id="translatedtitle">Wavelets-based clustering of multivariate <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Crisp and fuzzy clustering methods based on a combination of univariate and multivariate wavelet features are considered for the clustering of multivariate <span class="hlt">time</span> <span class="hlt">series</span>. The performance of each of these methods is evaluated for stationary and variance nonstationary multivariate <span class="hlt">time</span> <span class="hlt">series</span> with different error correlation structures. The main outcomes of the simulation studies are are as follows: the superior performance</p> <div class="credits"> <p class="dwt_author">Pierpaolo D'Urso; Elizabeth Ann Maharaj</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">390</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/13291527"> <span id="translatedtitle">On the Detection of Contemporaneous Relationships Among Multiple <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">The Box and Tiao (1977) canonical <span class="hlt">time</span> <span class="hlt">series</span> approach considers linear combinations of multiple <span class="hlt">time</span> <span class="hlt">series</span> and ranks them according to their predictability. When dealing with individually non stationary sequences, it is the least predictable components that are of interest as they suggest cointegrated stationary relationships. In this article, we review the Box and Tiao (1977) approach and point out</p> <div class="credits"> <p class="dwt_author">Johannes Ledolter</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">391</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/57798909"> <span id="translatedtitle">Forecasting Trending <span class="hlt">Time</span> <span class="hlt">Series</span> with Relative Growth Rate Models</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Many annual <span class="hlt">time</span> <span class="hlt">series</span> in socioeconomic systems are steadily increasing functions of time. This paper deals with an empirical approach to analyzing and projecting such trending <span class="hlt">time</span> <span class="hlt">series</span> from models of relative growth rates or percent changes. A class of relative growth rate models is defined which includes the linear. exponential, modified exponential and logistic growth curves as special eases.</p> <div class="credits"> <p class="dwt_author">Hans Levenbach; Blake E. Reuter</p> <p class="dwt_publisher"></p> <p class="publishDate">1976-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">392</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/6559040"> <span id="translatedtitle">Interaction-Based Clustering of Multivariate <span class="hlt">Time</span> <span class="hlt">Series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">In this paper, we present a novel approach to clustering multivariate <span class="hlt">time</span> <span class="hlt">series</span>. In contrast to previous approaches, we base our cluster notion on the interactions between the univariate <span class="hlt">time</span> <span class="hlt">series</span> within a data object. Our objective is to assign objects with a similar intrinsic interaction pattern to a common cluster. To formalize this idea, we define a cluster by</p> <div class="credits"> <p class="dwt_author">Claudia Plant; Afra M. Wohlschlager; Andrew Zherdin</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">393</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/2595308"> <span id="translatedtitle">A nearest neighbor bootstrap for resampling hydrologic <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A nonparametric method for resampling scalar or vector-valued <span class="hlt">time</span> <span class="hlt">series</span> is introduced. Multivariate nearest neighbor probability density estimation provides the basis for the resampling scheme developed. The motivation for this work comes from a desire to preserve the dependence structure of the <span class="hlt">time</span> <span class="hlt">series</span> while bootstrapping (resampling it with replacement). The method is data driven and is preferred where the</p> <div class="credits"> <p class="dwt_author">Upmanu Lall; Ashish Sharma</p> <p class="dwt_publisher"></p> <p class="publishDate">1996-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">394</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/12245186"> <span id="translatedtitle">Neural Networks, Game Theory and <span class="hlt">Time</span> <span class="hlt">Series</span> Generation</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">This dissertation highlights connections between the fields of neural networks, game theory and <span class="hlt">time</span> <span class="hlt">series</span> generation. The concept of antipredictability is explained, and the properties of <span class="hlt">time</span> <span class="hlt">series</span> that are antipredictable for several prototypical prediction algorithms (neural networks, Boolean funtions etc.) are studied. The Minority Game provides a framework in which antipredictability arises naturally. Several variations of the MG are</p> <div class="credits"> <p class="dwt_author">Richard Metzler</p> <p class="dwt_publisher"></p> <p class="publishDate">2002-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">395</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2009EGUGA..1110555C"> <span id="translatedtitle">Multiscale/Multitemporal Urban pattern morphology monitoring in southern Italy by using Landsat TM <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The size distribution and the dynamic expansion of urban areas is a key issue for the management of city growth and mitigation of negative impacts on environment and ecosystems. Even if urban growth is perceived as necessary for a sustainable economy, uncontrolled or sprawling urban growth can cause various problems such as loss of open space, landscape alteration, environmental pollution, traffic congestion, infrastructure pressure, and other social and economical issues. To face these drawbacks, a continuous monitoring of the urban growth evolution in terms of type and extent of changes over time is essential for supporting planners and decision makers in future urban planning. The analysis of the city size distribution deals with different disciplines such as geography, economy, demography, ecology, physics, statistics because the evolution of a city is a dynamic process involving a number of different factors. The main issue of great importance in modelling urban growth includes spatial and temporal dynamics, scale dynamics, man-induced land use change. The understanding and the monitoring of urban expansion processes are a challenging issue concerning the availability of both (i) <span class="hlt">time-series</span> data set and (ii) updated information relating to current urban spatial structure and city edges in order to define and locate the evolution trends. In such a context, an effective contribution can be offered by <span class="hlt">satellite</span> remote sensing technologies, which are able to provide both historical data archive and up-to-date imagery. <span class="hlt">Satellite</span> technologies represent a cost-effective mean for obtaining useful data that can be easily and systematically updated for the whole globe. The use of <span class="hlt">satellite</span> imagery along with spatial analysis techniques can be used for the monitoring and planning purposes as these enable the reporting of ongoing trends of urban growth at a detailed level. This paper analyses the spatial characterization of urban expansion by using multidate Multispectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) <span class="hlt">satellite</span> imagery. The investigation was focused on four small towns in southern Italy, for which the border was extracted from NASA Landsat <span class="hlt">images</span> acquired in 1976 (MSS), in 1991 (TM) and 1999 (ETM). The border was analyzed using the box counting method, which is a well-know technique to estimate the spatial fractal dimension, that quantifies the shape irregularity of an object. The obtained results show that the fractal dimension of the border of the investigated towns is a good indicator of the dynamics of the regular/irregular urban expansion.</p> <div class="credits"> <p class="dwt_author">Coluzzi, R.; Didonna, I.</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">396</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://pubs.er.usgs.gov/publication/pp1386"> <span id="translatedtitle"><span class="hlt">Satellite</span> <span class="hlt">image</span> atlas of glaciers of the world</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p class="result-summary">U.S. Geological Survey Professional Paper 1386, <span class="hlt">Satellite</span> <span class="hlt">Image</span> Atlas of Glaciers of the World, contains 11 chapters designated by the letters A through K. Chapter A provides a comprehensive, yet concise, review of the "State of the Earth's Cryosphere at the Beginning of the 21st Century: Glaciers, Global Snow Cover, Floating Ice, and Permafrost and Periglacial Environments," and a "Map/Poster of the Earth's Dynamic Cryosphere," and a set of eight "Supplemental Cryosphere Notes" about the Earth's Dynamic Cryosphere and the Earth System. The next 10 chapters, B through K, are arranged geographically and present glaciological information from Landsat and other sources of historic and modern data on each of the geographic areas. Chapter B covers Antarctica; Chapter C, Greenland; Chapter D, Iceland; Chapter E, Continental Europe (except for the European part of the former Soviet Union), including the Alps, the Pyrenees, Norway, Sweden, Svalbard (Norway), and Jan Mayen (Norway); Chapter F, Asia, including the European part of the former Soviet Union, China, Afghanistan, Pakistan, India, Nepal, and Bhutan; Chapter G, Turkey, Iran, and Africa; Chapter H, Irian Jaya (Indonesia) and New Zealand; Chapter I, South America; Chapter J, North America (excluding Alaska); and Chapter K, Alaska. Chapters A–D each include map plates.</p> <div class="credits"> <p class="dwt_author">Edited by Williams, Richard S., Jr.; Ferrigno, Jane G.</p> <p class="dwt_publisher"></p> <p class="publishDate">1988-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">397</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013SPIE.8871E..06A"> <span id="translatedtitle">Improving multispectral <span class="hlt">satellite</span> <span class="hlt">image</span> compression using onboard subpixel registration</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Future CNES earth observation missions will have to deal with an ever increasing telemetry data rate due to improvements in resolution and addition of spectral bands. Current CNES <span class="hlt">image</span> compressors implement a discrete wavelet transform (DWT) followed by a bit plane encoding (BPE) but only on a mono spectral basis and do not profit from the multispectral redundancy of the observed scenes. Recent CNES studies have proven a substantial gain on the achievable compression ratio, +20% to +40% on selected scenarios, by implementing a multispectral compression scheme based on a Karhunen Loeve transform (KLT) followed by the classical DWT+BPE. But such results can be achieved only on perfectly registered bands; a default of registration as low as 0.5 pixel ruins all the benefits of multispectral compression. In this work, we first study the possibility to implement a multi-bands subpixel onboard registration based on registration grids generated on-the-fly by the <span class="hlt">satellite</span> attitude control system and simplified resampling and interpolation techniques. Indeed bands registration is usually performed on ground using sophisticated techniques too computationally intensive for onboard use. This fully quantized algorithm is tuned to meet acceptable registration performances within stringent <span class="hlt">image</span> quality criteria, with the objective of onboard real-time processing. In a second part, we describe a FPGA implementation developed to evaluate the design complexity and, by extrapolation, the data rate achievable on a spacequalified ASIC. Finally, we present the impact of this approach on the processing chain not only onboard but also on ground and the impacts on the design of the instrument.</p> <div class="credits"> <p class="dwt_author">Albinet, Mathieu; Camarero, Roberto; Isnard, Maxime; Poulet, Christophe; Perret, Jokin</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">398</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23705469"> <span id="translatedtitle">[The meteorological <span class="hlt">satellite</span> spectral <span class="hlt">image</span> registration based on Fourier-Mellin transform].</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The meteorological <span class="hlt">satellite</span> spectral <span class="hlt">image</span> is an effective tool for researches on meteorological science and environmental remote sensing science. <span class="hlt">Image</span> registration is the basis for the application of the meteorological <span class="hlt">satellite</span> spectral <span class="hlt">image</span> data. In order to realize the registration of the <span class="hlt">satellite</span> <span class="hlt">image</span> and the template <span class="hlt">image</span>, a new registration method based on the Fourier-Mellin transform is presented in this paper. Firstly, we use the global coastline vector map data to build a landmark template, which is a reference for the meteorological <span class="hlt">satellite</span> spectral <span class="hlt">image</span> registration. Secondly, we choose infrared sub-<span class="hlt">image</span> of no cloud according to the cloud channel data, and extract the edges of the infrared <span class="hlt">image</span> by Sobel operator. Finally, the affine transform model parameters between the landmark template and the <span class="hlt">satellite</span> <span class="hlt">image</span> are determined by the Fourier-Mellin transform, and thus the registration is realized. The proposed method is based on the curve matching in essence. It needs no feature point extraction, and can greatly simplify the process of registration. The experimental results using the infrared spectral data of the FY-2D meteorological <span class="hlt">satellite</span> show that the method is robust and can reach a high speed and high accuracy. PMID:23705469</p> <div class="credits"> <p class="dwt_author">Wang, Liang; Liu, Rong; Zhang, Li; Duan, Fu-Qing; Lü, Ke</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-03-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">399</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=N7231190"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">Series</span> and Growth Curves Part 1 Survey of <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis . Zeitreihen und Wachstumskurven Teil 1 Ueberblick ueber Zeitreihenanalysen.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">The possibilities are described for using <span class="hlt">time</span> <span class="hlt">series</span> analysis in prognosis and planning. <span class="hlt">Time</span> <span class="hlt">series</span> are the most important basis of information for all long term prognoses and planning. In view of the increasing importance of long term planning in telec...</p> <div class="credits"> <p class="dwt_author">H. Petersen</p> <p class="dwt_publisher"></p> <p class="publishDate">1971-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">400</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/4610057"> <span id="translatedtitle">Flow Analysis of Cloud <span class="hlt">Images</span> from Geostationary <span class="hlt">Satellites</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Geostationary <span class="hlt">satellites</span> are a valuable source of rain- fall information due to the availability of a global view of clouds at an acceptable spatial and temporal resolution. However to retrieve the information from the <span class="hlt">satellite</span> im- ages is a significant challenge. For example, precipita- tion peaks while the cloud area is rapidly growing and reduces at the time of maximum</p> <div class="credits"> <p class="dwt_author">Aimamorn Suvichakorn; Adrian R. Tatnall</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_19");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' href="#">4</a> 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onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">401</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013SPIE.8871E..0IB"> <span id="translatedtitle">An FPGA implemented bridge over water recognition for an <span class="hlt">image</span> evaluation on-board of <span class="hlt">satellites</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">This paper presents an advanced method for the automatic recognition of bridges over water in high resolution <span class="hlt">satellite</span> <span class="hlt">image</span> data, intended for an application on-board of <span class="hlt">satellites</span>. The algorithm is implemented in recon gurable hardware, a so-called Field Programmable Gate Array (FPGA). Within a few seconds a thematic map is derived from the original <span class="hlt">satellite</span> <span class="hlt">image</span>. The map contains information about the water areas, islands and bridge deck areas in the captured scene. No a-priory knowledge is needed. Due to the autonomous <span class="hlt">image</span> processing and the low power consumption of the FPGA, this implementation seems suitable for an application on-board of <span class="hlt">satellites</span>. Especially in case of a natural disaster it could provide quick information about accessible transportation routes. The algorithm as well as experimental results on panchromatic and near-infrared <span class="hlt">satellite</span> imagery are presented in this article. The obtained results are promising.</p> <div class="credits"> <p class="dwt_author">Beulig, Sebastian; v. Schönermark, Maria; Huber, Felix</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">402</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3478812"> <span id="translatedtitle">Sensor-Generated <span class="hlt">Time</span> <span class="hlt">Series</span> Events: A Definition Language</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p class="result-summary">There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as <span class="hlt">time</span> <span class="hlt">series</span>. In many domains, like seismography or medicine, <span class="hlt">time</span> <span class="hlt">series</span> analysis focuses on particular regions of interest, known as events, whereas the remainder of the <span class="hlt">time</span> <span class="hlt">series</span> contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in <span class="hlt">time</span> <span class="hlt">series</span> recorded by sensors in any domain. The proposed language has been applied to the definition of <span class="hlt">time</span> <span class="hlt">series</span> events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated <span class="hlt">time</span> <span class="hlt">series</span>. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the <span class="hlt">time</span> <span class="hlt">series</span>.</p> <div class="credits"> <p class="dwt_author">Anguera, Aurea; Lara, Juan A.; Lizcano, David; Martinez, Maria Aurora; Pazos, Juan</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">403</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EGUGA..1511989V"> <span id="translatedtitle">Detecting and visualizing structural changes in groundwater head <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Since the fifties of the past century the dynamic behavior of the groundwater head has been monitored at many locations throughout the Netherlands and elsewhere. The data base of the Geological Survey of the Netherlands contains over 30,000 groundwater <span class="hlt">time</span> <span class="hlt">series</span>. For many water management purposes characteristics of the dynamic behavior are required, such as average, median, percentile etc.. These characteristics are estimated from the <span class="hlt">time</span> <span class="hlt">series</span>. In principle, the longer the <span class="hlt">time</span> <span class="hlt">series</span>, the more reliable the estimate. However, due to natural as well as man induced changes, the characteristics of a long <span class="hlt">time</span> <span class="hlt">series</span> are often changing in time as well. For water management it is important to be able to distinguish extreme values as part of the 'normal' pattern from structural changes in the groundwater regime. Whether or not structural changes are present in the <span class="hlt">time</span> <span class="hlt">series</span> can't be decided completely objective. Choices have to be made concerning the length of the period and the statistical parameters. Here a method is proposed to visualize the probability of structural changes in the <span class="hlt">time</span> <span class="hlt">series</span> using well known basic statistical tests. The visualization method is based on the mean values and standard deviation in a moving window. Apart from several characteristics that are calculated for each period separately, all pairs of two periods are compared and the difference is statistically tested. The results of these well known tests are combined in a visualization to supply to the user comprehensive information to examine structural changes in <span class="hlt">time</span> <span class="hlt">series</span>.</p> <div class="credits"> <p class="dwt_author">van Geer, Frans</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">404</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23112685"> <span id="translatedtitle">Sensor-generated <span class="hlt">time</span> <span class="hlt">series</span> events: a definition language.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as <span class="hlt">time</span> <span class="hlt">series</span>. In many domains, like seismography or medicine, <span class="hlt">time</span> <span class="hlt">series</span> analysis focuses on particular regions of interest, known as events, whereas the remainder of the <span class="hlt">time</span> <span class="hlt">series</span> contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in <span class="hlt">time</span> <span class="hlt">series</span> recorded by sensors in any domain. The proposed language has been applied to the definition of <span class="hlt">time</span> <span class="hlt">series</span> events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated <span class="hlt">time</span> <span class="hlt">series</span>. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the <span class="hlt">time</span> <span class="hlt">series</span>. PMID:23112685</p> <div class="credits"> <p class="dwt_author">Anguera, Aurea; Lara, Juan A; Lizcano, David; Martínez, Maria Aurora; Pazos, Juan</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-08-29</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">405</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/16383481"> <span id="translatedtitle">Wavelet analysis and scaling properties of <span class="hlt">time</span> <span class="hlt">series</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">We propose a wavelet based method for the characterization of the scaling behavior of nonstationary <span class="hlt">time</span> <span class="hlt">series</span>. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal <span class="hlt">time</span> <span class="hlt">series</span> with the present and earlier approaches of detrending for comparison, we analyze the <span class="hlt">time</span> <span class="hlt">series</span> of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multifractal behavior. PMID:16383481</p> <div class="credits"> <p class="dwt_author">Manimaran, P; Panigrahi, Prasanta K; Parikh, Jitendra C</p> <p class="dwt_publisher"></p> <p class="publishDate">2005-10-18</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">406</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2006PhyA..363..481H"> <span id="translatedtitle">The application of neural networks to forecast fuzzy <span class="hlt">time</span> <span class="hlt">series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Fuzzy <span class="hlt">time</span> <span class="hlt">series</span> models have been applied to handle nonlinear problems. To forecast fuzzy <span class="hlt">time</span> <span class="hlt">series</span>, this study applies a backpropagation neural network because of its nonlinear structures. We propose two models: a basic model using a neural network approach to forecast all of the observations, and a hybrid model consisting of a neural network approach to forecast the known patterns as well as a simple method to forecast the unknown patterns. The stock index in Taiwan for the years 1991 2003 is chosen as the forecasting target. The empirical results show that the hybrid model outperforms both the basic and a conventional fuzzy <span class="hlt">time</span> <span class="hlt">series</span> models.</p> <div class="credits"> <p class="dwt_author">Huarng, Kunhuang; Yu, Tiffany Hui-Kuang</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-05-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">407</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/23367072"> <span id="translatedtitle">High performance biomedical <span class="hlt">time</span> <span class="hlt">series</span> indexes using salient segmentation.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">The advent of remote and wearable medical sensing has created a dire need for efficient medical <span class="hlt">time</span> <span class="hlt">series</span> databases. Wearable medical sensing devices provide continuous patient monitoring by various types of sensors and have the potential to create massive amounts of data. Therefore, <span class="hlt">time</span> <span class="hlt">series</span> databases must utilize highly optimized indexes in order to efficiently search and analyze stored data. This paper presents a highly efficient technique for indexing medical <span class="hlt">time</span> <span class="hlt">series</span> signals using Locality Sensitive Hashing (LSH). Unlike previous work, only salient (or interesting) segments are inserted into the index. This technique reduces search times by up to 95% while yielding near identical search results. PMID:23367072</p> <div class="credits"> <p class="dwt_author">Woodbridge, Jonathan; Mortazavi, Bobak; Bui, Alex A T; Sarrafzadeh, Majid</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">408</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2013EL....10210004D"> <span id="translatedtitle">Testing <span class="hlt">time</span> <span class="hlt">series</span> irreversibility using complex network methods</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The absence of time-reversal symmetry is a fundamental property of many nonlinear <span class="hlt">time</span> <span class="hlt">series</span>. Here, we propose a new set of statistical tests for <span class="hlt">time</span> <span class="hlt">series</span> irreversibility based on standard and horizontal visibility graphs. Specifically, we statistically compare the distributions of time-directed variants of the common complex network measures degree and local clustering coefficient. Our approach does not involve surrogate data and is applicable to relatively short <span class="hlt">time</span> <span class="hlt">series</span>. We demonstrate its performance for paradigmatic model systems with known time-reversal properties as well as for picking up signatures of nonlinearity in neuro-physiological data.</p> <div class="credits"> <p class="dwt_author">Donges, Jonathan F.; Donner, Reik V.; Kurths, Jürgen</p> <p class="dwt_publisher"></p> <p class="publishDate">2013-04-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">409</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/54535227"> <span id="translatedtitle">Small <span class="hlt">satellite</span> plan for <span class="hlt">imaging</span> observation of the ionosphere, mesosphere, thermosphere and plasmasphere</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A small <span class="hlt">satellite</span> project is planned for the global <span class="hlt">imaging</span> observation of the ionosphere mesosphere thermosphere and plasmasphere by a Japanese scientist group The <span class="hlt">satellite</span> is designed in aiming to be launched to the geo-transfer orbit in the next solar maximum between 2011 and 2013 The observation is focused on the Earth s upper atmospheres in the mid- and low-latitude</p> <div class="credits"> <p class="dwt_author">A. Saito</p> <p class="dwt_publisher"></p> <p class="publishDate">2006-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">410</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/51008699"> <span id="translatedtitle">Application of genetic algorithm in tracking convective cloud <span class="hlt">images</span> from Chinese FY2C <span class="hlt">satellite</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">It is significance to identify and track convective clouds using <span class="hlt">satellite</span> data in nowcasting and severe weather warning. This article uses genetic algorithm to match and track convection clouds identified from infrared channel <span class="hlt">images</span> of FY - 2C <span class="hlt">satellite</span>. The preliminary results suggest that the genetic algorithm need set up enough group size & genetic algebra, and can select appropriate</p> <div class="credits"> <p class="dwt_author">Xiaofang Pei; Nan Li; Yating Zhan</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">411</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://redibericamm5.uib.es/publicacions/any1997/g07_Articulo2_97.pdf"> <span id="translatedtitle">Forecasting of Chaotic Cloud Absorption <span class="hlt">Time</span> <span class="hlt">Series</span> for Meteorological and Plume Dispersion Modeling</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">A nonlinear forecasting method based on the reconstruction of a chaotic strange attractor from about 1.5 years of cloud absorption data obtained from half-hourly Meteosat infrared <span class="hlt">images</span> was used to predict the behavior of the <span class="hlt">time</span> <span class="hlt">series</span> 24 h in advance. The forecast values are then used by a meteorological model for daily prediction of plume transport from the As</p> <div class="credits"> <p class="dwt_author">V. P EREZ-MUNUZURI</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">412</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50342916"> <span id="translatedtitle">A SAR <span class="hlt">time</span> <span class="hlt">series</span> analysis toolbox for extracting fire affected areas in wetlands</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">During the period 1999-2000 frequent fires occurred in the delta of Parana´ River, Buenos Aires, Argentina. A set of 13 ERS 2 <span class="hlt">images</span> were collected within the frame of the ESA AO3 232 project. One of the basic concerns when trying to make use of these data for <span class="hlt">time</span> <span class="hlt">series</span> analysis is the need of tools for calibration of the</p> <div class="credits"> <p class="dwt_author">H. Karszenbaum; J. Tiffenberg; F. Grings; J. M. Martinez; P. Kandus; P. Pratolongo</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">413</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.earsel.org/workshops/ForestFires2007/58-141_Fire%20Risk%20Estimation/Time%20series%20analysis%20of%20remote%20sensing%20to%20calculate%20and%20map%20operational%20indicators%20of%20wildfire%20risk.pdf"> <span id="translatedtitle"><span class="hlt">Time</span> <span class="hlt">series</span> analysis of remote sensing to calculate and map operational indicators of wildfire risk</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">MODIS ABSTRACT: This study is intended to show the ability of <span class="hlt">time</span> <span class="hlt">series</span> of remote sensing <span class="hlt">images</span> to estimate vegetation fire susceptibility in a Mediterranean r egion of France (Aude province). Remote sensing data consist in MODIS-Terra 16 days synthesis products acquired from 2000 to 2006 and we analysed both spatial and temporal components of the dataset. Two synthetic indicators</p> <div class="credits"> <p class="dwt_author">J. P. Denux; W. Sampara; M. Gay</p> <p class="dwt_publisher"></p> <p class="publishDate"></p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">414</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2012cosp...39..685G"> <span id="translatedtitle">Research on Complicated <span class="hlt">Imaging</span> Condition of GEO Optical High Resolution Earth Observing <span class="hlt">Satellite</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">The requirement for high time and space resolution of optical remote sensing <span class="hlt">satellite</span> in disaster, land resources, environment, marine monitoring and meteorology observation, etc is getting urgent and strict. For that reason, a remote sensing <span class="hlt">satellite</span> system solely located in MEO or LEO cannot operate continuous observation and Surveillance. GEO optical high resolution earth observing <span class="hlt">satellite</span> in the other hand can keep the mesoscale and microscale target under continuous surveillance by controlling line of sight(LOS), and can provide <span class="hlt">imaging</span> observation of an extensive region in a short time. The advantages of GEO <span class="hlt">satellite</span> such as real-time observation of the mesoscale and microscale target, rapid response of key events, have been recognized by lots of countries and become a new trend of remote sensing <span class="hlt">satellite</span>. As many advantages as the GEO remote sensing <span class="hlt">satellite</span> has, its <span class="hlt">imaging</span> condition is more complicated. Many new characteristics of <span class="hlt">imaging</span> observation and <span class="hlt">imaging</span> quality need to be discussed. We analyze each factor in the remote sensing link, using theoretical analysis and modeling simulation to get coefficient of each factor to represent its effect on <span class="hlt">imaging</span> system. Such research achievements can provide reference for <span class="hlt">satellite</span> mission analysis and system design.</p> <div class="credits"> <p class="dwt_author">Guo, Linghua</p> <p class="dwt_publisher"></p> <p class="publishDate">2012-07-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">415</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50757817"> <span id="translatedtitle">Application of Principal Component Extraction technique in processing cloud <span class="hlt">images</span> from Chinese FY1 <span class="hlt">satellite</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Principal component extraction technique is employed to process cloud <span class="hlt">images</span> from 10-channel radiometer onboard the Chinese FY-1 polar-orbiting meteorological <span class="hlt">satellites</span>. The results suggest that the consensus technique can concentrate the prominent distribution features of the grey shades of the targets, including clouds, landform and oceans shown on the 10 channel <span class="hlt">images</span> into a single <span class="hlt">image</span> which can be then used</p> <div class="credits"> <p class="dwt_author">Zhenhui Wang; Xiaofang Pei</p> <p class="dwt_publisher"></p> <p class="publishDate">2009-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">416</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/54422778"> <span id="translatedtitle">ONLINE <span class="hlt">satellite</span> <span class="hlt">images</span> and educational material: the Danish Galathea 3 world expedition under and after</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary">Students and teachers may use ONLINE <span class="hlt">satellite</span> <span class="hlt">image</span> in the classroom. <span class="hlt">Images</span> have been archived since August 2006 and the archive is updated every day since. This means that series of nearly four years of daily global <span class="hlt">images</span> are available online. The parameters include ocean surface temperature, sea level anomaly, ocean wave height, ocean winds, global ozone in the atmosphere</p> <div class="credits"> <p class="dwt_author">Charlotte Bay Hasager; Peter Brøgger Sørensen; Ole Baltazar Andersen; Merete Badger; Niels Kristian Højerslev; Jacob L. Høyer; Bo Løkkegaard; Jürg Lichtenegger; Lotte Nyborg; Roberto Saldo</p> <p class="dwt_publisher"></p> <p class="publishDate">2010-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">417</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=DE200415007470"> <span id="translatedtitle">Use of Machine Vision Techniques to Detect Human Settlements in <span class="hlt">Satellite</span> <span class="hlt">Images</span>.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">The automated production of maps of human settlement from recent <span class="hlt">satellite</span> <span class="hlt">images</span> is essential to studies of urbanization, population movement, and the like. The spectral and spatial resolution of such imagery is often high enough to successfully apply co...</p> <div class="credits"> <p class="dwt_author">C. Kamath S. K. Sengupta D. Poland J. A. H. Futterman</p> <p class="dwt_publisher"></p> <p class="publishDate">2003-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">418</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://academic.research.microsoft.com/Publication/50617448"> <span id="translatedtitle">Fusion of multispectral and panchromatic <span class="hlt">satellite</span> <span class="hlt">images</span> based on ihs and curvelet transformations</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://academic.research.microsoft.com/">Microsoft Academic Search </a></p> <p class="result-summary"><span class="hlt">Image</span> fusion is an important tool for remote sensing data processing technology, as many Earth observation <span class="hlt">satellites</span> provide both high-resolution panchromatic and low-resolution multispectral <span class="hlt">images</span>. This paper presents a new <span class="hlt">image</span> fusion method that combines IHS transform and curvelet transform. Experiments carried out on a enhanced thematic mapper plus <span class="hlt">image</span> show that the proposed method quantitatively outperforms state-of-the art <span class="hlt">image</span></p> <div class="credits"> <p class="dwt_author">Man Wang; Jie-Lin Zhang; Dai-Yong Cao</p> <p class="dwt_publisher"></p> <p class="publishDate">2007-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">419</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2011SPIE.8156E..26H"> <span id="translatedtitle">The extraction of multiple cropping index of China based on NDVI <span class="hlt">time-series</span></span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p class="result-summary">Multiple cropping index reflects the intensity of arable land been used by a certain planting system. The bond between multiple cropping index and NDVI <span class="hlt">time-series</span> is the crop cycle rule, which determines the crop process of seeding, jointing, tasseling, ripeness and harvesting and so on. The cycle rule can be retrieved by NDVI <span class="hlt">time-series</span> for that peaks and valleys on the <span class="hlt">time-series</span> curve correspond to different periods of crop growth. In this paper, we aim to extract the multiple cropping index of China from NDVI <span class="hlt">time-series</span>. Because of cloud contamination, some NDVI values are depressed. MVC (Maximum Value Composite) synthesis is used to SPOT-VGT data to remove the noise, but this method doesn't work sufficiently. In order to accurately extract the multiple cropping index, the algorithm HANTS (Harmonic Analysis of <span class="hlt">Time</span> <span class="hlt">Series</span>) is employed to remove the cloud contamination. The reconstructed NDVI <span class="hlt">time-series</span> can explicitly characterize the biophysical process of planting, seedling, elongating, heading, harvesting of crops. Based on the reconstructed curve, we calculate the multiple cropping index of arable land by extracting the number of peaks of the curve for that one peak represents one season crop. This paper presents a method to extracting the multiple cropping index from remote sensing <span class="hlt">image</span> and then the multiple cropping index of China is extracted from VEGETATION decadal composites NDVI <span class="hlt">time</span> <span class="hlt">series</span> of year 2000 and 2009. From the processed data, we can get the spatial distribution of tillage system of China, and then further discussion about cropping index change between the 10 years is conducted.</p> <div class="credits"> <p class="dwt_author">Huang, Haitao; Gao, Zhiqiang</p> <p class="dwt_publisher"></p> <p class="publishDate">2011-09-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">420</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=ADA080709"> <span id="translatedtitle">An Introduction to Applied Multiple <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">An approach to the modelling and analysis of multiple <span class="hlt">time</span> <span class="hlt">series</span> is proposed. Properties of a class of vector autoregressive moving average models are discussed. Modelling procedures consisting of tentative specification, estimation and diagnostic checki...</p> <div class="credits"> <p class="dwt_author">G. C. Tiao G. E. P. Box</p> <p class="dwt_publisher"></p> <p class="publishDate">1979-01-01</p> </div> </div> </div> </div> <div id="filter_results_form" class="filter_results_form floatContainer" style="visibility: visible;"> <div style="width:100%" id="PaginatedNavigation" class="paginatedNavigationElement"> <a id="FirstPageLink" onclick='return showDiv("page_1");' href="#" title="First Page"> <img id="FirstPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.first.18x20.png" alt="First Page" /></a> <a id="PreviousPageLink" onclick='return showDiv("page_20");' href="#" title="Previous Page"> <img id="PreviousPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.previous.18x20.png" alt="Previous Page" /></a> <span id="PageLinks" class="pageLinks"> <span> <a onClick='return showDiv("page_1");' href="#">1</a> <a onClick='return showDiv("page_2");' href="#">2</a> <a onClick='return showDiv("page_3");' href="#">3</a> <a onClick='return showDiv("page_4");' 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onclick='return showDiv("page_25.0");' href="#" title="Last Page"> <img id="LastPageLinkImage" class="Icon" src="http://www.science.gov/scigov/images/icon.last.18x20.png" alt="Last Page" /></a> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">421</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=PB80213978"> <span id="translatedtitle">Applications of <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis to Geophysical Data.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">This thesis consists of three papers applying the techniques of <span class="hlt">time</span> <span class="hlt">series</span> analysis to geophysical data. Surface wave dispersion along the Walvis Ridge, South Atlantic Ocean, is obtained by bandpass filtering the recorded seismogram in the frequency doma...</p> <div class="credits"> <p class="dwt_author">A. Chave</p> <p class="dwt_publisher"></p> <p class="publishDate">1980-01-01</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">422</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ntis.gov/search/product.aspx?ABBR=ADA222337"> <span id="translatedtitle">Adaptive <span class="hlt">Time</span> <span class="hlt">Series</span> Analysis Using Predictive Inference and Entropy.</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ntis.gov/search/index.aspx">National Technical Information Service (NTIS)</a></p> <p class="result-summary">Research is reported on adaptive <span class="hlt">time</span> <span class="hlt">series</span> methods for detecting and tracking both abrupt and slow changes in both structure and parameters of dynamic systems. The methods are based on a unified statistical framework which is motivated by statistical in...</p> <div class="credits"> <p class="dwt_author">R. K. Mehra S. Mahmood</p> <p class="dwt_publisher"></p> <p class="publishDate">1990-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">423</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.ncbi.nlm.nih.gov/pubmed/11017653"> <span id="translatedtitle">Prediction of spatiotemporal <span class="hlt">time</span> <span class="hlt">series</span> based on reconstructed local states</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p class="result-summary">Spatiotemporal <span class="hlt">time</span> <span class="hlt">series</span> are analyzed and predicted using reconstructed local states. As numerical examples the evolution of a Kuramoto-Sivashinsky equation and a coupled map lattice are predicted from previously sampled data. PMID:11017653</p> <div class="credits"> <p class="dwt_author">Parlitz; Merkwirth</p> <p class="dwt_publisher"></p> <p class="publishDate">2000-02-28</p> </div> </div> </div> </div> <div class="floatContainer result " lang="en"> <div class="resultNumber element">424</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://www.osti.gov/scitech/biblio/5607288"> <span id="translatedtitle">Practical overview of ARIMA models for <span class="hlt">time-series</span> forecasting</span></a>  </p> <div class="result-meta"> <p class="source"><a target="_blank" id="logoLink" href="http://www.osti.gov/scitech">SciTech Connect</a></p> <p class="result-summary">Single series analysis methodology is illustrated. The commentary summarizes the Box-Jenkins philosophy and the ARIMA model structure, with particular emphasis on practical aspects of application, forecast interpretation, strengths weaknesses, and comparison to other <span class="hlt">time</span> <span class="hlt">series</span> forecasting approaches. (GHT)</p> <div class="credits"> <p class="dwt_author">Pack, D.J.</p> <p class="dwt_publisher"></p> <p class="publishDate">1980-01-01</p> </div> </div> </div> </div> <div class="floatContainer result odd" lang="en"> <div class="resultNumber element">425</div> <div class="resultBody element"> <p class="result-title"><a target="resultTitleLink" href="http://science.gov/scigov/link.html?type=RESULT&redirectUrl=http://adsabs.harvard.edu/abs/2007embn.book...51C"> <span id="translatedtitle">Financial <span class="hlt">Time-series</span> Analysis: a Brief Overview</span></a>  </p> <div class="result-meta"> <p class="sour