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1

Clustering of satellite image time series under Time Warping  

Microsoft Academic Search

Satellite Image Time Series are becoming increasingly available and will continue to do so in the coming years thanks to the launch of space missions which aim at providing a coverage of the Earth every few days with high spatial resolution. In the case of optical imagery, it will be possible to produce land use and cover change maps with

Francois Petitjean; Jordi Inglada; Pierre Gancarskv

2011-01-01

2

A Nonlinear Harmonic Model for Fitting Satellite Image Time Series: Analysis and Prediction of Land Cover Dynamics  

Microsoft Academic Search

Numerous efforts have been made to develop models to fit multispectral reflectance and vegetation index (VI) time series from satellite images for diverse land cover classes. The common objective of these models is to derive a set of measurable parameters that are able to characterize and to reproduce the land cover dynamics of natural- and human-induced ecosystems. Good-fitting models should

Hugo Carrao; P. Gonalves; Mário Caetano

2010-01-01

3

Flood hazard and flood risk assessment using a time series of satellite images: a case study in Namibia.  

PubMed

In this article, the use of time series of satellite imagery to flood hazard mapping and flood risk assessment is presented. Flooded areas are extracted from satellite images for the flood-prone territory, and a maximum flood extent image for each flood event is produced. These maps are further fused to determine relative frequency of inundation (RFI). The study shows that RFI values and relative water depth exhibit the same probabilistic distribution, which is confirmed by Kolmogorov-Smirnov test. The produced RFI map can be used as a flood hazard map, especially in cases when flood modeling is complicated by lack of available data and high uncertainties. The derived RFI map is further used for flood risk assessment. Efficiency of the presented approach is demonstrated for the Katima Mulilo region (Namibia). A time series of Landsat-5/7 satellite images acquired from 1989 to 2012 is processed to derive RFI map using the presented approach. The following direct damage categories are considered in the study for flood risk assessment: dwelling units, roads, health facilities, and schools. The produced flood risk map shows that the risk is distributed uniformly all over the region. The cities and villages with the highest risk are identified. The proposed approach has minimum data requirements, and RFI maps can be generated rapidly to assist rescuers and decisionmakers in case of emergencies. On the other hand, limitations include: strong dependence on the available data sets, and limitations in simulations with extrapolated water depth values. PMID:24372226

Skakun, Sergii; Kussul, Nataliia; Shelestov, Andrii; Kussul, Olga

2014-08-01

4

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

Microsoft Academic Search

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)

Dirk Tiede; Stefan Lang

2009-01-01

5

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

NASA Technical Reports Server (NTRS)

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived from this study agree well with an existing urban extent polygon data set that was previously developed independently. The overall mapping accuracy was estimated at about 92.5% with 3% commission error and 12% omission error for the impervious type from all images regardless of image quality and initial spatial resolution.

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

2012-01-01

6

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

Microsoft Academic Search

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

L. L. Bourgeau-Chavez; E. Kasischke

2002-01-01

7

A radar image time series  

NASA Technical Reports Server (NTRS)

A set of ten side-looking radar images of a mining area in Arizona that were aquired over a period of 14 yr are studied to demonstrate the photogrammetric differential-rectification technique applied to radar images and to examine changes that occurred in the area over time. Five of the images are rectified by using ground control points and a digital height model taken from a map. Residual coordinate errors in ground control are reduced from several hundred meters in all cases to + or - 19 to 70 m. The contents of the radar images are compared with a Landsat image and with aerial photographs. Effects of radar system parameters on radar images are briefly reviewed.

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

1981-01-01

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

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

2010-11-01

10

Monitoring agricultural crop growth: comparison of high spatial-temporal satellite imagery versus UAV-based imaging spectrometer time series measurements  

NASA Astrophysics Data System (ADS)

In 2012, the Dutch National Satellite Data Portal (NSD) was launched as a preparation to the launch of the European SENTINEL satellites in the framework of the Copernicus Programme. At the same time the Unmanned Aerial Remote Sensing Facility (UARSF: www.wageningenUR.nl/uarsf) has been established as research facility at Wageningen University and Research Centre. The NSD became available for the development of services and advice through an investment from the Dutch government in collaboration with the Netherlands Space Office (NSO) in order to develop new services for precision agriculture. The NSD contains Formosat, Radarsat as well as DMC satellite imagery. The processing of the DMC imagery resulted in the Greenmonitor service (www.groenmonitor.nl). The Greenmonitor is an unique product that covers the Netherlands with a high spatial and temporal resolution. The Greenmonitor is now being exploited for various applications, amongst others crop identification, crop phenology, and identification of management activities. The UARSF of Wageningen UR has three objectives: 1) to develop innovation in the field of remote sensing science using Unmanned Aerial Vehicles (UAV) by providing a platform for dedicated and high-quality experiments; 2) to support high quality UAV services by providing calibration facilities and disseminating processing procedures to the UAV user community; 3) to promote and test the use of UAV in a broad range of application fields such as precision agriculture and habitat monitoring. Through this coincidence of new developments the goal of our study was to compare the information for the measurements of spatial variation in crops and soils as derived from high spatial-temporal satellite imagery from the national data portal compared to the exploitation of UAVs, in our case an Altura octocopter with a hyperspectral camera. As such, the focus is on the applications in precision agriculture. Both primary producers and chain partners and service providers are involved in the consortium. First results show that the Greenmonitor is much more suitable for comparison in growth between fields at regional scale, while UAV based imagery is much more suitable for mapping variation in crop biochemistry (i.e., chlorophyll, nitrogen) within the fields, which requires in the Netherlands a spatial resolution of a few meters. Finally, the spatial and spectral dimension of satellite and UAV derived vegetation indices (i.e., weighted difference vegetation index, chlorophyll red-edge index) to evaluate to which extent UAV based image acquisition could be adopted to complement missing data in satellite time-series.

Mucher, Sander; Roerink, Gerbert; Franke, Jappe; Suomalainen, Juha; Kooistra, Lammert

2014-05-01

11

Using time series of satellite SAR images to calibrate channel depth and friction parameters in the LISFLOOD-FP hydraulic model  

NASA Astrophysics Data System (ADS)

Synthetic Aperture Radar (SAR) satellites are capable of all-weather day/night observations that allow discrimination between land and smooth open water surfaces over large scales. Because of this there has been much interest in the use of SAR images to estimate flood extent and flood elevation in order to improve understanding of fluvial flood inundation processes. In past studies it has been proven that integrating SAR derived information with hydraulic models can improve simulations of flooding mechanisms. A repository of River Severn at Tewkesbury flood images from the ENVISAT satellite (wide-swath mode) have been processed and catalogued for events between 2005 and 2012. Information such as flood extent is taken from these images for floods occurring in 2007, 2008 and 2011 as the focus of this study. The flood events are simulated within a 2D LISFLOOD-FP Sub-Grid hydraulic model of the River Severn covering an area of 50x70km. The Sub-Grid capabilities of this particular version of LISFLOOD-FP allows any size of river channel below that of the grid resolution to be represented thus allowing improved hydraulic connectivity within the flooded area. The objective of this study is to calibrate the parameters of the LISFLOOD-FP Sub-Grid 2-D model that govern channel depth and channel roughness using SAR derived images of flood extent. Parameters 'r' and 'p' are variables used in the Sub-Grid model to define depth of channel at full bank. The equation estimates bank full depth D being equivalent to rWp¬¬, where W is bank full channel width. By varying the parameters 'r' and 'p' around an initial estimate we can create a number of unique models with ranging channel depth. It follows that models with differing channel depths generate results of differing flood levels and extent. The model calibration is achieved by selecting those models results with simulated flood extent which fit best with the observations of flood extent derived from the SAR images. A similar experiment was carried out to vary Manning's value 'n' (associated with channel roughness) with the channel depth parameter 'p' to determine whether the method would also work with pairings of two unrelated parameters. The study first compared the model simulations with a single SAR derived flood extent, then compared model results against a time series of images acquired over multiple flood events. This was to determine whether it is more useful in this method of calibration to use a time series of SAR derived extents. Validation is accomplished by use of surveyed cross sections of the Severn riverbed and aerial photographs, together with gauged records of discharge and water level located inside the limits of the model.

Wood, Melissa; Neal, Jeff; Hostache, Renaud; Corato, Giovanni; Bates, Paul; Giustarini, Laura; Chini, Marco; Matgen, Patrick

2014-05-01

12

Drought impact assessment from monitoring the seasonality of vegetation condition using long-term time-series satellite images: a case study of Mt. Kenya region.  

PubMed

Drought-induced anomalies in vegetation condition over wide areas can be observed by using time-series satellite remote sensing data. Previous methods to assess the anomalies may include limitations in considering (1) the seasonality in terms of each vegetation-cover type, (2) cumulative damage during the drought event, and (3) the application to various types of land cover. This study proposed an improved methodology to assess drought impact from the annual vegetation responses, and discussed the result in terms of diverse landscape mosaics in the Mt. Kenya region (0.4° N 35.8° E ~ 1.6° S 38.4° E). From the 30-year annual rainfall records at the six meteorological stations in the study area, we identified 2000 as the drought year and 2001, 2004, and 2007 as the normal precipitation years. The time-series profiles of vegetation condition in the drought and normal precipitation years were obtained from the values of Enhanced Vegetation Index (EVI; Huete et al. 2002), which were acquired from Terra MODIS remote sensing dataset (MOD13Q1) taken every 16 days at the scale of 250-m spatial resolution. The drought impact was determined by integrating the annual differences in EVI profiles between drought and normal conditions, per pixel based on nearly same day of year. As a result, we successfully described the distribution of landscape vulnerability to drought, considering the seasonality of each vegetation-cover type at every MODIS pixel. This result will contribute to the large-scale landscape management of Mt. Kenya region. Future study should improve this method by considering land-use change occurred during the long-term monitoring period. PMID:22972316

Song, Youngkeun; Njoroge, John B; Morimoto, Yukihiro

2013-05-01

13

Use of intra-annual satellite imagery time-series for land cover characterization purposes  

Microsoft Academic Search

Automatic image classification often fails at separating a large number of land cover classes that punctually may present similar spectral reflectances. To improve the classification accuracy of such situations, multi-temporal satellite data has proven valuable auxiliary information. In this paper, we present a study exploring the use fulness of intra-annual satellite images time-series for automatic land cover classi- fication. The

H. Carrao; P. Goncalves; M. Caetano

2007-01-01

14

Time series hyperspectral chemical imaging data: challenges, solutions and applications.  

PubMed

Hyperspectral chemical imaging (HCI) integrates imaging and spectroscopy resulting in three-dimensional data structures, hypercubes, with two spatial and one wavelength dimension. Each spatial image pixel in a hypercube contains a spectrum with >100 datapoints. While HCI facilitates enhanced monitoring of multi-component systems; time series HCI offers the possibility of a more comprehensive understanding of the dynamics of such systems and processes. This implies a need for modeling strategies that can cope with the large multivariate data structures generated in time series HCI experiments. The challenges posed by such data include dimensionality reduction, temporal morphological variation of samples and instrumental drift. This article presents potential solutions to these challenges, including multiway analysis, object tracking, multivariate curve resolution and non-linear regression. Several real world examples of time series HCI data are presented to illustrate the proposed solutions. PMID:21962370

Gowen, A A; Marini, F; Esquerre, C; O'Donnell, C; Downey, G; Burger, J

2011-10-31

15

Classification of satellite time series-derived land surface phenology focused on the northern Fertile Crescent  

NASA Astrophysics Data System (ADS)

Land surface phenology describes events in a seasonal vegetation cycle and can be used in a variety of applications from predicting onset of future drought conditions, to revealing potential limits of historical dry farming, to guiding more accurate dating of archeological sites. Traditional methods of monitoring vegetation phenology use data collected in situ. However, vegetation health indices derived from satellite remote sensor data, such as the normalized difference vegetation index (NDVI), have been used as proxy for vegetation phenology due to their repeated acquisition and broad area coverage. Land surface phenology is accessible in the NDVI satellite record when images are processed to be intercomparable over time and temporally ordered to create a time series. This study utilized NDVI time series to classify areas of similar vegetation phenology in the northern Fertile Crescent, an area from the middle Mediterranean coast to southern/south-eastern Turkey to western Iran and northern Iraq. Phenological monitoring of the northern Fertile Crescent is critical due to the area's minimal water resources, susceptibility to drought, and understanding ancient historical reliance on precipitation for subsistence dry farming. Delineation of phenological classes provides areal and temporal synopsis of vegetation productivity time series. Phenological classes were developed from NDVI time series calculated from NOAA's Advanced Very High Resolution Radiometer (AVHRR) imagery with 8 × 8 km spatial resolution over twenty-five years, and by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) with 250 × 250 m spatial resolution over twelve years. Both AVHRR and MODIS time series were subjected to data reduction techniques in spatial and temporal dimensions. Optimized ISODATA clusters were developed for both of these data reduction techniques in order to compare the effects of spatial versus temporal aggregation. Within the northern Fertile Crescent study area, the spatial reduction technique showed increased cluster cohesion over the temporal reduction method. The latter technique showed an increase in temporal smoothing over the spatial reduction technique. Each technique has advantages depending on the desired spatial or temporal granularity. Additional work is required to determine optimal scale size for the spatial data reduction technique.

Bunker, Brian

16

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

17

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

18

Wavelet analysis of the Earth center of mass time series determined by satellite techniques  

NASA Astrophysics Data System (ADS)

The Earth center of mass (geocenter) time series with the sampling interval of one week are determined from Satellite Laser Ranging (SLR), Global Navigation Satellite System (GNSS) and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) observations. The 3D geocenter time series were projected onto XY, YZ and ZX planes of the International Terrestrial Reference Frame (ITRF), thus, three complex-valued time series can be analyzed for each observation technique. The signal to noise ratio in these geocenter time series is very small and detectable oscillations are rather broadband, however, the annual oscillation can be noticed in each one of them. The wavelet transform technique with the Morlet wavelet function was applied to compute the mean and spectra-temporal polarization functions from the prograde (positive periods) and retrograde (negative periods) spectra of the examined complex-valued time series. The sign of the polarization function determines turning direction in the elliptical motion. If this function is positive or negative for oscillation with a chosen period, then this oscillation is prograde or retrograde, respectively. To estimate the significance level of polarization functions, corresponding to time series data length, the Monte Carlo experiment was performed using complex-valued white noise data. In order to detect similarity between elliptic oscillations in two different time series the spectra-temporal wavelet semblance function was computed. This function reveals that in the XY equatorial plane there is phase agreement between retrograde annual oscillation for SLR and GNSS techniques, and between prograde annual oscillation for DORIS and two other techniques. To construct a model of geocenter motion from GNSS and SLR center of mass time series the wavelet based semblance filtering method was applied. Common oscillations in the analyzed time series are dominated by the annual oscillation with amplitude less than 5 mm.

Kosek, Wies?aw; Wn?k, Agnieszka; Zbylut-Górska, Maria; Popi?ski, Waldemar

2014-10-01

19

The CACAO Method for Smoothing, Gap Filling, and Characterizing Seasonal Anomalies in Satellite Time Series  

NASA Technical Reports Server (NTRS)

Consistent, continuous, and long time series of global biophysical variables derived from satellite data are required for global change research. A novel climatology fitting approach called CACAO (Consistent Adjustment of the Climatology to Actual Observations) is proposed to reduce noise and fill gaps in time series by scaling and shifting the seasonal climatological patterns to the actual observations. The shift and scale CACAO parameters adjusted for each season allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. CACAO was assessed first over simulated daily Leaf Area Index (LAI) time series with varying fractions of missing data and noise. Then, performances were analyzed over actual satellite LAI products derived from AVHRR Long-Term Data Record for the 1981-2000 period over the BELMANIP2 globally representative sample of sites. Comparison with two widely used temporal filtering methods-the asymmetric Gaussian (AG) model and the Savitzky-Golay (SG) filter as implemented in TIMESAT-revealed that CACAO achieved better performances for smoothing AVHRR time series characterized by high level of noise and frequent missing observations. The resulting smoothed time series captures well the vegetation dynamics and shows no gaps as compared to the 50-60% of still missing data after AG or SG reconstructions. Results of simulation experiments as well as confrontation with actual AVHRR time series indicate that the proposed CACAO method is more robust to noise and missing data than AG and SG methods for phenology extraction.

Verger, Aleixandre; Baret, F.; Weiss, M.; Kandasamy, S.; Vermote, E.

2013-01-01

20

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

21

Advanced tools for astronomical time series and image analysis  

NASA Astrophysics Data System (ADS)

The algorithms described here, which I have developed for applications in X-ray and ?-ray astronomy, will hopefully be of use in other ways, perhaps aiding in the exploration of modern astronomy's data cornucopia. The goal is to describe principled approaches to some ubiquitous problems, such as detection and characterization of periodic and aperiodic signals, estimation of time delays between multiple time series, and source detection in noisy images with noisy backgrounds. The latter problem is related to detection of clusters in data spaces of various dimensions. A goal of this work is to achieve a unifying view of several related topics: signal detection and characterization, cluster identification, classification, density estimation, and multivariate regression. In addition to being useful for analysis of data from space-based and ground-based missions, these algorithms may be a basis for a future automatic science discovery facility, and in turn provide analysis tools for the Virtual Observatory. This chapter has ties to those by Larry Bretthorst, Tom Loredo, Alanna Connors, Fionn Murtagh, Jim Berger, David van Dyk, Vicent Martinez & Enn Saar.

Scargle, Jeffrey D.

22

Time series analysis of satellite derived surface temperature for Lake Garda  

NASA Astrophysics Data System (ADS)

Remotely sensed satellite imageryis the most suitable tool for researchers around the globe in complementing in-situ observations. Nonetheless, it would be crucial to check for quality, validate and standardize methodologies to estimate the target variables from sensor data. Satellite imagery with thermal infrared bands provides opportunity to remotely measure the temperature in a very high spatio-temporal scale. Monitoring surface temperature of big lakes to understand the thermal fluctuations over time is considered crucial in the current status of global climate change scenario. The main disadvantage of remotely sensed data is the gaps due to presence of clouds and aerosols. In this study we use statistically reconstructed daily land surface temperature products from MODIS (MOD11A1 and MYD11A1) at a better spatial resolution of 250 m. The ability of remotely sensed datasets to capture the thermal variations over time is validated against historical monthly ground observation data collected for Lake Garda. The correlation between time series of satellite data LST (x,y,t) and the field measurements f (x,y,t) are found to be in acceptable range with a correlation coefficient of 0.94. We compared multiple time series analysis methods applied on the temperature maps recorded in the last ten years (2002 - 2012) and monthly field measurements in two sampling points in Lake Garda. The time series methods STL - Seasonal Time series decomposition based on Loess method, DTW - Dynamic Time Waping method, and BFAST - Breaks for Additive Season and Trend, are implemented and compared in their ability to derive changes in trends and seasonalities. These methods are mostly implemented on time series of vegetation indices from satellite data, but seldom used on thermal data because of the temporal incoherence of the data. The preliminary results show that time series methods applied on satellite data are able to reconstruct the seasons on an annual scale while giving us a graphical view of intra-annual variations in the trends with residuals. The time series trend analysis shows similar pattern from both the datasets reinstating the importance of remotely sensed data in climate change related studies.

Pareeth, Sajid; Metz, Markus; Rocchini, Duccio; Salmaso, Nico; Neteler, Markus

2014-05-01

23

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

24

Fusion of MODIS time-series images and TM image based on wavelet transform  

NASA Astrophysics Data System (ADS)

The fusion method for the wide range resolution images will contribute to take the advantage of high time-resolution of MODIS data and high spatial-resolution of TM data, which will provide the time-series information matching the crop growth. The paper test the wavelet transform model from wavelet basis, decomposition level and fusion rule. By evaluating the quality of fusion images from several indexes, the paper analyzed the impact of fusion quality of MODIS and TM images from the parameter setting of wavelet transform. According to the comparison of many experiments, the study chose decomposition level 4, BIOR 6.8 of wavelet basis and high-replace-low of fusion rule. The study showed that the fusion method of wavelet transform could reserve the spectral feature of time-series information and enhance the spatial resolution from 250 meter to 30 meter. The time-series fusing images could be applied for crop monitoring.

Gu, Xiaohe; He, Xin; Guo, Wei; Dong, Yansheng

2011-12-01

25

Coastal changes in the Sendai area from the impact of the 2011 T?hoku-oki tsunami: Interpretations of time series satellite images, helicopter-borne video footage and field observations  

NASA Astrophysics Data System (ADS)

A combination of time-series satellite imagery, helicopter-borne video footage and field observation is used to identify the impact of a major tsunami on a low-lying coastal zone located in eastern Japan. A comparison is made between the coast protected by armoured 'engineered' sea walls and the coast without. Changes are mapped from before and after imagery, and sedimentary processes identified from the video footage. The results are validated by field observations. The impact along a 'natural' coast, with minimal defences, is erosion focussed on the back beach. Along coasts with hard engineered protection constructed to defend against erosion, the presence of three to six metre high concrete-faced embankments results in severe erosion on their landward faces. The erosion is due to the tsunami wave accelerating through a hydraulic jump as it passes over the embankment, resulting in the formation of a ditch into which the foundations collapse. Engineered coastal defences are thus found to be small defence against highly energetic tsunami waves that overtop them. There is little erosion (or sedimentation) of the whole beach, and where active, it mainly forms V-shaped channels. These channels are probably initiated during tsunami inflow and then further developed during tsunami backflow. Tsunami backflow on such a low lying area takes place energetically as sheet flow immediately after tsunami flooding has ceased. Subsequently, when the water level landward of the coastal dune ridges falls below their elevation, flow becomes confined to rivers and breaches in the coast formed during tsunami inflow. Enigmatic, short lived, 'strand lines' are attributed to the slow fall of sea level after such a major tsunami. Immediately after the tsunami coastal reconstruction begins, sourced from the sediment recently flushed into the sea by tsunami backflow.

Tappin, David R.; Evans, Hannah M.; Jordan, Colm J.; Richmond, Bruce; Sugawara, Daisuke; Goto, Kazuhisa

2012-12-01

26

Surveillance of Vrancea active seismic region in Romania through time series satellite data  

NASA Astrophysics Data System (ADS)

Cumulative stress energy in active seismic regions caused by tectonic forces creates various earthquake precursors. This energy transformation may result in enhanced transient thermal infrared (TIR) emission, which can be detected through satellites equipped with thermal sensors like MODIS (Terra/Aqua) and AVHRR (NOAA). 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. This paper presents observations made using time series MODIS and NOAA-AVHRR satellite data for derived multi-parameters including land surface temperature (LST), outgoing long-wave radiation (OLR), and mean air temperature (AT) for the moderate, 5.9 magnitude earthquake, which took place on the 27th of October, 2004, inthe seismic region of Vrancea, in Romania. Anomalous thermal infrared signals, reflected by a rise of several degrees celsius (°C) in LSTs, and higher OLR values were seen several days before the earthquake. AT values in the epicentral area also increased almost two days prior to the earthquake and intensified three days after the main shock. Increases in LSTs and OLR disappeared three days after the main shock. The survey and joint analysis of geospatial and in-situ geophysical information on land surface temperatures and outgoing long-wave radiation provides new insights into the field of seismic hazard assessment in Vrancea, a significant area of tectonic activity in Romania and Europe.

Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.

2014-06-01

27

Time series modeling and large scale global solar radiation forecasting from geostationary satellites data  

E-print Network

When a territory is poorly instrumented, geostationary satellites data can be useful to predict global solar radiation. In this paper, we use geostationary satellites data to generate 2-D time series of solar radiation for the next hour. The results presented in this paper relate to a particular territory, the Corsica Island, but as data used are available for the entire surface of the globe, our method can be easily exploited to another place. Indeed 2-D hourly time series are extracted from the HelioClim-3 surface solar irradiation database treated by the Heliosat-2 model. Each point of the map have been used as training data and inputs of artificial neural networks (ANN) and as inputs for two persistence models (scaled or not). Comparisons between these models and clear sky estimations were proceeded to evaluate the performances. We found a normalized root mean square error (nRMSE) close to 16.5% for the two best predictors (scaled persistence and ANN) equivalent to 35-45% related to ground measurements. F...

Voyant, Cyril; Muselli, Marc; Paoli, Christophe; Nivet, Marie Laure

2014-01-01

28

Mesoscale variability in time series data: Satellite-based estimates for the U.S. JGOFS Bermuda Atlantic Time-Series Study (BATS) site  

NASA Astrophysics Data System (ADS)

Objectively analyzed fields of satellite sea surface temperature (SST, advanced very high resolution radiometer (AVHRR) Pathfinder) and sea surface height anomaly (SSHA, combined TOPEX/Poseidon-ERS-1/2) are used to characterize, statistically, the mesoscale variability about the U.S. Joint Global Ocean Flux Study (JGOFS) Bermuda Atlantic Time-Series Study (BATS) site. These results are applied to the in situ BATS time series data and a local one-dimensional (1-D) physical upper ocean model to better understand the contribution of mesoscale eddies to the time series record and the model-data mismatch. Using a low-pass spatial filter, we decompose the anomalies from the seasonal cycle into two components: the large-scale, regional climate variability and a mesoscale signal. The mesoscale SST and SSHA fields are positively cross-correlated at a statistically significant level, consistent with near-surface isotherm displacements for cyclonic and anticyclonic eddies. The results from time-lagged cross-correlation analysis show that detectable eddy signatures exist in the in situ SST data and that eddies are a noticeable (~10%) but not dominant error source for the 1-D model solution. Several factors may be at work: the 1-D model captures a more regional signal, whereas the BATS in situ data include small-scale spatial heterogeneity; the satellite data and 1-D model are indirectly coupled via the National Centers for Environmental Prediction (NCEP) reanalysis forcing data; and the satellite-based mesoscale variability estimates are also missing specific events because of the sparse space-time sampling of a polar orbiting, visible/infrared wavelength sensor. The mesoscale eddy cross-correlation signature did not show up clearly in a similar analysis conducted on the original anomaly fields, highlighting the fact that climate scale variability needs to be carefully removed to isolate the eddy signature.

Glover, David M.; Doney, Scott C.; Mariano, Arthur J.; Evans, Robert H.; McCue, Scott J.

2002-08-01

29

Fifteen-year global time series of satellite-derived fine particulate matter.  

PubMed

Ambient fine particulate matter (PM2.5) is a leading environmental risk factor for premature mortality. We use aerosol optical depth (AOD) retrieved from two satellite instruments, MISR and SeaWiFS, to produce a unified 15-year global time series (1998-2012) of ground-level PM2.5 concentration at a resolution of 1° x 1°. The GEOS-Chem chemical transport model (CTM) is used to relate each individual AOD retrieval to ground-level PM2.5. Four broad areas showing significant, spatially coherent, annual trends are examined in detail: the Eastern U.S. (-0.39 ± 0.10 ?g m(-3) yr(-1)), the Arabian Peninsula (0.81 ± 0.21 ?g m(-3) yr(-1)), South Asia (0.93 ± 0.22 ?g m(-3) yr(-1)) and East Asia (0.79 ± 0.27 ?g m(-3) yr(-1)). Over the period of dense in situ observation (1999-2012), the linear tendency for the Eastern U.S. (-0.37 ± 0.13 ?g m(-3) yr(-1)) agrees well with that from in situ measurements (-0.38 ± 0.06 ?g m(-3) yr(-1)). A GEOS-Chem simulation reveals that secondary inorganic aerosols largely explain the observed PM2.5 trend over the Eastern U.S., South Asia, and East Asia, while mineral dust largely explains the observed trend over the Arabian Peninsula. PMID:25184953

Boys, B L; Martin, R V; van Donkelaar, A; MacDonell, R J; Hsu, N C; Cooper, M J; Yantosca, R M; Lu, Z; Streets, D G; Zhang, Q; Wang, S W

2014-10-01

30

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

31

Satellite Images  

NSDL National Science Digital Library

In this online, interactive module, students learn about the three types of satellite images (visible, infrared, and water vapor); how to identify basic cloud types and storm systems in satellite images; and demonstrate the basic knowledge necessary to interpret satellite observations. The module is part of an online course for grades 7-12 in satellite meteorology, which includes 10 interactive modules. The site also includes lesson plans developed by teachers and links to related resources. Each module is designed to serve as a stand-alone lesson, however, a sequential approach is recommended. Designed to challenge students through the end of 12th grade, middle school teachers and students may choose to skim or skip a few sections.

32

Reconstructing long time series of burned areas in arid grasslands of southern Russia by satellite remote sensing  

E-print Network

Reconstructing long time series of burned areas in arid grasslands of southern Russia by satellite: AVHRR MODIS RESURS Landsat Burned area mapping Southern Russia Arid grasslands Grazing Fire, assessing fire regime changes is challenging, especially in grasslands because of high intra- and inter

Radeloff, Volker C.

33

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

34

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

35

Motion Artifact Reduction in Ultrasound Based Thermal Strain Imaging of Atherosclerotic Plaques Using Time Series Analysis  

PubMed Central

Large lipid pools in vulnerable plaques, in principle, can be detected using US based thermal strain imaging (US-TSI). One practical challenge for in vivo cardiovascular application of US-TSI is that the thermal strain is masked by the mechanical strain caused by cardiac pulsation. ECG gating is a widely adopted method for cardiac motion compensation, but it is often susceptible to electrical and physiological noise. In this paper, we present an alternative time series analysis approach to separate thermal strain from the mechanical strain without using ECG. The performance and feasibility of the time-series analysis technique was tested via numerical simulation as well as in vitro water tank experiments using a vessel mimicking phantom and an excised human atherosclerotic artery where the cardiac pulsation is simulated by a pulsatile pump. PMID:24808628

Dutta, Debaditya; Mahmoud, Ahmed M.; Leers, Steven A.; Kim, Kang

2013-01-01

36

Use of spectral channels and vegetation indices from satellite VEGETATION time series for the Post-Fire vegetation recovery estimation  

NASA Astrophysics Data System (ADS)

Satellite data can help monitoring the dynamics of vegetation in burned and unburned areas. Several methods can be used to perform such kind of analysis. This paper is focused on the use of different satellite-based parameters for fire recovery monitoring. In particular, time series of single spectral channels and vegetation indices from SPOT-VEGETATION have investigated. The test areas is the Mediterranean ecosystems of Southern Italy. For this study we considered: 1) the most widely used index to follow the process of recovery after fire: normalized difference vegetation index (NDVI) obtained from the visible (Red) and near infrared (NIR) by using the following formula NDVI = (NIR_Red)/(NIR + Red), 2) moisture index MSI obtained from the near infrared and Mir for characterization of leaf and canopy water content. 3) NDWI obtained from the near infrared and Mir as in the case of MSI, but with the normalization (as the NDVI) to reduce the atmospheric effects. All analysis for this work was performed on ten-daily normalized difference vegetation index (NDVI) image composites (S10) from the SPOT- VEGETATION (VGT) sensor. The final data set consisted of 279 ten-daily, 1 km resolution NDVI S1O composites for the period 1 April 1998 to 31 December 2005 with additional surface reflectance values in the blue (B; 0.43-0.47,um), red (R; 0.61-0.68,um), near-infrared (NIR; 0.78-0.89,um) and shortwave-infrared (SWIR; 1.58-1.75,um) spectral bands, and information on the viewing geometry and pixel status. Preprocessing of the data was performed by the Vlaamse Instelling voor Technologisch Onderzoek (VITO) in the framework of the Global Vegetation Monitoring (GLOVEG) preprocessing chain. It consisted of the Simplified Method for Atmospheric Correction (SMAC) and compositing at ten-day intervals based on the Maximum Value Compositing (MVC) criterion. All the satellite time series were analysed using the Detrended Fluctuation Analysis (DFA) to estimate post fire vegetation recovery. The DFA is a well-known methodology, which allows the detectin of long-range power-law correlations in signals possibly characterized by non-stationarity, which features most of the observational and experimental signals. We analyzed time variation of both single channels and spectral indices from 1998 to 2005 of fire- affected and fire unaffected areas. In order to eliminate the seasonal and/or phenological fluctuations, for each decadal composition, we focused on the normalized departure: 1) NDVI; 2) NDWId, 3) MSId. Results from our analysis point out that the persistence of vegetation dynamics is significantly increased by the occurrence of fires. In particular, a scaling behavior of two classes of vegetation (burned and unburned) has been best revealed by NDVI. The estimated scaling exponents of both classes suggest a persistent character of the vegetation dynamics. But, the burned sites show much larger exponents than those calculated for the unburned sites. Small variations have been observed between the estimated scaling exponents of both fire-affected and fire-unaffected areas.

Coluzzi, Rosa; Lasaponara, Rosa; Montesano, Tiziana; Lanorte, Antonio; de Santis, Fortunato

2010-05-01

37

Surface differential rotation of IL Hya from time-series Doppler images  

NASA Astrophysics Data System (ADS)

We present a time-series Doppler imaging study of the K-subgiant component in the RS CVn-type binary system IL Hya (P orb=12.905 d). From re-processing the unique long-term spectroscopic dataset of 70 days taken in 1996/97, we perform a thorough cross-correlation analysis to derive surface differential rotation. As a result we get solar-type differential rotation with a shear value ? of 0.05, in agreement with preliminary suggestions from previous attempts. A possible surface pattern of meridional circulation is also detected.

K?vári, Zsolt; Kriskovics, Levente; Oláh, Katalin; Vida, Krisztián; Bartus, János; Strassmeier, Klaus G.; Weber, Michael

2014-08-01

38

DORIS satellite antenna maps derived from long-term residuals time series  

NASA Technical Reports Server (NTRS)

Recent studies have shown that phase pattern models for the Jason-1 GPS antenna significantly benefit GPS-based precise orbit determination (POD) for the satellite. We have used a similar technique to derive DORIS receiver antenna maps, using all available DORIS tracking data over long time periods (from 1993.0 to 2004.0). We demonstrate that the derived correction models are satellite specific. For a given satellite, year-to-year estimations show clear systematic patterns. Some of these systematic patterns are attributable to the derivative of the multi-path effects in the direction of the satellite velocity. For early SPOT data, the patterns can be explained by an offset in the TAI time tagging (typically 8 (mu)s). In a second step, we have applied the SPOT2 antenna correction models in precise orbit determination and in the positioning of ground beacons. Preliminary results on DORIS/SPOT2 show that application of the DORIS antenna maps lead to a slight improvement of the derived POD and geodetic results (typically less than 5%).

Willis, Pascal R.; Desai, S. D.; Bertiger, W. I.; Haines, B. J.; Auriol, A.

2004-01-01

39

DORIS satellite antenna maps derived from long-term residuals time series  

NASA Astrophysics Data System (ADS)

Recent studies have shown that phase pattern models for the Jason-1 GPS antenna significantly benefit GPS-based precise orbit determination (POD) for the satellite. We have used a similar technique to derive DORIS receiver antenna maps, using all available DORIS tracking data over long time periods (from 1993.0 to 2004.0). We demonstrate that the derived correction models are satellite specific. For a given satellite, year-to-year estimations show clear systematic patterns. Some of these systematic patterns are attributable to the derivative of the multi-path effects in the direction of the satellite velocity. For early SPOT data, the patterns can be explained by an offset in the TAI time tagging (typically 8 ?s). In a second step, we have applied the SPOT2 antenna correction models in precise orbit determination and in the positioning of ground beacons. Preliminary results on DORIS/SPOT2 show that application of the DORIS antenna maps lead to a slight improvement of the derived POD and geodetic results (typically less than 5%).

Willis, P.; Desai, S. D.; Bertiger, W. I.; Haines, B. J.; Auriol, A.

40

Trend analysis of time-series phenology derived from satellite data  

Microsoft Academic Search

Remote sensing information has been used in studies of the seasonal dynamics (phenology) of the land surface for the past 15 years. While our understanding of remote sensing phenology is still in development, it is regarded as a key to understanding land surface processes over large areas. Repeat observations from satellite-borne multispectral sensors provide a mechanism to move from plant-specific

Bradley C. Reed; Jesslyn F. Brown

2005-01-01

41

Time series comparisons of satellite and rocketsonde temperatures in 1978-1979  

NASA Technical Reports Server (NTRS)

The Limb Infrared Monitor of the Stratosphere (LIMS) experiment on Nimbus 7 yielded temperature-versus-pressure (T(p)) profiles for each radiance scan. The present report describes time series comparisons between LIMS and rocketsonde T(p) values at rocketsonde station locations. Sample size has increased up to 665 by this new approach, leading to better statistics for a T(p) validation. The results indicate no clearly significant bias for LIMS versus Datasonde from 10 kPa at low and mid latitudes. There is a positive LIMS bias of 2 to 3 K in the upper stratosphere at high latitudes for the Northern Hemisphere in both winter and spring. LIMS is progressively colder than Datasonde from 0.4 kPa (about -3 K) to 0.1 kPa (about -9 K) at all latitudes. A similar comparison between LIMS and the more accurate falling sphere measurements reveals an equivalent mid-latitude LIMS bias at 0.4 kPa but a much smaller bias at 0.1 kPa (-4.6 K). Because the biases do not vary noticeably with season, it is concluded that they are not a function of atmospheric state. This result confirms the robustness of the LIMS temperature retrieval technique.

Remsberg, Ellis E.; Bhatt, Praful P.; Schmidlin, Francis J.

1994-01-01

42

Global distributions, time series and error characterization of atmospheric ammonia (NH3) from IASI satellite observations  

NASA Astrophysics Data System (ADS)

Ammonia (NH3) emissions in the atmosphere have increased substantially over the past decades, largely because of intensive livestock production and use of fertilizers. As a short-lived species, NH3 is highly variable in the atmosphere and its concentration is generally small, except near local sources. While ground-based measurements are possible, they are challenging and sparse. Advanced infrared sounders in orbit have recently demonstrated their capability to measure NH3, offering a new tool to refine global and regional budgets. In this paper we describe an improved retrieval scheme of NH3 total columns from the measurements of the Infrared Atmospheric Sounding Interferometer (IASI). It exploits the hyperspectral character of this instrument by using an extended spectral range (800-1200 cm-1) where NH3 is optically active. This scheme consists of the calculation of a dimensionless spectral index from the IASI level1C radiances, which is subsequently converted to a total NH3 column using look-up tables built from forward radiative transfer model simulations. We show how to retrieve the NH3 total columns from IASI quasi-globally and twice daily above both land and sea without large computational resources and with an improved detection limit. The retrieval also includes error characterization of the retrieved columns. Five years of IASI measurements (1 November 2007 to 31 October 2012) have been processed to acquire the first global and multiple-year data set of NH3 total columns, which are evaluated and compared to similar products from other retrieval methods. Spatial distributions from the five years data set are provided and analyzed at global and regional scales. In particular, we show the ability of this method to identify smaller emission sources than those previously reported, as well as transport patterns over the ocean. The five-year time series is further examined in terms of seasonality and interannual variability (in particular as a function of fire activity) separately for the Northern and Southern Hemispheres.

Van Damme, M.; Clarisse, L.; Heald, C. L.; Hurtmans, D.; Ngadi, Y.; Clerbaux, C.; Dolman, A. J.; Erisman, J. W.; Coheur, P. F.

2014-03-01

43

Prediction Method for Time Series of Imagery Data in Eigen Space Validity of the Proposed Prediction Metyhod for Remote Sensing Satellite Imagery Data  

Microsoft Academic Search

Prediction method for time series of imagery data on eigen space is proposed. Although the conventional prediction method is defined on the real world space and time domains, the proposed method is defined on eigen space. Prediction accuracy of the proposed method is supposed to be superior to the conventional methods. Through experiments with time series of satellite imagery data,

Kohei Arai

2013-01-01

44

Detecting damage to coastal forests caused by the Tohoku earthquake in Japan using time-series remote sensing images  

NASA Astrophysics Data System (ADS)

The Tohoku earthquake of 2011 caused extensive damage to the coastal pine forest that protects inland areas from sea breezes. The tsunami uprooted, broke, and tilted the pine trees. In addition, subsequently, the leaves of coastal pine forest turned red and fell down after summer in 2011 in large areas. To detect damage to the coastal forest caused by the Tohoku earthquake, we analyzed time-series airborne orthophotos and high-resolution satellite image. After the earthquake, many coastal forests were washed away and there is no sign of coastal forest stands in the orthophotos. We compared orthophotos taken before and just after the earthquake by the Japan Geographical Survey Institute. We mapped the damaged forest in Aomori, Iwate, and Miyagi prefectures and classified the damage into three classes: extensive, moderate, and slight damage. We also obtained and high-resolution satellite image (DigitalGlobe, WorldView-2) observed after the summer in 2011. We surveyed the forest damage using field plots. We measured the damage of 50 - 60 trees in a circular plot. The tree damage was classified on a 0 to 10 point scale: a sound tree had 0 damage, while a tree with a completely damaged crown was scored 10. The most crown leaves of a tree scored 7-9 turned red and fell off. The average plots damage were calculated and a linear regression analysis was performed to compare the data for 21 field plots and satellite data. The coefficient of determination was large and we mapped the forest damage using satellite image.

Kodani, Eiji; Nakamura, Katsunori; Sakamoto, Tomoki; Kimura, Koki

2012-10-01

45

Nonlinear denoising of functional magnetic resonance imaging time series with wavelets.  

PubMed

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 signal changes of the BOLD response. Thus, noise reduction is important to allow an accurate estimation of single activation-related BOLD signals across brain regions. Techniques employed so far include filtering in the time or frequency domain which, however, does not take into account possible nonlinearities of the BOLD response. We here evaluate a previously proposed method for nonlinear denoising of short and transient signals, which combines the wavelet transform with techniques from nonlinear time series analysis. We adopt the method to the problem at hand and show that successful noise reduction and, more importantly, preservation of the shape of individual BOLD signals can be achieved even in the presence of in-band noise. PMID:19518263

Stausberg, Sven; Lehnertz, Klaus

2009-04-01

46

Nonlinear denoising of functional magnetic resonance imaging time series with wavelets  

NASA Astrophysics Data System (ADS)

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 signal changes of the BOLD response. Thus, noise reduction is important to allow an accurate estimation of single activation-related BOLD signals across brain regions. Techniques employed so far include filtering in the time or frequency domain which, however, does not take into account possible nonlinearities of the BOLD response. We here evaluate a previously proposed method for nonlinear denoising of short and transient signals, which combines the wavelet transform with techniques from nonlinear time series analysis. We adopt the method to the problem at hand and show that successful noise reduction and, more importantly, preservation of the shape of individual BOLD signals can be achieved even in the presence of in-band noise.

Stausberg, Sven; Lehnertz, Klaus

2009-04-01

47

Time series analysis of satellite multi-sensors imagery to study the recursive abnormal grow of floating macrophyte in the lake victoria (central Africa)  

NASA Astrophysics Data System (ADS)

Remote sensing allows multi-temporal mapping and monitoring of large water bodies. The importance of remote sensing for wetland and inland water inventory and monitoring at all scales was emphasized several times by the Ramsar Convention on Wetlands and from EU projects like SALMON and ROSALMA, e.g. by (Finlayson et al., 1999) and (Lowry and Finlayson, 2004). This paper aims at assessing the capability of time series of satellite imagery to provide information suitable for enhancing the understanding of the temporal cycles shown by the macrophytes growing in order to support the monitor and management of the lake Victoria water resources. The lake Victoria coastal areas are facing a number of challenges related to water resource management which include growing population, water scarcity, climate variability and water resource degradation, invasive species, water pollution. The proliferation of invasive plants and aquatic weeds, is of growing concern. In particular, let us recall some of the problems caused by the aquatic weeds growing: Ø interference with human activities such as fishing, and boating; Ø inhibition or interference with a balanced fish population; Ø fish killing due to removal of too much oxygen from the water; Ø production of quiet water areas that are ideal for mosquito breeding. In this context, an integrated use of medium/high resolution images from sensors like MODIS, ASTER, LANDSAT/TM and whenever available CHRIS offers the possibility of creating a congruent time series allowing the analysis of the floating vegetation dynamic on an extended temporal basis. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution, further its spatial resolution can results not always adequate to map the extension of floating plants. Therefore, the integrated use of sensors with different spatial resolution, were used to map across seasons the evolution of the phenomena. The integrated use of satellite resources allowed the estimate of the temporal variability of physical parameters that were used to i) sample the spatio-temporal distribution of the whole floating vegetation (i.e. native vegetation and weed) and ii) assess the seasonal recurrence of the abnormal weeds grow, as well as, their possible relation with the hydrological regimes of the rivers. The paper describes how the 2000 - 2009 MODIS images time series, were analysed (navigated and processed) to derive i) the map the floating vegetation on the test area and ii) identify the areas more interested by the growing iii) to discriminate, whenever possible, according to the spectral and spatial resolution of the sensor applied (i.e. LANDSAT, ASTER, CHRIS), the different vegetation species in order to discriminate the weeds from the floating vegetation. The spectral identification of the different species was performed by exploiting the results of a field campaign performed in the past along the Kenyan coastal areas devoted to define a data base of spectral signatures of the main species. Spectral information was treated to define indexes and spectral analysis procedure customized to multispectral high resolution satellite data. Moreover, the results of the images time series has been analysed to identify a possible definition of the temporal occurrence of the floating vegetation growing considering both the natural phenomenological cycles and the conditions related to the abnormal growing. These results, whenever related to ancillary hydrological information (e.g. the amount of rain), they have shown that the synergy of MODIS images time series with lower temporal frequency time series imagery is a powerful tool to monitor the lake Victoria ecosystem and to follow the floating vegetation extension and even to foresee the possibility to set up a model for the abnormal vegetation growing.

Fusilli, Lorenzo; Cavalli, Rosa Maria; Laneve, Giovanni; Pignatti, Stefano; Santilli, Giancarlo; Santini, Federico

2010-05-01

48

Imaging transient slip events in southwest Japan using reanalyzed Japanese GEONET GPS time series  

NASA Astrophysics Data System (ADS)

The Japanese continuous GPS network (GEONET) with ~1450 stations provide a unique opportunity to study ongoing subduction zone dynamics, and crustal deformation at various spatiotemporal scales. Recently we completed a reanalysis of GPS position time series for the entire GEONET from 1996 to 2012 using JPL GIPSY/OASIS-II based GPS Network Processor [Owen et al., 2006] and raw data provided by Geospatial Information Authority of Japan (GSI) and Caltech. We use the JPL precise GPS orbits reestimated from the present through 1996 [Desai et al., 2011], troposphere global mapping function, and single receiver phase ambiguity resolution strategy [Bertiger et al., 2010] in the analysis. The resultant GPS time series solution shows improved repeatability and consistency over the ~16 yrs span, in comparison with 1996-2006 GPS position estimates used in our previous analysis [Liu et al., 2010a,b]. We apply a time-series analysis framework to estimate bias, offsets caused by instrument changes, earthquakes and other unknown sources, linear trends, seasonal variations, post-seismic deformation and other transient signals. The principal component analysis method is used to estimate the common mode error across the network [Dong et al. 2006]. We construct an interplate fault geometry from a composite plate boundary model [Wang et al. 2004] and apply a Kalman filter based network inversion method to image the spatiotemporal slip variation of slip transient events on the plate interface. The highly precise GPS time series enables the detectability of much smaller transient signals and start to reveal previously unobserved features of slow slip events. For example, the application to 2009-2011 Bungo Channel slow slip event shows it has a complex slip history with the major event initiating in late 2009 beneath the northeast corner of the region and migrating southwestward and updip. At ~2010.75 there is activation of a smaller slip subevent to the east of main slip region, persisting through the end of modeling period (2011.1786). We found clear temporal correspondence of adjacent low frequency earthquakes (LFEs)/tremor following transient slip variation, similar to what we found for other slip events in the region. This indicates that transient slip acts as a driving force to modulate the occurrence of LFEs/tremor. Despite many similarities between 2009-2011 and 2002-2004 slip events, there is considerable difference between the two in terms of slip details, suggesting these recurrent episodic events are not exactly identical. We find the 2009-2011 Bungo Channel event as well as previous ones (e.g, 2002-2004, 1996-1998) all initiated at the same location on the plate interface, suggesting that they are controlled by inherent frictional properties with secondary factors affecting the evolution details. Integrating plate coupling and SSEs confirmed the spatial pattern seen before in other events that the transient slip zones are located in a region between the locked zones and the epicenters of the LFEs/tremor. Recurrent SSEs release nearly all accumulated elastic strain over depths of ~20-30km where slip occurs and at least part of slip deficit at a shallower depth. We are in the process of imaging other slip transients along this part of subduction margin in a systematic effort to improve estimates of slip deficits and future large earthquake hazards.

Liu, Z.; Moore, A. W.; Owen, S. E.

2012-12-01

49

Cerebral blood flow imaging using time-series analysis of indocyanine green molecular dynamics in mice  

NASA Astrophysics Data System (ADS)

Measurement of cerebral perfusion is important for study of various brain disorders such as stroke, epilepsy, and vascular dementia; however, efficient and convenient methods which can provide quantitative information about cerebral blood flow are not developed. Here we propose an optical imaging method using time-series analysis of dynamics of indocyanine green (ICG) fluorescence to generate cerebral blood flow maps. In scalp-removed mice, ICG was injected intravenously, and 740nm LED light was illuminated for fluorescence emission signals around 820nm acquired by cooled-CCD. Time-lapse 2-dimensional images were analyzed by custom-built software, and the maximal time point of fluorescent influx in each pixel was processed as a blood flow-related parameter. The generated map exactly reflected the shape of the brain without any interference of the skull, the dura mater, and other soft tissues. This method may be further applicable for study of other disease models in which the cerebral hemodynamics is changed either acutely or chronically.

Ku, Taeyun; Lee, Jungsul; Choi, Chulhee

2010-02-01

50

Using Landsat image time series to study a small water body in Northern Spain.  

PubMed

Ramsar Convention and EU Water Framework Directive are two international agreements focused on the conservation and achievement of good ecological and chemical status of wetlands. Wetlands are important ecosystems holding many plant and animal communities. Their environmental status can be characterised by the quality of their water bodies. Water quality can be assessed from biophysical parameters (such as Chlorophyll-a concentration ([Chla]), water surface temperature and transparency) in the deeper or lacustrine zone, or from bioindicators (as submerged aquatic vegetation) in the shallow or palustrine zone. This paper proves the use of Landsat time series to measure the evolution of water quality parameters and the environmental dynamics of a small water body (6.57 ha) in a Ramsar wetland (Arreo Lake in the North of Spain). Our results show that Landsat TM images can be used to describe periodic behaviours such as the water surface temperature or the phenologic state of the submerged vegetation (through normalized difference vegetation index, NDVI) and thus detect anomalous events. We also show how [Chla] and transparency can be measured in the lacustrine zone using Landsat TM images and an algorithm adjusted for mesotrophic Spanish lakes, and the resulting values vary in time in accordance with field measurements (although these were not synchronous with the images). The availability of this algorithm also highlights anomalies in the field data series that are found to be related with the concentration of suspended matter. All this potential of Landsat imagery to monitor small water bodies in wetlands can be used for hindcasting of past evolution of these wetlands (dating back to 1970s) and will be also useful in the future thanks to the Landsat continuity mission and the Operational Land Imager. PMID:24452860

Chao Rodríguez, Y; el Anjoumi, A; Domínguez Gómez, J A; Rodríguez Pérez, D; Rico, E

2014-06-01

51

IMAGE Satellite Scaling  

NSDL National Science Digital Library

This is an activity about satellite size. Learners will calculate the volume of the IMAGE (Imager for Magnetopause-to-Aurora Global Exploration) satellite, the first satellite mission to image the Earth's magnetosphere. They will then determine the effect of doubling and tripling the satellite dimensions on the satellite's mass and cost. This is the first activity in the Solar Storms and You: Exploring Satellite Design educator guide.

52

Application of Time Series Landsat Images to Examining Land-use/Land-cover Dynamic Change  

PubMed Central

A hierarchical-based classification method was designed to develop time series land-use/land-cover datasets from Landsat images between 1977 and 2008 in Lucas do Rio Verde, Mato Grosso, Brazil. A post-classification comparison approach was used to examine land-use/land-cover change trajectories, which emphasis is on the conversions from vegetation or agropasture to impervious surface area, from vegetation to agropasture, and from agropasture to regenerating vegetation. Results of this research indicated that increase in impervious surface area mainly resulted from the loss of cerrado in the initial decade of the study period and from loss of agricultural lands in the last two decades. Increase in agropasture was mainly at the expense of losing cerrado in the first two decades and relatively evenly from the loss of primary forest and cerrado in the last decade. When impervious surface area was less than approximately 40 km2 before 1999, impervious surface area was negatively related to cerrado and forest, and positively related to agropasture areas, but after impervious surface area reached 40 km2 in 1999, no obvious relationship exists between them.

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying

2013-01-01

53

Constructing new satellite-only time series of global mean, sea surface temperature data for climate from ATSR data  

NASA Astrophysics Data System (ADS)

The Along Track Scanning Radiometers (ATSRs) have provided a near-continuous record of sea surface temperature (SST) data for climate from the launch of ATSR-1 in 1991 to the loss of the Advanced ATSR (AATSR) in April 2012. The intention was always to provide an SST record, independent of in situ data, to corroborate and improve climate data records in recent times. We show that the ATSR record provides a very suitable data set with which to study the recent climate record, particularly during the ATSR-2 and AATSR periods (1995 to 2012) in three major respects. First, ATSR climate time series achieve anomaly accuracies of better than 0.05 K (and high stability). Second, the overlap between instruments allows for excellent determination and removal of biases; between ATSR-2 and AATSR, these are less than 0.05 K for the highest accuracy SST data. Finally, uncertainties on global monthly mean data are less than 0.02 K and hence comparable to those achieved by in situ analyses such as HadSST3. A particular hallmark of the ATSR instruments was their exceptional design for accuracy incorporating high accuracy radiometric calibration, dual-view of the Earth's surface and the use of three thermal emission channels; additional channels are included for cloud clearing in this context. The use of dual-view and multiple thermnal wavelengths allows a number of combinations for retrievals of SST, the most accurate being the dual-view, three-channel retrieval (D3) at nighttime. This restriction is due to the use of the 3.7 micron channel which is sensitive to solar radiation during the day. Extensive work has resulted in a major advances recently resulting in both an operational V2.0 SST product and a further improved ATSR Re-analysis for Climate (ARC) product, a particular feature of the latter being the development of a depth SST product in addition to the skin SST directly determined from satellite data. We will discuss the characteristics of these data sets in terms of accuracy, stability and inter-instrument calibration. We will further describe the methods we use to construct global monthly time series of SST anomalies from ATSR data, noting particularly the significance of sampling maps in quantifying the "global" coverage. For a climate data record, estimation of uncertainty is as important as the parameter values themselves. We will discuss measurement errors, time sampling errors and effects of error correlation in determining the final uncertainty budgets. For use of the D3 ATSR product as the basis for the climate time series, time sampling is the dominant error particularly due to restrictions on valid data points in cloudier regions such as the Pacific at northern mid-latitudes. It will be shown that the overall error budget for the satellite-only data is highly suitable for an independent climate record. The ATSR studies described in this paper mark the culmination of two decades of effort to deliver high accuracy SST data from satellite sensors, giving high confidence also in our understanding of the current in situ record. We conclude that climate-quality must be achieved by the Sea and Land Surface Radiometer (SLSTR) due to be launched on Sentinel-3 in 2014 and we note the importance of gap-bridging and gap-filling between AATSR and SLSTR.

Veal, Karen; Remedios, John; Ghent, Darren

2013-04-01

54

Time Series of Imaging Spectroscopy of Dust Radiative Forcing in Snow  

NASA Astrophysics Data System (ADS)

The two most critical properties for understanding snowmelt totals and timing are the distribution of snow water equivalent (SWE) and the distribution of snow albedo, respectively. Despite their importance in controlling volume and timing of runoff, the snowpack is still poorly quantified in the US and not at all in most of the globe, leaving runoff models poorly constrained. While in the western US, we have relatively sparse measurements of SWE, mostly at lower and middle elevations and only a few per basin, albedo is even more drastically under sampled. With in situ measurements, we have begun to understand that changes in albedo from light absorbing impurities can have first order impacts on duration of snow cover and timing and magnitude of downstream runoff. To fully understand this control on runoff response however, we need time series of spatially explicit, quantitative retrievals of albedo and radiative forcing by dust and black carbon. Here we present an analysis of albedo and radiative forcing by mainly dust in snow in the Upper Colorado River Basin from data acquired by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) in the snowmelt season of 2011. AVIRIS measures reflected radiance continuously across the wavelength range 350 to 2500 nm at nominal 10 nm full-width half-maximum spectral response. The imaging spectrometer is unique in providing a direct measurement of the spectrally resolved radiative impact of dust and black carbon in snow. These acquisitions were anchored by ground-based directional reflectance measurements at time of acquisition (ideally isomorphic with the AVIRIS derived surface directional reflectances), in situ measurements of spectral irradiance at time of acquisition (to constrain the atmospheric compensation), and snow samples of dust loading.

Painter, T. H.; Skiles, M.; Bryant, A. C.; Seidel, F. C.

2011-12-01

55

Mapping agroecological zones and time lag in vegetation growth by means of Fourier analysis of time series of NDVI images  

NASA Technical Reports Server (NTRS)

Examples are presented of applications of a fast Fourier transform algorithm to analyze time series of images of Normalized Difference Vegetation Index values. The results obtained for a case study on Zambia indicated that differences in vegetation development among map units of an existing agroclimatic map were not significant, while reliable differences were observed among the map units obtained using the Fourier analysis.

Menenti, M.; Azzali, S.; Verhoef, W.; Van Swol, R.

1993-01-01

56

Destriping Satellite Images.  

National Technical Information Service (NTIS)

Before satellite images obtained with multiple image sensors can be used in image analysis, corrections must be introduced for the differences in transfer functions of these sensors. Methods are here presented for obtaining the required information direct...

B. K. P. Horn, R. J. Woodham

1978-01-01

57

Destriping Satellite Images  

E-print Network

Before satellite images obtained with multiple image sensors can be used in image analysis, corrections must be introduced for the differences in transfer functions on these sensors. Methods are here presented for ...

Horn, B.K.P.

1978-03-01

58

ASTER's Satellite Image Gallery  

NSDL National Science Digital Library

This site provides access to satellite images acquired by NASA's Advanced Spaceborne Thermal Emission and Reflection Radiometer satellite. The images are sorted into eight categories: Archeology, Cities, Geology, Hydrology, Land Use, Natural Hazards, and Volcanoes. Users can also view the most popular images and the most recent additions to the gallery.

Laboratory, Nasa J.

59

The BEYOND center of excellence for the effective exploitation of satellite time series towards natural disasters monitoring and assessment  

NASA Astrophysics Data System (ADS)

BEYOND project (2013-2016, 2.3Meuro) funded under the FP7-REGPOT scheme is an initiative which aims to build a Centre of Excellence for Earth Observation (EO) based monitoring of natural disasters in south-eastern Europe (http://beyond-eocenter.eu/), established at the National Observatory of Athens (NOA). The project focuses on capacity building on top of the existing infrastructure, aiming at unlocking the institute's potential through the systematic interaction with high-profile partners across Europe, and at consolidating state-of-the-art equipment and technological know-how that will allow sustainable cutting-edge interdisciplinary research to take place with an impact on the regional and European socioeconomic welfare. The vision is to set up innovative integrated observational solutions to allow a multitude of space borne and ground-based monitoring networks to operate in a complementary and cooperative manner, create archives and databases of long series of observations and higher level products, and make these available for exploitation with the involvement of stakeholders. In BEYOND critical infrastructural components are being procured for fostering access, use, retrieval and analysis of long EO data series and products. In this framework NOA has initiated activities for the development, installation and operation of important acquisition facilities and hardware modules, including space based observational infrastructures as the X-/L-band acquisition station for receiving EOS Aqua/Terra, NPP, JPSS, NOAA, Metop, Feng Yun data in real time, the setting up of an ESA's Mirror Site of Sentinel missions to be operable from 2014 onwards, an advanced Raman Lidar portable station, a spectrometer facility, several ground magnetometer stations. All these are expected to work in synergy with the existing capacity resources and observational networks including the MSG/SEVIRI acquisition station, nationwide seismographic, GPS, meteo and atmospheric networks. The analysis of the satellite time series from this diverse EO based monitoring network facilities established at NOA covers a broad spectrum of research activities. Indicatively using Landsat TM/ETM+ imagery we have developed algorithms for the automatic diachronic mapping of burnt areas over Greece since 1984 and we have been using MSG/SEVIRI data to detect forest wildfires in Greece since 2007, analyze their temporal and geographical signatures and store these events for further analysis in relation with auxiliary geo-information layers for risk assessment applications. In the field of geophysics we have been employing sophisticated radar interferometry techniques using SAR sensor diversity with multi-frequency, multi-resolution and multi-temporal datasets (e.g. ERS1/ERS2, ENVISAT, TerraSAR-X, COSMO-SkyMED) to map diachronic surface deformation associated with volcanic activity, tectonic stress accumulation and urban subsidence. In the field of atmospheric research, we have developed a 3-dimentional global climatology of aerosol and cloud distributions using the CALIPSO dataset. The database, called LIVAS, will continue utilizing CALIPSO observations but also datasets from the upcoming ADM-Aeolus and EarthCARE ESA missions in order to provide a unique historical dataset of global aerosol and cloud vertical distributions, as well as respective trends in cloud cover, aerosol/cloud amount and variability of the natural and anthropogenic aerosol component. Additionally, our team is involved in Swarm magnetic field constellation, a new Earth Explorer mission in ESA's Living Planet Programme launched on November 22, 2013, as member of the validation team of the mission. Finally, assessment of heat wave risk and hazards is carried out systematically using MODIS satellite data.

Kontoes, Charalampos; Papoutsis, Ioannis; Amiridis, Vassilis; Balasis, George; Keramitsoglou, Iphigenia; Herekakis, Themistocles; Christia, Eleni

2014-05-01

60

1st EARSeL Workshop on Temporal Analysis of Satellite Images Mykonos, Greece, 23rd 25th May, 2012  

E-print Network

valuable data source. However, processing and analysis of satellite image time series poses some challenges1st EARSeL Workshop on Temporal Analysis of Satellite Images Mykonos, Greece, 23rd ­ 25th May, 2012 81 CLOUD-SCREENING FROM MULTISPECTRAL SATELLITE IMAGE TIME SERIES Luis G´omez-Chova, Julia Amor

Camps-Valls, Gustavo

61

Effective Interpolation of Incomplete Satellite-Derived Leaf-Area Index Time Series for the Continental United States  

NASA Technical Reports Server (NTRS)

Many earth science modeling applications employ continuous input data fields derived from satellite data. Environmental factors, sensor limitations and algorithmic constraints lead to data products of inherently variable quality. This necessitates interpolation of one form or another in order to produce high quality input fields free of missing data. The present research tests several interpolation techniques as applied to satellite-derived leaf area index, an important quantity in many global climate and ecological models. The study evaluates and applies a variety of interpolation techniques for the Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf-Area Index Product over the time period 2001-2006 for a region containing the conterminous United States. Results indicate that the accuracy of an individual interpolation technique depends upon the underlying land cover. Spatial interpolation provides better results in forested areas, while temporal interpolation performs more effectively over non-forest cover types. Combination of spatial and temporal approaches offers superior interpolative capabilities to any single method, and in fact, generation of continuous data fields requires a hybrid approach such as this.

Jasinski, Michael F.; Borak, Jordan S.

2008-01-01

62

TIME SERIES Syllabus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii  

E-print Network

TIME SERIES Contents Syllabus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv 1 Models for time series 1 1.1 Time series data Time series analysis refers to problems in which observations are collected at regular time intervals

Weber, Richard

63

Image-based correlation of Laser Scanning point cloud time series for landslide monitoring  

NASA Astrophysics Data System (ADS)

Very high resolution monitoring of landslide kinematics is an important aspect for a physical understanding of the failure mechanisms and for quantifying the associated hazard. In the last decade, the potential of Terrestrial Laser Scanning (TLS) to monitor slow-moving landslides has been largely demonstrated but accurate processing methods are still needed to extract useful information available in point cloud time series. This work presents an approach to measure the 3D deformation and displacement patterns from repeated TLS surveys. The method is based on the simplification of a 3D matching problem in a 2D matching problem by using a 2D statistical normalized cross-correlation function. The computed displacement amplitudes are compared to displacements (1) calculated with the classical approach of Iterative Closest Point and (2) measured from repeated dGPS observations. The performance of the method is tested on a 3 years dataset acquired at the Super-Sauze landslide (South French Alps). The observed landslide displacements are heterogeneous in time and space. Within the landslide, sub-areas presenting different deformation patterns (extension, compression) are detected by a strain analysis. It is demonstrated that pore water pressure changes within the landslide is the main controlling factor of the kinematics.

Travelletti, Julien; Malet, Jean-Philippe; Delacourt, Christophe

2014-10-01

64

Radiometric quality and performance of TIMESAT for smoothing moderate resolution imaging spectroradiometer enhanced vegetation index time series from western Bahia State, Brazil  

NASA Astrophysics Data System (ADS)

The launch of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua platforms in 1999 and 2002, respectively, with temporal resolutions of 1 to 2 days opened the possibility of using a longtime series of satellite images to map land use and land cover classes from different regions of the Earth, to study vegetation phenology, and to monitor regional and global climate change, among other applications. The main objectives of this study were twofold: to analyze the radiometric quality of the time series of enhanced vegetation index (EVI) products derived from the Terra MODIS sensor in western Bahia State, Brazil, and to identify the most appropriate filter to smooth MODIS EVI time series of the study area among those available in the public domain, the TIMESAT algorithm. The 2000 to 2011 time period was considered (a total of 276 scenes). The radiometric quality was analyzed based on the pixel reliability data set available in the MOD13Q1 product. The performances of the three smoothing filters available within TIMESAT (double logistic, Savitzky-Golay, and asymmetric Gaussian) were analyzed using the Graybill's F test and Willmott statistics. Five percent of the MODIS pixels from the study area were cloud-affected, almost all of which were from the rainy season. The double logistic filter presented the best performance.

Borges, Elane F.; Sano, Edson E.; Medrado, Euzébio

2014-01-01

65

Construction of merged satellite total O3 and NO2 time series in the tropics for trend studies and evaluation by comparison to NDACC SAOZ measurements  

NASA Astrophysics Data System (ADS)

Long time series of ozone and NO2 total column measurements in the southern tropics are available from two ground-based SAOZ (Système d'Analyse par Observation Zénithale) UV-visible spectrometers operated within the Network for the Detection of Atmospheric Composition Change (NDACC) in Bauru (22° S, 49° W) in S-E Brazil since 1995 and Reunion Island (21° S, 55° E) in the S-W Indian Ocean since 1993. Although the stations are located at the same latitude, significant differences are observed in the columns of both species, attributed to differences in tropospheric content and equivalent latitude in the lower stratosphere. These data are used to identify which satellites operating during the same period, are capturing the same features and are thus best suited for building reliable merged time series for trend studies. For ozone, the satellites series best matching SAOZ observations are EP-TOMS (1995-2004) and OMI-TOMS (2005-2011), whereas for NO2, best results are obtained by combining GOME version GDP5 (1996-2003) and SCIAMACHY - IUP (2003-2011), displaying lower noise and seasonality in reference to SAOZ. Both merged data sets are fully consistent with the larger columns of the two species above South America and the seasonality of the differences between the two stations, reported by SAOZ, providing reliable time series for further trend analyses and identification of sources of interannual variability in the future analysis.

Pastel, M.; Pommereau, J.-P.; Goutail, F.; Richter, A.; Pazmiño, A.; Ionov, D.; Portafaix, T.

2014-10-01

66

Classification of agricultural fields using time series of dual polarimetry TerraSAR-X images  

NASA Astrophysics Data System (ADS)

Due to its special imaging characteristics, Synthetic Aperture Radar (SAR) has become an important source of information for a variety of remote sensing applications dealing with environmental changes. SAR images contain information about both phase and intensity in different polarization modes, making them sensitive to geometrical structure and physical properties of the targets such as dielectric and plant water content. In this study we investigate multi temporal changes occurring to different crop types due to phenological changes using high-resolution TerraSAR-X imagers. The dataset includes 17 dual-polarimetry TSX data acquired from June 2012 to August 2013 in Lorestan province, Iran. Several features are extracted from polarized data and classified using support vector machine (SVM) classifier. Training samples and different features employed in classification are also assessed in the study. Results show a satisfactory accuracy for classification which is about 0.91 in kappa coefficient.

Mirzaee, S.; Motagh, M.; Arefi, H.; Nooryazdan, M.

2014-10-01

67

Mapping Deforestation and Age of Evergreen Trees by Applying a Binary Coding Method to Time-Series Landsat November Images  

Microsoft Academic Search

This paper proposes a binary coding method, a novel post classification change detection method that indexes multitemporal satellite images into a single information layer. As a case study, this method is applied to the production of a deforestation map and a tree age map of evergreen trees. Seven images of Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced TM Plus of

Hoonyol Lee

2008-01-01

68

A Quantitative Image Cytometry Technique for Time Series or Population Analyses of Signaling Networks  

PubMed Central

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 image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-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 imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling. PMID:20376360

Ozaki, Yu-ichi; Uda, Shinsuke; Saito, Takeshi H.; Chung, Jaehoon; Kubota, Hiroyuki; Kuroda, Shinya

2010-01-01

69

Volcano Watch Satellite Images  

NSDL National Science Digital Library

The University of Wisconsin's Space Science and Engineering Center displays these satellite images of the world's ten most active volcanoes. Users can view images of the Colima Volcano in Central Mexico or Mount Etna in Sicily, Italy. The latest images are updated every half-hour. Also, a Java animation feature splices together the last four images to show a simulation over a two-hour period.

70

What are Satellite Images?  

NSDL National Science Digital Library

This is an activity about image analysis. Learners will create a map of the room and discuss the perspectives shown in their drawings and how this relates to satelite images. Participants brainstorm a list of features that might be recognizable in satellite photos, search the Earth Images for these features, and place the images in categories depicting these features. This is activity 2 of 9 in Mars and Earth: Science Learning Activities for After School.

71

Image Classification Using Histograms and Time Series Analysis: A Study of Age-Related Macular Degeneration Screening in Retinal Image Data  

Microsoft Academic Search

\\u000a An approach to image mining is described that combines a histogram based representation with a time series analysis technique.\\u000a More specifically a Dynamic Time Warping (DTW) approach is applied to histogram represented image sets that have been enhanced\\u000a using CLAHE and noise removal. The focus of the work is the screening (classification) of retinal image sets to identify age-related\\u000a macular

Mohd Hanafi Ahmad Hijazi; Frans Coenen; Yalin Zheng

2010-01-01

72

Satellite Images: GOES  

NSDL National Science Digital Library

Updated every one to three hours, this Environment Canada page offers the latest Geosynchronous Operational Environmental Satellite (GOES) images (in MPEG format) from GOES-8 and GOES-9, covering Eastern Canada, Western Canada, Eastern North America, Western North America, Pacific North America, and North and South America. Images show global climate/weather patterns in the form of color graphics (full-size or scaled) and small or large animations. A particularly useful feature of the site is the FAQ section; users will find help with image interpretation by browsing the many questions and answers or by following links to other satellite information sites.

73

A 20-year long volume transport time series of the Antarctic Circumpolar Current obtained from in situ and satellite observations. Part IÂ : production and validation  

NASA Astrophysics Data System (ADS)

A 20-year long volume transport time series of the Antarctic Circumpolar Current (ACC) across the Drake Passage has been produced combining information from in situ mooring data (3 years, 2006-2009, current meter and ADCP) and satellite altimetry data (20 years, 1992-2012). A new method is designed to account for the dependence of the vertical structure on surface velocity and latitude. This method is based on the elaboration of a look-up table of velocity profiles. Yet unpublished velocity profile time series from Acoustic Doppler Current Profilers are analysed and used to provide accurate vertical structure estimates in the upper 500m. The cross-track mean surface geostrophic velocities are estimated using an error/correction scheme in a sensitivity study to the mean velocities deduced from two recent Mean Dynamic Topographies (MDT) : the CNES-CLS09 MDT and the CNES-CLS13 MDT. The look-up table is carefully checked with independent velocity data, and the robustness of the new method established. The volume transport is 140 +/- 2,2 Sv (standard error of the mean) in the upper 3000m and 141 +/- 2,2 Sv from the bottom to the surface. Both transports show a slightly significant decreasing trend with 95% confidence (between -0,15 and -0,35 Sv per year). The small 1 Sv difference between the 0-3000M and 0-bottom transports results from the deep recirculation cells. Partition between baroclinic/ barotropic transport over 3000m is 112 +/-1,6 / 28 +/-1,6 Sv and from the surface to the bottom 136 +/-1,6 Sv / 5 +/-1,6Sv. The barotropic time series present a decreasing trend (-0,35 Sv over 3000m and -0,6 SV from 0 to the bottom) while the baroclinic time series show an increasing trend (0,1 Sv over 3000 m, 0,3 Sv from 0 to the bottom). The total and baroclinic transport time series exhibit 5-year period variations that are significant at the beginning of the series.

Koenig, Zoé; Provost, Christine; Ferrari, Ramiro; Sennéchael, Nathalie; Rio, Marie-Hélène

2014-05-01

74

On the evaluation of vegetation resilience in Southern Italy by using VEGETATION, MODIS, TM satellite time series  

NASA Astrophysics Data System (ADS)

Satellite technologies can be profitably used for investigating the dynamics of vegetation re-growth after disturbance at different temporal and spatial scales. Nevertheless, disturbance -induced dynamical processes are very difficult to study since they affect the complex soil-surface-atmosphere system, due to the existence of feedback mechanisms involving human activity, ecological patterns and different subsystems of climate. The remote sensing of vegetation has been traditionally carried out by using vegetation indices, which are quantitative measures, based on vegetation spectral properties, that attempt to measure biomass or vegetative vigor. The vegetation indices operate by contrasting intense chlorophyll pigment absorption in the red against the high reflectance of leaf mesophyll in the near infrared. The simplest form of vegetation index is simply a ratio between two digital values from these two spectral bands. The most widely used index is the well-known normalized difference vegetation index NDVI = [NIR-R]/ [NIR+R]. The normalization of the NDVI reduces the effects of variations caused by atmospheric contaminations. High values of the vegetation index identify pixels covered by substantial proportions of healthy vegetation. NDVI is indicative of plant photosynthetic activity and has been found to be related to the green leaf area index and the fraction of photosynthetically active radiation absorbed by vegetation. Variations in NDVI values become indicative of variations in vegetation composition and dynamics. In this study, we analyze the mutiscale satellite temporal series ( 2000 to 2008) of NDVI and other vegetation indices from SPOT VEGETATION, MODIS and Landsat TM data acquired for some significant test areas affetced and unaffected (Southern Italy) by different types of environmental diturbances (drought, salinity, pollution, etc). Our objective was to characterize quantitatively the resilient effect of vegetation cover at differen temporal and spatial scales.

Didonna, I.; Coluzzi, R.

2009-04-01

75

On the evaluation of vegetation resilience in Southern Italy by using satellite VEGETATION, MODIS, TM time series  

NASA Astrophysics Data System (ADS)

Satellite technologies can be profitably used for investigating the dynamics of vegetation re-growth after disturbance at different temporal and spatial scales. Nevertheless, disturbance -induced dynamical processes are very difficult to study since they affect the complex soil-surface-atmosphere system, due to the existence of feedback mechanisms involving human activity, ecological patterns and different subsystems of climate. The remote sensing of vegetation has been traditionally carried out by using vegetation indices, which are quantitative measures, based on vegetation spectral properties, that attempt to measure biomass or vegetative vigor. The vegetation indices operate by contrasting intense chlorophyll pigment absorption in the red against the high reflectance of leaf mesophyll in the near infrared. The simplest form of vegetation index is simply a ratio between two digital values from these two spectral bands. The most widely used index is the well-known normalized difference vegetation index NDVI = [NIR-R]/ [NIR+R]. The normalization of the NDVI reduces the effects of variations caused by atmospheric contaminations. High values of the vegetation index identify pixels covered by substantial proportions of healthy vegetation. NDVI is indicative of plant photosynthetic activity and has been found to be related to the green leaf area index and the fraction of photosynthetically active radiation absorbed by vegetation. Therefore variations in NDVI values become indicative of variations in vegetation composition and dynamics. In this study, we analyze the mutiscale satellite temporal series ( 1998 to 2008) of NDVI and other vegetation indices from SPOT VEGETATION and Landsat TM data acquired for some significant test areas affetced and unaffected (Southern Italy) by different type of environmenta diturbances (drought, salinity, pollution, etc). Our objective is to characterize quantitatively the resilient effect of vegetation cover at different temporal and spatial scales

Coluzzi, C.; Didonna, I.

2009-04-01

76

Exploring Time Series Plots  

NSDL National Science Digital Library

Students will explore time series plots and raw data to understand the role of sea surface temperature increases on arctic ice melt. This is part three of a four-part activity on polar science. The activity builds on the knowledge gained in Using Data and Images to Understand Albedo (part 2). Extension activities examining air and sea surface temperature in relation to changing Earth albedo are included. Information is provided on data access using the NOAA Earth System Research Laboratory Web site. This activity is one of several learning activities connected with the 2007 GLOBE Earth system poster.

77

A 20-year long volume transport time series of the Antarctic Circumpolar Current obtained from in situ and satellite observations. Part II : Analysis of the variations  

NASA Astrophysics Data System (ADS)

A 20 year long transport time series of the Antarctic Circumpolar Current (ACC) has been produced from in situ and altimetric satellite observations across the Drake Passage (see Part I : mean 140 Sv, std 10 Sv ). Variations of the total, baroclinic and barotropic volume transports are analysed and their relation to the atmospheric forcing discussed. Sea level anomalies are used to understand the spatial patterns associated with transport variations. The spectral content of the volume transport time series present different significant periods: a five year trend, annual and semi annual periods that disappears between 2000-2002 and high frequencies. Variations in the volume transports are principally caused by variations in the Yaghan Basin, and more precisely by variations in the Subantarctic Front (SAF) and the Polar Front (PF). The total transport ranges between 100 Sv and 180 Sv, with several extreme cases (larger than 165 Sv and smaller than 110 Sv). The altimetric maps and velocity profiles corresponding to these extreme transport values are analysed to examine the typical patterns associated with these situations. Eastward rossby wave propagation is identified and associated with the semi annual period. The 5 year trend is caused by an indirect response of the baroclinic component of the transport to atmospheric variations via the Southern Annular Mode (SAM), with a lag of around 1,5 years. This 5-year trend disappears soon after 2000. The barotropic transport does not show this-5 year trend.

Koenig, Zoé; Provost, Christine; Ferrari, Ramiro; Sennéchael, Nathalie; Park, Young-Hyang

2014-05-01

78

Remote Sensing Time Series Product Tool  

NASA Technical Reports Server (NTRS)

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, 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 Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image 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 satellite 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 satellites, 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 time series plots and image 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 images. This type of time series 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 time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Predos, Don; Ryan, Robert E.; Ross, Kenton W.

2006-01-01

79

Reduction of Influences of the Earth's Surface Fluid Loads on GPS Site Coordinate Time Series and Global Satellite Laser Ranging Analysis  

NASA Astrophysics Data System (ADS)

Temporal change of surface loadings due to the mass redistribution of the fluid envelope of the Earth, deform the Earth and cause the coordinate changes of the observation sites. We estimated the crustal displacements due to the atmospheric load (AL), the non-tidal ocean load (NTOL), the continental water load (CWL) and the snow load (SL) influences using the several meteorological data and model. And then, we tried to eliminate the load influences from the GPS site coordinate time series and global Satellite Laser Ranging (SLR) analysis. As the time series of GPS site coordinates, we employed a solution of IGS which was calculated by using GIPSY-OASIS II (Heflin et al., 2002) by the Jet Propulsion Laboratory (JPL) and the routine solution of GEONET called F2 solution which was calculated by Bernese version 4.2 software (Hatanaka et al., 2003) by the Geographical Survey Institute. To eliminate periodic signals of the loading effects, we calculated Corrected GPS = GPS - (Load1 + Load2 + . . . . . + Loadn). The results show that a combination of atmospheric, non-tidal ocean, continental water, and snow loads can eliminate about 20% of the annual signal in the coordinate time series for vertical components. We applied the loading correction to the data of the 1997 Bungo channel slow slip event and showed that the correction can benefit the analysis of such a non-periodic event. Next, we applied the time series of NTOL and CWL to precise SLR analysis that used the "concerto" program version 4 developed by the National Institute of Information and Communications Technology (NICT). The LAGEOS orbit analysis reveals that the Estimating the Circulation and Climate of the Ocean (ECCO) model makes the root mean square (RMS) of the range residual 0.2% smaller, and that the CWL makes it 0.8% smaller, compared with the case where loading displacement is neglected. On the other hand, with the NTOL derived from Topex/Poseidon altimetry data, the SLR orbit fit is not improved.

Takiguchi, H.; Otsubo, T.; Fukuda, Y.

2006-12-01

80

Monitoring of Ground Deformation in the Haoud Berkaoui Oil Field (Sahara, Algeria) Using Time Series Analysis of SAR Images  

NASA Astrophysics Data System (ADS)

We investigate the surface displacement in the Haoud Berkaoui (Algerian Sahara) area, a locus of an oil well accident since 1978, using an advanced MT-InSAR analysis. The Haoud Berkaoui area also includes numerous wells that served for oil extraction starting from 1970s. Among all wells, OKN32 and OKN32bis collapsed due to dissolution of evaporitic rocks inducing rapid ground subsidence and eventually a spectacular 320-m-diameter crater and ~80-m-depth as per today. We apply the small baseline (SB) and the PS-InSAR (Persistent Scatterer) methods to retrieve deformation maps and displacement time series from ESA - SAR images (ERS1 and ERS2) acquired between 1992 and 2002. Our analysis delimits the subsidence area and shows an average 1.5 mm/year subsidence located around the OKN32 (oil well) and in the direction of Ouargla city. We also evaluate the possible propagation and the direction of subsidence by studying the spatial temporal variation of subsidence together with the distribution of the other oil wells in the same area. An elastic model with volume decrease is calculated to correlate the surface subsidence with the dissolution-collapse at depth. The study of this incident helps in the understanding of the subsidence process and the mitigation of further underground collapse that may affect neighboring urban areas.

Meghraoui, M.; Bouraoui, S.; Bougdal, R.; Cakir, Z.

2012-12-01

81

Satellite camera image navigation  

NASA Technical Reports Server (NTRS)

Pixels within a satellite camera (1, 2) image are precisely located in terms of latitude and longitude on a celestial body, such as the earth, being imaged. A computer (60) on the earth generates models (40, 50) of the satellite's orbit and attitude, respectively. The orbit model (40) is generated from measurements of stars and landmarks taken by the camera (1, 2), and by range data. The orbit model (40) is an expression of the satellite's latitude and longitude at the subsatellite point, and of the altitude of the satellite, as a function of time, using as coefficients (K) the six Keplerian elements at epoch. The attitude model (50) is based upon star measurements taken by each camera (1, 2). The attitude model (50) is a set of expressions for the deviations in a set of mutually orthogonal reference optical axes (x, y, z) as a function of time, for each camera (1, 2). Measured data is fit into the models (40, 50) using a walking least squares fit algorithm. A transformation computer (66 ) transforms pixel coordinates as telemetered by the camera (1, 2) into earth latitude and longitude coordinates, using the orbit and attitude models (40, 50).

Kamel, Ahmed A. (Inventor); Graul, Donald W. (Inventor); Savides, John (Inventor); Hanson, Charles W. (Inventor)

1987-01-01

82

Subsidence history of the city of Morelia, Mexico based on InSAR images processed as time series  

NASA Astrophysics Data System (ADS)

The city of Morelia in central Mexico sits on lacustrine and fluvio-lacustrine deposits. Subsidence due to the extraction of water from the subsoil is evidenced by the presence of differential soil compaction, causing faulting and cracking of the ground and adjacent constructions. In order to study the subsidence history of the past nine years, twenty-eight ENVISAT Synthetic Aperture Radar (SAR) images acquired between May 2003 and September 2010 were processed using ROI_PAC. All scenes are descending orbit images. The resulting interferograms were filtered using an adaptive filter and, in order to increase coherence and signal-to-noise ratio, they were unwrapped using the "branch-cut" algorithm. A subset of the resulting interferograms was selected based on the following criteria. Only interferograms with spatial baseline of less than 400 m and a temporal baseline of less than 420 days were considered. The primary objective of our work was to determine the temporal evolution of the subsidence in different parts of the city. To this end, selected pixels are inverted in an independent manner from neighbouring pixels using a time series analysis. Preliminary results suggest that the central part of the basin, near the fault known as the "Central Camionera", the subsidence is almost constant with a value of 3 to 4 cm/yr until 2008. From this date on, the subsidence rates increase to values with an average of 7 to 8 cm/yr. This increase in the subsidence rate is clearly appreciated in the appearance of two clearly visible circular patterns from 2008 to 2010. Currently, an inversion is being conducted to obtain the overall subsidence history of the basin.

Jaramillo, S. H.; Suárez, G.; López-Quiroz, P.

2012-04-01

83

Volume transport of the Antarctic Circumpolar Current: Production and validation of a 20 year long time series obtained from in situ and satellite observations  

NASA Astrophysics Data System (ADS)

20 year long volume transport time series of the Antarctic Circumpolar Current across the Drake Passage is estimated from the combination of information from in situ current meter data (2006-2009) and satellite altimetry data (1992-2012). A new method for transport estimates had to be designed. It accounts for the dependence of the vertical velocity structure on surface velocity and latitude. Yet unpublished velocity profile time series from Acoustic Doppler Current Profilers are used to provide accurate vertical structure estimates in the upper 350 m. The mean cross-track surface geostrophic velocities are estimated using an iterative error/correction scheme to the mean velocities deduced from two recent mean dynamic topographies. The internal consistency and the robustness of the method are carefully assessed. Comparisons with independent data demonstrate the accuracy of the method. The full-depth volume transport has a mean of 141 Sv (standard error of the mean 2.7 Sv), a standard deviation (std) of 13 Sv, and a range of 110 Sv. Yearly means vary from 133.6 Sv in 2011 to 150 Sv in 1993 and standard deviations from 8.8 Sv in 2009 to 17.9 Sv in 1995. The canonical ISOS values (mean 133.8 Sv, std 11.2 Sv) obtained from a year-long record in 1979 are very similar to those found here for year 2011 (133.6 Sv and 12 Sv). Full-depth transports and transports over 3000 m barely differ as in that particular region of Drake Passage the deep recirculations in two semiclosed basins have a close to zero net transport.

Koenig, Zoé; Provost, Christine; Ferrari, Ramiro; Sennéchael, Nathalie; Rio, Marie-Hélène

2014-08-01

84

Satellite Hyperspectral Imaging Simulation  

NASA Technical Reports Server (NTRS)

Simulation of generic pushbroom satellite hyperspectral sensors have been performed to evaluate the potential performance and validation techniques for satellite systems such as COIS(NEMO), Warfighter-1(OrbView-4) and Hyperion(EO-1). The simulations start with a generation of synthetic scenes from material maps of studied terrain. Scene-reflected radiance is corrected for atmospheric effects and convolved with sensor spectral response using MODTRAN 4 radiance and transmissions calculations. Scene images are further convolved with point spread functions derived from Optical Transfer Functions (OTF's) of the sensor system. Photon noise and etectorr/electronics noise are added to the simulated images, which are also finally quantized to the sensor bit resolution. Studied scenes include bridges and straight roads used for evaluation of sensor spatial resolution, as well as fields of minerals, vegetation and manmade materials used for evaluation of sensor radiometric response and sensitivity. The scenes are simulated with various seasons and weather conditions. Signal-to-noise ratios and expected performance are estimated for typical satellite system specifications and are discussed for all the scenes.

Zanoni, Vicki; Stanley, Tom; Blonski, Slawomir; Cao, Changyong; Gasser, Jerry; Ryan, Robert

1999-01-01

85

Bootstrapping time series models  

Microsoft Academic Search

This paper surveys recent development in bootstrap methods and the modifications needed for their applicability in time series models. The paper discusses some guidelines for empirical researchers in econometric analysis of time series. Different sampling schemes for bootstrap data generation and different forms of bootstrap test statistics are discussed. The paper also discusses the applicability of direct bootstrapping of data

G. S. Hongyi Li; G. S. Maddala

1996-01-01

86

Time Series Data Library  

NSDL National Science Digital Library

This is a collection of time series datasets covering many application areas, but are all for time series 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.

Hyndman, Robert

2009-08-13

87

Mining Time Series Data  

NASA Astrophysics Data System (ADS)

Much of the world's supply of data is in the form of time series. In the last decade, there has been an explosion of interest in mining time series data. A number of new algorithms have been introduced to classify, cluster, segment, index, discover rules, and detect anomalies/novelties in time series. While these many different techniques used to solve these problems use a multitude of different techniques, they all have one common factor; they require some high level representation of the data, rather than the original raw data. These high level representations are necessary as a feature extraction step, or simply to make the storage, transmission, and computation of massive dataset feasible. A multitude of representations have been proposed in the literature, including spectral transforms, wavelets transforms, piecewise polynomials, eigenfunctions, and symbolic mappings. This chapter gives a high-level survey of time series Data Mining tasks, with an emphasis on time series representations.

Ratanamahatana, Chotirat Ann; Lin, Jessica; Gunopulos, Dimitrios; Keogh, Eamonn; Vlachos, Michail; Das, Gautam

88

Quantification of fluorescent spots in time series of 3D confocal microscopy images of endoplasmic reticulum exit sites based on the HMAX transform  

NASA Astrophysics Data System (ADS)

We present an approach for the quantification of fluorescent spots in time series of 3-D confocal microscopy images of endoplasmic reticulum exit sites of dividing cells. Fluorescent spots are detected based on extracted image regions of highest response using the HMAX transform and prior convolution of the 3-D images with a Gaussian kernel. The sensitivity of the involved parameters was studied and a quantitative evaluation using both 3-D synthetic and 3-D real data was performed. The approach was successfully applied to more than one thousand 3-D confocal microscopy images.

Matula, Petr; Verissimo, Fatima; Wörz, Stefan; Eils, Roland; Pepperkok, Rainer; Rohr, Karl

2010-03-01

89

Ordinal time series analysis  

Microsoft Academic Search

We discuss robust methods of time series analysis which use only comparisons of values and not their actual size. Local and global order structure are defined as matrices or by rank numbers. Local ranks, autocorrelation by Kendall’s tau, and permutation entropy as complexity measure are introduced in such a way that they contain a scale parameter which allows to study

Christoph Bandt

2005-01-01

90

Digital Watermarking Of Satellite Images  

Microsoft Academic Search

In this paper an efficient watermarking algorithm is proposed for copyrighting of satellite images. A look-up table method in pixel domain that does not distort certain specific regions in the original image has been used. A watermark is embedded invisibly and irreversibly in the host image without disturbing the vital areas of ones interest. This watermark is embedded in such

Yogesh Chauhan; P. Gupta; Kantilal L. Majumder

2002-01-01

91

Recent Advances in Mining Time Series Data  

Microsoft Academic Search

\\u000a Much of the world’s supply of data is in the form of time series. Furthermore, as we shall see, many types of data can be\\u000a meaningfully converted into ”time series”, including text, DNA, video, images etc. The last decade has seen an explosion of\\u000a interest in mining time series data from the academic community. There has been significant work on

Eamonn J. Keogh

2005-01-01

92

Recent Advances in Mining Time Series Data  

Microsoft Academic Search

\\u000a Much of the world’s supply of data is in the form of time series. Furthermore, as we shall see, many types of data can be\\u000a meaningfully converted into ”time series”, including text, DNA, video, images etc. The last decade has seen an explosion of\\u000a interest in mining time series data from the academic community. There has been significant work on

Eamonn Keogh

93

Contrail Detection in Satellite Images  

NASA Astrophysics Data System (ADS)

Methods for detecting linear contrail pixels in satellite infrared images are described. An objective contrail detection algorithm has been developed and extensively applied to data from various polar and geostationary satellite sensors. The method uses the contrast in brightness temperatures near 11 and 12 ?m wavelengths and detects linear contrails using image 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 satellite data in correlation with traffic and meteorological data.

Mannstein, Hermann; Vázquez-Navarro, Margarita; Graf, Kaspar; Duda, David P.; Schumann, Ulrich

94

Aerial Photographs and Satellite Images  

USGS Publications Warehouse

Photographs and other images of the Earth taken from the air and from space show a great deal about the planet's landforms, vegetation, and resources. Aerial and satellite images, known as remotely sensed images, permit accurate mapping of land cover and make landscape features understandable on regional, continental, and even global scales. Transient phenomena, such as seasonal vegetation vigor and contaminant discharges, can be studied by comparing images acquired at different times. The U.S. Geological Survey (USGS), which began using aerial photographs for mapping in the 1930's, archives photographs from its mapping projects and from those of some other Federal agencies. In addition, many images from such space programs as Landsat, begun in 1972, are held by the USGS. Most satellite scenes can be obtained only in digital form for use in computer-based image processing and geographic information systems, but in some cases are also available as photographic products.

U.S. Geological Survey

1997-01-01

95

Geomatics techniques applied to time series of aerial images for multitemporal geomorphological analysis of the Miage Glacier (Mont Blanc).  

NASA Astrophysics Data System (ADS)

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 images (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 images (still in analogic form) through photogrammetric scanners (very low image distortions devices) taking care of correctly defining the resolution of the acquisition compared to the scale mapping images are suitable for; b) to import digitized images into an appropriate digital photogrammetry software environment; c) to manage images 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 images 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.

Perotti, Luigi; Carletti, Roberto; Giardino, Marco; Mortara, Giovanni

2010-05-01

96

Detection method for small and dim targets from a time series of images observed by a space-based optical detection system  

NASA Astrophysics Data System (ADS)

To revisit cataloged space targets, a space-based optical detection system normally observes space targets continuously in a target tracking mode. In the time series of images produced by continuous observation, there are not only the target but also complicated background clutter (a mass of stars) and noises. The existing method only can detect the target with an signal-to-noise ratio (SNR) greater than 6 from these images. This paper presents a detection method for the target with an SNR less than 6. The proposed method consists of an SNR enhancement algorithm and an adaptive background and noise suppression algorithm. Simulation and analytical results show the proposed method detects the target submerged in noise and background clutter when SNR is equal to 3 and the detection probability and the false alarm probability both reach very high performance. This proposed method can help solve the problem of revisiting some weak cataloged space targets.

Pan, HaiBin; Song, GuangHua; Xie, LiJun; Zhao, Yao

2014-05-01

97

Characterizing Methane Emissions at Local Scales with a 20 Year Total Hydrocarbon Time Series, Imaging Spectrometry, and Web Facilitated Analysis  

NASA Astrophysics Data System (ADS)

Methane is an important greenhouse gas for which uncertainty in local emission strengths necessitates improved source characterizations. Although CH4 plume mapping did not motivate the NASA Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) design and municipal air quality monitoring stations were not intended for studying marine geological seepage, these assets have capabilities that can make them viable for studying concentrated (high flux, highly heterogeneous) CH4 sources, such as the Coal Oil Point (COP) seep field (˜0.015 Tg CH4 yr-1) offshore Santa Barbara, California. Hourly total hydrocarbon (THC) data, spanning 1990 to 2008 from an air pollution station located near COP, were analyzed and showed geologic CH4 emissions as the dominant local source. A band ratio approach was developed and applied to high glint AVIRIS data over COP, resulting in local-scale mapping of natural atmospheric CH4 plumes. A Cluster-Tuned Matched Filter (CTMF) technique was applied to Gulf of Mexico AVIRIS data to detect CH4 venting from offshore platforms. Review of 744 platform-centered CTMF subsets was facilitated through a flexible PHP-based web portal. This dissertation demonstrates the value of investigating municipal air quality data and imaging spectrometry for gathering insight into concentrated methane source emissions and highlights how flexible web-based solutions can help facilitate remote sensing research.

Bradley, Eliza Swan

98

Satellite Image Mosaic Engine  

NASA Technical Reports Server (NTRS)

A computer program automatically builds large, full-resolution mosaics of multispectral images of Earth landmasses from images acquired by Landsat 7, complete with matching of colors and blending between adjacent scenes. While the code has been used extensively for Landsat, it could also be used for other data sources. A single mosaic of as many as 8,000 scenes, represented by more than 5 terabytes of data and the largest set produced in this work, demonstrated what the code could do to provide global coverage. The program first statistically analyzes input images to determine areas of coverage and data-value distributions. It then transforms the input images from their original universal transverse Mercator coordinates to other geographical coordinates, with scaling. It applies a first-order polynomial brightness correction to each band in each scene. It uses a data-mask image for selecting data and blending of input scenes. Under control by a user, the program can be made to operate on small parts of the output image space, with check-point and restart capabilities. The program runs on SGI IRIX computers. It is capable of parallel processing using shared-memory code, large memories, and tens of central processing units. It can retrieve input data and store output data at locations remote from the processors on which it is executed.

Plesea, Lucian

2006-01-01

99

Discrimination problems for satellite images  

Microsoft Academic Search

This paper discusses the pitfalls of classifying satellite images using automatic classifiers. The discussion is illustrated by application of quadratic and linear discrimination to high resolution data produced for the National Remote Sensing Centre campaign. Within the training set there is good discrimination between most land uses, but the lack of agreement between overall results of discrimination for the two

C. D. KERSHAW

1987-01-01

100

Causality between time series  

E-print Network

Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging question, which is of wide concern in different disciplines, a positive answer. Here causality is measured by the time rate of change of information flowing from one series, say, X2, to another, X1. The measure is asymmetric between the two parties and, particularly, if the process underlying X1 does not depend on X2, then the resulting causality from X2 to X1 vanishes. The formula is tight in form, involving only the commonly used statistics, sample covariances. It has been validated with touchstone series purportedly generated with one-way causality. It has also been applied to the investigation of real world problems; an example presented here is the cause-effect relation between two climate modes, El Ni\\~no and Indian Ocean Dipole, which have been linked to the hazards in f...

Liang, X San

2014-01-01

101

ENVIRONMENTALLYORIENTED PROCESSING OF MULTISPECTRAL SATELLITE IMAGES  

E-print Network

ENVIRONMENTALLY­ORIENTED PROCESSING OF MULTI­SPECTRAL SATELLITE IMAGES: NEW CHALLENGES FOR BAYESIAN words: satellite imaging, multi­spectral satellite data, environmental appli­ cations, Bayes risk 1 from the processing of data obtained from sensors mounted on satellites with the capability of taking

Kreinovich, Vladik

102

Least-squares analysis of time series data and its application to two-way satellite time and frequency transfer measurements  

Microsoft Academic Search

Two-way satellite time and frequency transfer (TWSTFT) has been used operationally by the international time and frequency community for several years. This paper describes analysis techniques being developed at the National Physical Laboratory for the processing of TWSTFT measurements. The measurements are modelled in terms of phase and normalized frequency offsets together with random errors considered to be a linear

P. M. Harris; J. A. Davis; M. G. Cox; S. L. Shemar

2003-01-01

103

Least-squares analysis of time series data and its application to two-way satellite time and frequency transfer measurements  

Microsoft Academic Search

Two-way satellite time and frequency transfer (TWSTFT) has been used operationally by the international time and frequency community for several years. This paper describes analysis techniques being developed at the National Physical Laboratory for the processing of TWSTFT measurements.The measurements are modelled in terms of phase and normalized frequency offsets together with random errors considered to be a linear combination

P M Harris; J A Davis; M G Cox; S L Shemar

2003-01-01

104

Uncertainties assessment and satellite validation over 2 years time series of multispectral and hyperspectral measurements in coastal waters at Long Island Sound Coastal Observatory  

NASA Astrophysics Data System (ADS)

Optical remote sensing of coastal waters from space is a basic requirement for monitoring global water quality and assessing anthropogenic impacts. However, this task remains highly challenging due to the optical complexity of the atmosphere-water system in coastal areas. In order to support present and future multi- and hyper-spectral calibration/validation activities for the Ocean Color Radiometry (OCR) satellites, as well as the development of new measurements and retrieval techniques for coastal waters, City College of New York along with the Naval Research Laboratory (Stennis) has established a scientifically comprehensive observation platform, the Long Island Sound Coastal Observatory (LISCO). As an integral part of the NASA AERONET - Ocean Color Network, LISCO is equipped with a multispectral SeaPRISM system. In addition, LISCO expands its observational capabilities through hyperspectral measurements with a HyperSAS system. The related multi- and hyperspectral data processing and data quality analysis are described. The three main OCR satellites, MERIS, MODIS and SeaWiFS, have been evaluated against the LISCO dataset of quality-checked measurements of SeaPRISM and HyperSAS. Adjacency effects impacting satellite data have been analyzed and found negligible. The remote sensing reflectances retrieved from satellite and in situ data are also compared. These comparisons show satisfactory correlations (R2 > 0.91 at 547nm) and consistencies (median value of the absolute percentage difference ~ 7.4%). It is also found that merging of the SeaPRISM and HyperSAS data at LISCO site significantly improve the overall data quality which makes this dataset highly suitable for satellite data validation purposes or for potential vicarious calibration activities.

Ahmed, S. A.; Harmel, T.; Gilerson, A.; Tonizzo, A.; Hlaing, S.; Weidemann, A.; Arnone, R. A.

2011-11-01

105

Satellite imagery meets prepress - Producing image maps  

SciTech Connect

Satellite imagery provided by Landsat, SPOT, AVHRR, and ERS-1 is being exploited for production of satellite image maps which incorporate images. Satellite image 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 satellite image maps for the military and environmental resource organizations.

Audrain, V.; Fehrenbach, J.; Reading, M.; Stauffer, R. (Intergraph Corp., Huntsville, AL (United States))

1993-07-01

106

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool  

NASA Technical Reports Server (NTRS)

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

2008-01-01

107

Collecting and Animating Online Satellite Images.  

ERIC Educational Resources Information Center

Describes how to generate automated classroom resources from the Internet. Topics covered include viewing animated satellite weather images using file transfer protocol (FTP); sources of images on the Internet; shareware available for viewing images; software for automating image retrieval; procedures for animating satellite images; and storing…

Irons, Ralph

1995-01-01

108

Figure 1. Satellite image before neural net Figure 5. Satellite image after  

E-print Network

Figure 1. Satellite image before neural net processing Figure 5. Satellite image after processing. Satellite image after processing for identification of land and water (Water is colored as jet black regions such as image processing. This paper develops an efficient method for processing remote-sensing satellite data

Michel, Howard E.

109

Large scale variability, long-term trends and extreme events in total ozone over the northern mid-latitudes based on satellite time series  

NASA Astrophysics Data System (ADS)

Various generations of satellites (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 satellite 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.

Rieder, H. E.; Staehelin, J.; Maeder, J. A.; Ribatet, M.; Davison, A. C.

2009-04-01

110

Time-series of biomass burning products from ground-based FTIR measurements at Reunion Island (21°S, 55°E) and comparisons with the CTM IMAGES  

NASA Astrophysics Data System (ADS)

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 time-series of several biomass burning products such as C2H2, C2H6 and HCN. These ground-based data are compared to the CTM IMAGES. The Lagrangian particle dispersion model FLEXPART is used to explain the day-to-day variability of these species by the transport pathways.

Vigouroux, Corinne; de Mazière, Martine; Dils, Bart; Müller, Jean-François; Senten, Cindy; Stavrakou, Trissevgeni; Vanhaelewyn, Gauthier; Fally, Sophie; Duflot, Valentin; Baray, Jean-Luc

2010-05-01

111

Diagrammatic Description of Satellite Image Processing Workflow  

Microsoft Academic Search

Multiple experiments on grid based satellite imagery classification require flexible descriptions of the processing workflow. The user develops the processing workflow pattern by visual tools in terms of satellite image multi-band spectral data. Each pattern may be stored into a repository and instantiated later for a particular area and time of the satellite image. The specific processing can be scheduled

Anca Radu; Victor Bacu; Dorian Gorgan

2007-01-01

112

Spectrally Consistent Satellite Image Fusion with Improved Image Priors  

E-print Network

Spectrally Consistent Satellite Image Fusion with Improved Image Priors H. Aanæs, A. A. Nielsen}@hi.is Abstract-- Here an improvement to our previous frame- work for satellite image fusion is presented-dependent image smoothing. I. INTRODUCTION Image fusion is the subset of data fusion dealing with merging images

113

Time Series Hilary Term 2002  

E-print Network

Time Series Practical Hilary Term 2002 Dr. Gesine Reinert The following are data of new on nightingale. Carry out an analysis of the data. 1. Load the data as a time series, for example attach the function gls. It is advisable to shift the time axis. For example timtime(newcars) -1990 fit

114

13 years time series of stratospheric and mesospheric ozone profiles measured by the NDACC microwave radiometer SOMORA over Switzerland: comparison to radiosonde and MLS/AURA satellite ozone profiles.  

NASA Astrophysics Data System (ADS)

The microwave radiometer SOMORA measures ozone volume mixing ratio in the stratosphere and lower mesosphere since January 2000 with a time resolution of 30 min. The ozone vertical distribution is calculated from the measurement of the rotational emission line of ozone at 142.17 GHz. Ozone profiles are retrieved using ARTS/Qpack, a general environment for radiative transfer simulation and retrieval of ozone profiles based on the optimal estimation method (OEM) of Rodgers. SOMORA is an instrument of the NDACC.The measurement time series has been influenced by the upgrade from an acousto optical spectrometer (AOS) setup to a digital FFT spectrometer setup in 2010. The ozone profiles dataset measured by the AOS (2000-2010) and FFT spectrometer (since 2010) is then homogenized using one year parallel measurements by adding an altitude dependent offset to the AOS ozone profiles. The ozone profiles measured by AOS show a slightly better vertical resolution above 55 km than the ozone profiles measured by FFT due to the higher spectral resolution.The homogenized 13 years SOMORA time series has been validated against Payerne radiosonde (RS) ozone profiles, GROMOS microwave radiometer ozone profiles of Bern, another NDACC instrument, and MLS/AURA satellite simultaneous ozones profiles, and the results will be shown. For the whole period of respective common measurements, SOMORA ozone profiles are within 5% of Payerne RS, 15% of GROMOS and 10% of MLS ozone profiles.

Maillard Barras, Eliane; Haefele, Alexander; Ruffieux, Dominique; Kämpfer, Niklaus

2014-05-01

115

Developing an automated global validation site time series system for VIIRS  

NASA Astrophysics Data System (ADS)

Long-term top of atmosphere (TOA) reflectance, brightness temperature, and band ratio time series over well-established validation sites provide important information for post-launch calibration stability monitoring and analysis. In this study, we present an automated and highly extensible global validation site time series system for the Visible and Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) satellite. The system includes 30 globally distributed sites. Validation site database and quality control parameters for each site can be easily modified without software code modification. VIIRS sensor data records over each validation site are automatically identified from NPP product archives. Validation time series plots for all VIIRS Reflective Solar Bands and Thermal Emissive Bands are updated daily and available online. Bands I2/M7 and I3/M10 inter-channel consistency analysis using the validation time series developed in this study is also included.

Wang, Wenhui; Cao, Changyong; Uprety, Sirish; Bai, Yan; Padula, Frank; Shao, Xi

2014-10-01

116

IMAGE Satellite 1/4-scale Model  

NSDL National Science Digital Library

This is an activity about scale model building. Learners will use mathematics to determine the scale model size, construct a pattern, and build a one-fourth size scale model of the IMAGE (Imager for Magnetopause-to-Aurora Global Exploration) satellite, the first satellite mission to image the Earth's magnetosphere. This is the third activity in the Solar Storms and You: Exploring Satellite Design educator guide.

117

Potential of time series-hyperspectral imaging (TS-HSI) for non-invasive determination of microbial spoilage of salmon flesh.  

PubMed

This study investigated the potential of using time series-hyperspectral imaging (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

Wu, Di; Sun, Da-Wen

2013-07-15

118

Satellite image maps of Pakistan  

USGS Publications Warehouse

Georeferenced Landsat satellite image maps of Pakistan are now being made available for purchase from the U.S. Geological Survey (USGS). The first maps to be released are a series of Multi-Spectral Scanner (MSS) color image maps compiled from Landsat scenes taken before 1979. The Pakistan image maps were originally developed by USGS as an aid for geologic and general terrain mapping in support of the Coal Resource Exploration and Development Program in Pakistan (COALREAP). COALREAP, a cooperative program between the USGS, the United States Agency for International Development, and the Geological Survey of Pakistan, was in effect from 1985 through 1994. The Pakistan MSS image maps (bands 1, 2, and 4) are available as a full-country mosaic of 72 Landsat scenes at a scale of 1:2,000,000, and in 7 regional sheets covering various portions of the entire country at a scale of 1:500,000. The scenes used to compile the maps were selected from imagery available at the Eros Data Center (EDC), Sioux Falls, S. Dak. Where possible, preference was given to cloud-free and snow-free scenes that displayed similar stages of seasonal vegetation development. The data for the MSS scenes were resampled from the original 80-meter resolution to 50-meter picture elements (pixels) and digitally transformed to a geometrically corrected Lambert conformal conic projection. The cubic convolution algorithm was used during rotation and resampling. The 50-meter pixel size allows for such data to be imaged at a scale of 1:250,000 without degradation; for cost and convenience considerations, however, the maps were printed at 1:500,000 scale. The seven regional sheets have been named according to the main province or area covered. The 50-meter data were averaged to 150-meter pixels to generate the country image on a single sheet at 1:2,000,000 scale

Geological Survey (U.S.)

1997-01-01

119

FROG: Time-series analysis  

NASA Astrophysics Data System (ADS)

FROG performs time series analysis and display. It provides a simple user interface for astronomers wanting to do time-domain astrophysics but still offers the powerful features found in packages such as PERIOD (ascl:1406.005). FROG includes a number of tools for manipulation of time series. Among other things, the user can combine individual time series, detrend series (multiple methods) and perform basic arithmetic functions. The data can also be exported directly into the TOPCAT (ascl:1101.010) application for further manipulation if needed.

Allan, Alasdair

2014-06-01

120

Time Series of the Biscuit Fire  

NSDL National Science Digital Library

This animation contains a time series of print resolution still images showing the progression of the Biscuit fire in Oregon during 2002. Fire locations are represented as particles that change color as the fire ages. The Biscuit fire burned 500,000 acres of forest in Oregon and Northern California during the summer and fall of 2002.

Starr, Cindy; Justice, Chris; Sohlberg, Robert; Gunther, Fred; North, William

2003-08-04

121

Rule Discovery from Time Series  

Microsoft Academic Search

We consider the problem of finding rules relating pat- terns in a time series 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 \\

Gautam Das; King-ip Lin; Heikki Mannila; Gopal Renganathan; Padhraic Smyth

1998-01-01

122

Seasonal variabilty of surface velocities and ice discharge of Columbia Glacier, Alaska using high-resolution TanDEM-X satellite time series and NASA IceBridge data  

NASA Astrophysics Data System (ADS)

Columbia Glacier is a grounded tidewater glacier located on the south coast of Alaska. It has lost half of its volume during 1957-2007, more rapidly after 1980. It is now split into two branches, known as Main/East and West branch due to the dramatic retreat of ~ 23 km and calving of iceberg from its terminus in past few decades. In Alaska, a majority of the mass loss from glaciers is due to rapid ice flow and calving icebergs into tidewater and lacustrine environments. In addition, submarine melting and change in the frontal position can accelerate the ice flow and calving rate. We use time series of high-resolution TanDEM-X stripmap satellite imagery during 2011-2013. The active image of the bistatic TanDEM-X acquisitions, acquired over 11 or 22 day repeat intervals, are utilized to derive surface velocity fields using SAR intensity offset tracking. Due to the short temporal baselines, the precise orbit control and the high-resolution of the data, the accuracies of the velocity products are high. We observe a pronounce seasonal signal in flow velocities close to the glacier front of East/Main branch of Columbia Glacier. Maximum values at the glacier front reach up to 14 m/day were recorded in May 2012 and 12 m/day in June 2013. Minimum velocities at the glacier front are generally observed in September and October with lowest values below 2 m/day in October 2012. Months in between those dates show corresponding increase or deceleration resulting a kind of sinusoidal annual course of the surface velocity at the glacier front. The seasonal signal is consistently decreasing with the distance from the glacier front. At a distance of 17.5 km from the ice front, velocities are reduced to 2 m/day and almost no seasonal variability can be observed. We attribute these temporal and spatial variability to changes in the basal hydrology and lubrification of the glacier bed. Closure of the basal drainage system in early winter leads to maximum speeds while during a fully developed basal drainage system speeds are at their minimum. We also analyze the variation in conjunction with the prevailing meteorological conditions as well as changes in calving front position in order to exclude other potential influencing factors. In a second step, we also exploit TanDEM-X data to generate various digital elevation models (DEMs) at different time steps. The multi-temporal DEMs are used to estimate the difference in surface elevation and respective ice thickness changes. All TanDEM-X DEMs are well tied with a SPOT reference DEM. Errors are estimated over ice free moraines and rocky areas. The quality of the TanDEM-X DEMs on snow and ice covered areas are further assessed by a comparison to laser scanning data from NASA Icebridge campaigns. The time wise closest TanDEM-X DEMs were compared to the Icebridge tracks from winter and summer surveys in order to judge errors resulting from the radar penetration of the x/band radar signal into snow, ice and firn. The average differences between laser scanning and TanDEM-X in August, 2011 and March, 2012 are observed to be 8.48 m and 14.35 m respectively. Retreat rates of the glacier front are derived manually by digitizing the terminus position. By combining the data sets of ice velocity, ice thickness and the retreat rates at different time steps, we estimate the seasonal variability of the ice discharge of Columbia Glacier.

Vijay, Saurabh; Braun, Matthias

2014-05-01

123

Robust airplane detection in satellite images  

Microsoft Academic Search

Automatic target detection in satellite images remains a challenging problem. The main difficulties lie in the cooccurrence of variations of target type, pose, and size in huge satellite image. In this paper, we propose a new airplane detection approach based on visual saliency computation and symmetry detection. The advantages are twofold. First, saliency and symmetry detection perform stably in obtaining

Wei Li; Shiming Xiang; Haibo Wang; Chunhong Pan

2011-01-01

124

Multispectral inverse problems in satellite image processing  

Microsoft Academic Search

Satellite imaging is nowadays one of the main sources of geophysical and environmental information. It is, therefore, extremely important to be able to solve the corresponding inverse problem,: reconstruct the actual geophysics- or environmental-related image from the observed noisy data. Traditional image reconstruction techniques have been developed for the case when we have a single observed image. This case corresponds

Scott A. Starks; Vladik Kreinovich

1998-01-01

125

Multiscale Change Detection in Multitemporal Satellite Images  

Microsoft Academic Search

In this letter, we propose a novel technique for unsupervised change detection in multitemporal satellite images. The difference image which is computed from multitemporal images acquired on the same geographical area at two different time instances is decomposed using S-levels undecimated discrete wavelet transform (UDWT). For each pixel in the difference image, a multiscale feature vector is extracted using the

Turgay Celik

2009-01-01

126

Satellite image classification using convolutional learning  

NASA Astrophysics Data System (ADS)

A satellite image classification method using Convolutional Neural Network (CNN) architecture is proposed in this paper. As a special case of deep learning, CNN classifies classes of images without any feature extraction step while other existing classification methods utilize rather complex feature extraction processes. Experiments on a set of satellite image 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.

Nguyen, Thao; Han, Jiho; Park, Dong-Chul

2013-10-01

127

Economic Time-Series Page.  

ERIC Educational Resources Information Center

Describes the Economagic Web site, a comprehensive site of free economic time-series data that can be used for research and instruction. Explains that it contains 100,000+ economic data series from sources such as the Federal Reserve Banking System, the Census Bureau, and the Department of Commerce. (CMK)

Bos, Theodore; Culver, Sarah E.

2000-01-01

128

CHEMICAL TIME-SERIES SAMPLING  

EPA Science Inventory

The rationale for chemical time-series 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...

129

Time Series Hilary Term 2002  

E-print Network

models Weak and strong stationarity, some time-domain models, analysis in the frequency domain, state, maximum-likelihood #12;tting, frequency domain 4. Some more advanced topics Multiple time series voltage (2), transitional sleep (3), active sleep - low voltage (4), active sleep - high voltage (5

130

Interactive management of time series  

Microsoft Academic Search

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 time series. 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

Carlo Bianchi; Giorgio Calzolari; Paolo Corsi

1974-01-01

131

Sequoia 2000 metadata schema for satellite images  

Microsoft Academic Search

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 satellite images. We examine how satellite 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

Jean T. Anderson; Michael Stonebraker

1994-01-01

132

GNSS Network time series analysis  

NASA Astrophysics Data System (ADS)

Time series of GNSS station results of both the EUPOS®-Riga and LatPos networks have been developed at the Institute of Geodesy and Geoinformation (University of Latvia) using Bernese v.5.0 software. The base stations were selected among the EPN and IGS stations in surroundings of Latvia at the distances up to 700 km. The results of time series are analysed and coordinate velocity vectors have been determined. The background of the map of tectonic faults helps to interpret the GNSS station coordinate velocity vector behaviour in proper environment. The outlying situations recognized. The question still aroused on the nature of the some of outlying situations. The dependence from various influences has been tested.

Normand, M.; Balodis, J.; Janpaule, I.; Haritonova, D.

2012-12-01

133

Cloudsat Satellite Images of Amanda  

NASA Video Gallery

NASA's CloudSat satellite flew over Hurricane Amanda on May 25, at 5 p.m. EDT and saw a deep area of moderate to heavy-moderate precipitation below the freezing level (where precipitation changes f...

134

Entropy of electromyography time series  

NASA Astrophysics Data System (ADS)

A nonlinear analysis based on Renyi entropy is applied to electromyography (EMG) time series from back muscles. The time dependence of the entropy of the EMG signal exhibits a crossover from a subdiffusive regime at short times to a plateau at longer times. We argue that this behavior characterizes complex biological systems. The plateau value of the entropy can be used to differentiate between healthy and low back pain individuals.

Kaufman, Miron; Zurcher, Ulrich; Sung, Paul S.

2007-12-01

135

Automatic registration of satellite images  

Microsoft Academic Search

Image registration is one of the basic image processing operations in remote sensing. With the increase in the number of images collected every day from different sensors, automated registration of multi-sensor\\/multi-spectral images has become an important issue. A wide range of registration techniques has been developed for many different types of applications and data. Given the diversity of the data,

LEILA M. G. FONSECA; MAX H. M. COSTA

1997-01-01

136

Image sets for satellite image processing systems  

Microsoft Academic Search

The development of novel image processing algorithms requires a diverse and relevant set of training images to ensure the general applicability of such algorithms for their required tasks. Images must be appropriately chosen for the algorithm's intended applications. Image processing algorithms often employ the discrete wavelet transform (DWT) algorithm to provide efficient compression and near-perfect reconstruction of image data. Defense

Michael R. Peterson; Toby Horner; Asael Temple

2011-01-01

137

Performance assessment of fire-sat monitoring system based on satellite time series for fire danger estimation : the experience of the pre-operative application in the Basilicata Region (Italy)  

NASA Astrophysics Data System (ADS)

This paper presents the results we obtained in the context of the FIRE-SAT project during the 2012 operative application of the satellite based tools for fire monitoring. FIRE_SAT project has been funded by the Civil Protection of the Basilicata Region in order to set up a low cost methodology for fire danger monitoring and fire effect estimation based on satellite Earth Observation techniques. To this aim, NASA Moderate Resolution Imaging Spectroradiometer (MODIS), ASTER, Landsat TM data were used. Novel data processing techniques have been developed by researchers of the ARGON Laboratory of the CNR-IMAA for the operative monitoring of fire. In this paper we only focus on the danger estimation model which has been fruitfully used since 2008 to 2012 as an reliable operative tool to support and optimize fire fighting strategies from the alert to the management of resources including fire attacks. The daily updating of fire danger is carried out using satellite MODIS images selected for their spectral capability and availability free of charge from NASA web site. This makes these data sets very suitable for an effective systematic (daily) and sustainable low-cost monitoring of large areas. The preoperative use of the integrated model, pointed out that the system properly monitor spatial and temporal variations of fire susceptibility and provide useful information of both fire severity and post fire regeneration capability.

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

2013-04-01

138

Introduction to Time Series Analysis  

NASA Technical Reports Server (NTRS)

The field of time series analysis is explored from its logical foundations to the most modern data analysis techniques. The presentation is developed, as far as possible, for continuous data, so that the inevitable use of discrete mathematics is postponed until the reader has gained some familiarity with the concepts. The monograph seeks to provide the reader with both the theoretical overview and the practical details necessary to correctly apply the full range of these powerful techniques. In addition, the last chapter introduces many specialized areas where research is currently in progress.

Hardin, J. C.

1986-01-01

139

Measuring Earthquakes from Optical Satellite Images  

Microsoft Academic Search

Syst me pour l Observation de la Terre images are used to map ground displacements induced by earthquakes. Deformations (offsets) induced by stereoscopic effect and roll, pitch, and yaw of satellite and detector artifacts are estimated and compensated. Images are then resampled in a cartographic projection with a low-bias interpolator. A subpixel correlator in the Fourier domain provides two-dimensional offset

Nadége van Puymbroeck; Rémi Michel; Renaud Binet; Jean-Philippe Avouac; Jean Taboury

2000-01-01

140

MPP: a supersystem for satellite image processing  

Microsoft Academic Search

In 1971 NASA Goddard Space Flight Center initiated a program to develop high-speed image processing systems. These systems use thousands of processing elements (PE's) operating simultaneously to achieve their speed (massive parallelism). A typical satellite image contains millions of picture elements (pixels) that can generally be processed in parallel. In 1979 a contract was awarded to construct a massively parallel

Kenneth E. Batcher

1982-01-01

141

Removal of impulse bursts in satellite images  

Microsoft Academic Search

Characteristics of impulse bursts in satellite images are analyzed and methods for burst removal are considered. Artificial compact burst model is proposed and test images are created. An advanced multipass algorithm for the detection and removal of compact bursts in the presence of both additive and multiplicative noise is proposed. The efficiency of the algorithm is evaluated quantitatively using the

O. V. Tsymbal; V. V. Lukin; P. T. Koivisto; V. P. Melnik

2003-01-01

142

GNSS Network Time Series Analysis  

NASA Astrophysics Data System (ADS)

Time series of GNSS station results of both the EUPOS®-RIGA and LATPOS networks has been developed at the Institute of Geodesy and Geoinformation (University of Latvia) using Bernese v.5.0 software. The base stations were selected among the EPN and IGS stations in surroundings of Latvia. In various day solutions the base station selection has been miscellaneous. Most frequently 5 - 8 base stations were selected from a set of stations {BOR1, JOEN, JOZE, MDVJ, METS, POLV, PULK, RIGA, TORA, VAAS, VISO, VLNS}. The rejection of "bad base stations" was performed by Bernese software depending on the quality of proper station data in proper day. This caused a reason of miscellaneous base station selection in various days. The results of time series are analysed. The question aroused on the nature of some outlying situations. The seasonal effect of the behaviour of the network has been identified when distance and elevation changes between stations has been analysed. The dependence from various influences has been recognised.

Balodis, J.; Janpaule, I.; Haritonova, D.; Normand, M.; Silabriedis, G.; Zarinjsh, A.; Zvirgzds, J.

2012-04-01

143

Albedo Pattern Recognition and Time-Series Analyses in Malaysia  

NASA Astrophysics Data System (ADS)

Pattern recognition and time-series analyses will enable one to evaluate and generate predictions of specific phenomena. The albedo pattern and time-series analyses are very much useful especially in relation to climate condition monitoring. This study is conducted to seek for Malaysia albedo pattern changes. The pattern recognition and changes will be useful for variety of environmental and climate monitoring researches such as carbon budgeting and aerosol mapping. The 10 years (2000-2009) MODIS satellite images were used for the analyses and interpretation. These images were being processed using ERDAS Imagine remote sensing software, ArcGIS 9.3, the 6S code for atmospherical calibration and several MODIS tools (MRT, HDF2GIS, Albedo tools). There are several methods for time-series analyses were explored, this paper demonstrates trends and seasonal time-series analyses using converted HDF format MODIS MCD43A3 albedo land product. The results revealed significance changes of albedo percentages over the past 10 years and the pattern with regards to Malaysia's nebulosity index (NI) and aerosol optical depth (AOD). There is noticeable trend can be identified with regards to its maximum and minimum value of the albedo. The rise and fall of the line graph show a similar trend with regards to its daily observation. The different can be identified in term of the value or percentage of rises and falls of albedo. Thus, it can be concludes that the temporal behavior of land surface albedo in Malaysia have a uniform behaviours and effects with regards to the local monsoons. However, although the average albedo shows linear trend with nebulosity index, the pattern changes of albedo with respects to the nebulosity index indicates that there are external factors that implicates the albedo values, as the sky conditions and its diffusion plotted does not have uniform trend over the years, especially when the trend of 5 years interval is examined, 2000 shows high negative linear trend relationship (R2 = 0.8017), while in 2005 the R2 is 0.4428 of positive linear trend relationship and in 2009 its negative relationship has remarkably change when the R2 is 0.9663 according to the second order polynomial trend line.

Salleh, S. A.; Abd Latif, Z.; Mohd, W. M. N. Wan; Chan, A.

2012-07-01

144

High Resolution Satellite Image Orientation Models  

Microsoft Academic Search

\\u000a A few years ago high resolution satellite imagery became available to a limited number of government and defense agencies\\u000a that managed such imagery with highly sophisticated software and hardware tools. Such images became available to civil users\\u000a in 1999 with the launch of Ikonos, the first civil satellite offering a spatial resolution of 1 m. Since then other high resolution

Mattia Crespi; Francesca Fratarcangeli; Francesca Giannone; Francesca Pieralice

145

Algorithm for Compressing Time-Series Data  

NASA Technical Reports Server (NTRS)

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

Hawkins, S. Edward, III; Darlington, Edward Hugo

2012-01-01

146

Aerial photographs and satellite images  

USGS Publications Warehouse

Because photographs and images taken from the air or from space are acquired without direct contact with the ground, they are referred to as remotely sensed images. The U.S. Geological Survey (USGS) has used remote sensing from the early years of the 20th century to support earth science studies and for mapping purposes.

U.S. Geological Survey

1995-01-01

147

Aperiodic time series in astronomy.  

NASA Astrophysics Data System (ADS)

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 time series 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.

Krolik, J. H.

148

Auroral imaging from a spinning satellite.  

PubMed

For optimizing in situ particle and field measurements, auroral research satellites are best operated in a spinning mode. Simultaneous imaging of the optical aurora from such satellites 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 image blur often occurs due to the misalignments between the actual and the nominal spin axes of the satellite. 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 satellite while a despinning flat 45° mirror directs the field of view toward the spacecraft nadir. The resultant image will appear to rotate in the frame of reference of the detector in the camera. In our scheme the images are exposed rapidly and a derotation algorithm is applied to the coordinates of each pixel in real time before the images 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 satellite spin cycles. The system was simulated including a 1.8° misalignment between the nominal satellite 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 images and correct for the axes misalignment, allowing the observation of the aurora at full resolution and with continuous coverage. PMID:21280811

Mende, Stephen B

2011-01-01

149

Northern Everglades, Florida, satellite image map  

USGS Publications Warehouse

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

Thomas, Jean-Claude; Jones, John W.

2002-01-01

150

South Florida Everglades: satellite image map  

USGS Publications Warehouse

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

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

2001-01-01

151

Satellite Image Deconvolution Using Complex Wavelet Packets  

Microsoft Academic Search

The deconvolution of blurred and noisy satellite im- ages is an ill-posed inverse problem. Donoho has pro- posed to deconvolve the image without regularization and to denoise the result in a wavelet basis by thresh- olding the transformed coefficients. We have developed a new filtering method, con- sisting of using a complex wavelet packet basis. Herein, the thresholding functions associated

André Jalobeanu; Laure Blanc-féraud; Josiane Zerubia

2000-01-01

152

Geometric calibration of ERS satellite SAR images  

Microsoft Academic Search

Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed and calibrated by using the European Space Agency (ESA) transponders at Flevoland. The resulting accuracy of the slant range

Johan Jacob Mohr; Søren Nørvang Madsen

2001-01-01

153

Satellite image processing and air pollution detection  

Microsoft Academic Search

Environmental sensing is closely related to digital processing of observed signals and images. The paper is devoted to the analysis of mathematical methods allowing for detection of concentration of aerosol particles observed at ground measuring stations and by satellites. The first part of the contribution presents basic methods of two-dimensional interpolation allowing for the estimation of the observed variables over

A. Prochazka; M. Kolinova; J. Fiala; P. Hampl; K. Hlavaty

2000-01-01

154

Offshore wind resource assessment through satellite images  

E-print Network

, Morten Nielsen, Sara Pryor Wind Energy Department European Geosciences Union (EGU) Nice, France, 25 angle Coefficients depend on radar incidence angle and wind speed OCEAN SEA BOTTOM CMOD4 Stoffelen et al1 Slide no. 4 Offshore wind resource assessment through satellite images Charlotte Bay Hasager

155

Multivariate Time Series Similarity Searching  

PubMed Central

Multivariate time series (MTS) datasets are very common in various financial, multimedia, and hydrological fields. In this paper, a dimension-combination method is proposed to search similar sequences for MTS. Firstly, the similarity of single-dimension series is calculated; then the overall similarity of the MTS is obtained by synthesizing each of the single-dimension similarity based on weighted BORDA voting method. The dimension-combination method could use the existing similarity searching method. Several experiments, which used the classification accuracy as a measure, were performed on six datasets from the UCI KDD Archive to validate the method. The results show the advantage of the approach compared to the traditional similarity measures, such as Euclidean distance (ED), cynamic time warping (DTW), point distribution (PD), PCA similarity factor (SPCA), and extended Frobenius norm (Eros), for MTS datasets in some ways. Our experiments also demonstrate that no measure can fit all datasets, and the proposed measure is a choice for similarity searches. PMID:24895665

Wang, Jimin; Zhu, Yuelong; Li, Shijin; Wan, Dingsheng; Zhang, Pengcheng

2014-01-01

156

4-D display of satellite cloud images  

NASA Technical Reports Server (NTRS)

A technique has been developed to display GOES satellite cloud images in perspective over a topographical map. Cloud heights are estimated using temperatures from an infrared (IR) satellite image, surface temperature observations, and a climatological model of vertical temperature profiles. Cloud levels are discriminated from each other and from the ground using a pattern recognition algorithm based on the brightness variance technique of Coakley and Bretherton. The cloud regions found by the pattern recognizer are rendered in three-dimensional perspective over a topographical map by an efficient remap of the visible image. The visible shades are mixed with an artificial shade based on the geometry of the cloud-top surface, in order to enhance the texture of the cloud top.

Hibbard, William L.

1987-01-01

157

A neuromorphic approach to satellite image understanding  

NASA Astrophysics Data System (ADS)

Remote sensing satellite imagery provides high altitude, top viewing aspects of large geographic regions and as such the depicted features are not always easily recognizable. Nevertheless, geoscientists familiar to remote sensing data, gradually gain experience and enhance their satellite image interpretation skills. The aim of this study is to devise a novel computational neuro-centered classification approach for feature extraction and image understanding. Object recognition through image processing practices is related to a series of known image/feature based attributes including size, shape, association, texture, etc. The objective of the study is to weight these attribute values towards the enhancement of feature recognition. The key cognitive experimentation concern is to define the point when a user recognizes a feature as it varies in terms of the above mentioned attributes and relate it with their corresponding values. Towards this end, we have set up an experimentation methodology that utilizes cognitive data from brain signals (EEG) and eye gaze data (eye tracking) of subjects watching satellite images of varying attributes; this allows the collection of rich real-time data that will be used for designing the image classifier. Since the data are already labeled by users (using an input device) a first step is to compare the performance of various machine-learning algorithms on the collected data. On the long-run, the aim of this work would be to investigate the automatic classification of unlabeled images (unsupervised learning) based purely on image attributes. The outcome of this innovative process is twofold: First, in an abundance of remote sensing image datasets we may define the essential image specifications in order to collect the appropriate data for each application and improve processing and resource efficiency. E.g. for a fault extraction application in a given scale a medium resolution 4-band image, may be more effective than costly, multispectral, very high resolution imagery. Second, we attempt to relate the experienced against the non-experienced user understanding in order to indirectly assess the possible limits of purely computational systems. In other words, obtain the conceptual limits of computation vs human cognition concerning feature recognition from satellite imagery. Preliminary results of this pilot study show relations between collected data and differentiation of the image attributes which indicates that our methodology can lead to important results.

Partsinevelos, Panagiotis; Perakakis, Manolis

2014-05-01

158

Antarctica: measuring glacier velocity from satellite images  

SciTech Connect

Many Landsat images of Antarctica show distinctive flow and crevasse features in the floating part of ice streams and outlet glaciers immediately below their grounding zones. Some of the features, which move with the glacier or ice stream, remain visible over many years and thus allow time-lapse measurements of ice velocities. Measurements taken from Landsat images of features on Byrd Glacier agree well with detailed ground and aerial observations. The satellite-image technique thus offers a rapid and cost-effective method of obtaining average velocities, to a first order of accuracy, of many ice streams and outlet glaciers near their termini.

Lucchitta, B.K.; Ferguson, H.M.

1986-11-28

159

Antarctica: Measuring glacier velocity from satellite images  

USGS Publications Warehouse

Many Landsat images of Antarctica show distinctive flow and crevasse features in the floating part of ice streams and outlet glaciers immediately below their grounding zones. Some of the features, which move with the glacier or ice stream, remain visible over many years and thus allow time-lapse measurements of ice velocities. Measurements taken from Landsat images of features on Byrd Glacier agree well with detailed ground and aerial observations. The satellite-image technique thus offers a rapid and cost-effective method of obtaining average velocities, to a first order of accuracy, of many ice streams and outlet glaciers near their termini.

Lucchitta, B. K.; Ferguson, H. M.

1986-01-01

160

Efficient spectral estimation for time series with intermittent gaps  

Microsoft Academic Search

Data from magnetic satellites like CHAMP, Ørsted, and Swarm can be used to study electromagnetic induction in Earth's mantle. Time series of internal and external spherical harmonic coefficients (usually those associated with the predominantly dipolar structure of ring current variations) are used to determine Earth's electromagnetic response as a function of frequency of the external variations. Inversion of this response

L. T. Smith; C. Constable

2009-01-01

161

Adaptive median filtering for preprocessing of time series measurements  

NASA Technical Reports Server (NTRS)

A median (L1-norm) filtering program using polynomials was developed. This program was used in automatic recycling data screening. Additionally, a special adaptive program to work with asymmetric distributions was developed. Examples of adaptive median filtering of satellite laser range observations and TV satellite time measurements are given. The program proved to be versatile and time saving in data screening of time series measurements.

Paunonen, Matti

1993-01-01

162

An Introduction to Wavelet Analysis with Application to Water Quality Time Series  

E-print Network

An Introduction to Wavelet Analysis with Application to Water Quality Time Series Don Percival!!!) · wavelets can help us understand - time series (i.e., observations collected over time) - images 1 Overview: II · wavelets capable of describing how - time series evolve over time on a given scale - images

Percival, Don

163

A review of subsequence time series clustering.  

PubMed

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332

Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

2014-01-01

164

Contented-Based Satellite Cloud Image Processing and Information Retrieval  

Microsoft Academic Search

Satellite cloud image is a kind of useful image which includes abundant information, for acquired this information, the image\\u000a processing and character extraction method adapt to satellite cloud image has to be used. Content-based satellite cloud image\\u000a processing and information retrieval (CBIPIR) is a very important problem in image processing and analysis field. The basic\\u000a character, like color, texture, edge

Yanling Hao; Wei Shangguan; Yi Zhu; Yanhong Tang

2007-01-01

165

A satellite image watermarkig scheme based on perspective distance  

Microsoft Academic Search

This paper proposes adaptive watermarking scheme depending on perspective distance using hue histogram in order to protect the copyrights of satellite image. The proposed scheme uses the different color distribution and the edge component depending on the overlooking distance when acquiring satellite images. It analyzes the hue histogram of acquired satellite images to determine the perspective distance, uses the edge

Jun-Hee Kim; Suk-Hwan Lee; Ki-Ryong Kown

2011-01-01

166

Estimating seasonal evapotranspiration from temporal satellite images  

USGS Publications Warehouse

Estimating seasonal evapotranspiration (ET) has many applications in water resources planning and management, including hydrological and ecological modeling. Availability of satellite remote sensing images is limited due to repeat cycle of satellite 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 images. 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 satellite overpass using eight Landsat images 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.

Singh, Ramesh K.; Liu, Shuguang; Tieszen, Larry L.; Suyker, Andrew E.; Verma, Shashi B.

2012-01-01

167

Image-Based Attitude Control of a Remote Sensing Satellite  

Microsoft Academic Search

This paper deals with the image-based control of a satellite for remote sensing. Approach is demonstrated by simulation where\\u000a the position of the satellite is obtained with the Simplified General Perturbations Version 3 model and its orientation by\\u000a simulating its dynamic and kinematic models. For a known position and orientation of the satellite the images are obtained\\u000a using the satellite’s

Gregor Klan?ar; Sašo Blaži?; Drago Matko

168

Biorthogonal wavelets applied to meterological satellite images (METEOSAT) image compressing  

Microsoft Academic Search

In this paper we develop fast numerical algorithms for representations of periodic functions in biorthogonal multiresolution analyses in two dimensions. We show that in the Fourier domain the decomposition and reconstruction algorithms have a matrix representation in terms of permutations and block diagonal matrices. We present some illustrative examples using biorthogonal spline wavelets applied to meteorological satellite images (METEOSAT) compression.

Margarete O. Domingues; Sonia M. Gomes; Elsa Cortina

1995-01-01

169

Pattern Recognition and Image Processing of Infrared Astronomical Satellite Images  

Microsoft Academic Search

The Infrared Astronomical Satellite (IRAS) images 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 \\

Lun Xiong He

1996-01-01

170

Absolute image registration for geosynchronous satellites  

NASA Technical Reports Server (NTRS)

A procedure for the absolute registration of earth images acquired by cameras on geosynchronous satellites is described. A conventional least squares process is used to estimate navigational parameters and camera pointing biases from observed minus computed landmark line and element numbers. These estimated parameters along with orbit and attitude dynamic models are used to register images, employing an automated grey-level correlation technique, inside the span represented by the landmark data. Experimental results obtained from processing the SMS-2 observation data base covering May 2, 1979 through May 20, 1979 show registration accuracies with a standard deviation of less than two pixels if the registration is within the landmark data span. It is also found that accurate registration can be expected for images obtained up to 48 hours outside of the landmark data span.

Nankervis, R.; Koch, D.; Sielski, H.; Hall, D.

1980-01-01

171

Novel aircraft type recognition with learning capabilities in satellite images  

Microsoft Academic Search

The collection of satellite images is not constrained by time and can be captured day and night. It is unlike the images captured by aircrafts which are heavily constrained by weather conditions and environmental factors to secure useful images. Recently, satellite images have been widely applied in many fields, such as resource mining, pollution monitoring, etc. In this paper, we

Jun-wei Hsieh; Jian-ming Chen; Chi-hung Chuang; Kuo-chin Fan

2004-01-01

172

Accurate mapping of forest types using dense seasonal Landsat time-series  

NASA Astrophysics Data System (ADS)

An accurate map of forest types is important for proper usage and management of forestry resources. Medium resolution satellite images (e.g., Landsat) have been widely used for forest type mapping because they are able to cover large areas more efficiently than the traditional forest inventory. However, the results of a detailed forest type classification based on these images are still not satisfactory. To improve forest mapping accuracy, this study proposed an operational method to get detailed forest types from dense Landsat time-series incorporating with or without topographic information provided by DEM. This method integrated a feature selection and a training-sample-adding procedure into a hierarchical classification framework. The proposed method has been tested in Vinton County of southeastern Ohio. The detailed forest types include pine forest, oak forest, and mixed-mesophytic forest. The proposed method was trained and validated using ground samples from field plots. The three forest types were classified with an overall accuracy of 90.52% using dense Landsat time-series, while topographic information can only slightly improve the accuracy to 92.63%. Moreover, the comparison between results of using Landsat time-series and a single image reveals that time-series data can largely improve the accuracy of forest type mapping, indicating the importance of phenological information contained in multi-seasonal images for discriminating different forest types. Thanks to zero cost of all input remotely sensed datasets and ease of implementation, this approach has the potential to be applied to map forest types at regional or global scales.

Zhu, Xiaolin; Liu, Desheng

2014-10-01

173

Spatial Cloud Detection and Retrieval System for Satellite Images  

Microsoft Academic Search

In last the decade we witnessed a large increase in data generated by earth observing satellites. Hence, intelligent processing of the huge amount of data received by hundreds of earth receiving stations, with specific satellite image oriented approaches, presents itself as a pressing need. One of the most important steps in earlier stages of satellite image processing is cloud detection.

Noureldin Laban; Ayman Nasr; Alf Maskan; Motaz ElSaban; Hoda Onsi

2012-01-01

174

Graph-based ship extraction scheme for optical satellite image  

Microsoft Academic Search

Automatic detection and recognition of ship in satellite images is very important and has a wide array of applications. This paper concentrates on optical satellite sensor, which provides an important approach for ship monitoring. Graph-based fore\\/background segmentation scheme is used to extract ship candidant from optical satellite image chip after the detection step, from course to fine. Shadows on the

Feng Chen; Wenxian Yu; Xingzhao Liu; Kaizhi Wang; Lin Gong; Wentao Lv

2011-01-01

175

An Introduction to Wavelet Analysis with Application to Water Quality Time Series  

E-print Network

An Introduction to Wavelet Analysis with Application to Water Quality Time Series Don Percival of material!!!) · wavelets can help us understand - time series (i.e., observations collected over time) - images 1 #12;Overview: II · wavelets capable of describing how - time series evolve over time on a given

Percival, Don

176

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

PubMed

As compared with terrestrial circuits, communication satellites possess superior characteristics such as wide area coverage, broadcasting functions, high capacity, and resistance to disasters. Utilizing the narrow band channel (64 kbps) of the stationary communication satellite JCSAT1 located at an altitude of 36,000 km above the equator, we investigated satelliterelayed dynamic medical images transmitted by video signals, using hepatic ultrasonography as a model. We conclude that the "variable playing speed transmission scheme" proposed by us is effective for the transmission of dynamic images in the narrow band channel. This promises to permit diverse utilization and applications for purposes such as the transmission of other types of ultrasonic images as well as remotely directed medical diagnosis and treatment. PMID:8916265

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

1996-01-01

177

Macintosh Program performs time-series analysis  

Microsoft Academic Search

A Macintosh computer program that can perform many time-series analysis procedures is now available on the Internet free of charge. Although AnalySeries was originally designed for paleoclimatic time series, 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

Didier Paillard; Laurent Labeyrie; Pascal Yiou

1996-01-01

178

Time Series Analysis in Intensive Care Medicine  

Microsoft Academic Search

Objectives: Time series analysis techniques facilitate statistical analysis of variables in the course of time. Continuous monitoring of the critically ill in intensive care offers an especially wide range of applications. In an open clinical study time series analysis was applied to the monitoring of lab vari- ables after liver surgery, and to support clinical decision making in the treatment

Chirurgische Klinik

179

Grouping Multivariate Time Series: A Case Study  

Microsoft Academic Search

We present a case study to demonstrate a process for grouping massive multivariate time series based on nonpara- metric statistical summaries aided by information visualization. We want a method that allows us to quickly find approximate groups in time series, both to identify typical aggregate behaviors and to find aberrant outliers. We use simple statistical summaries to capture the temporal

Tamraparni Dasu; Deborah F. Swayne; David Poole

180

Time series analysis of lava flux  

Microsoft Academic Search

We have applied time series analytical techniques to the flux of lava from an extrusive eruption. Tilt data acting as a proxy for flux are used in a case study of the May–August 1997 period of the eruption at Soufrière Hills Volcano, Montserrat. We justify the use of such a proxy by simple calibratory arguments. Three techniques of time series

H. M. Odbert; G. Wadge

2009-01-01

181

Time series analysis of geological data  

Microsoft Academic Search

Time series analysis is being applied to the following geological data: tree rings, Sr isotope data for Phanerozoic seawater, and the El Niño phenomenon. First the data are treated by ARIMA models that enable, for stationary time series, to construct a stochastic model that can be utilized to forecast future values of the series. The subsequent R\\/S analysis allows detection

G. Cimino; G. Del Duce; L. K. Kadonaga; G. Rotundo; A. Sisani; G. Stabile; B. Tirozzi; M. Whiticar

1999-01-01

182

Time Series Analysis in Intensive Care Medicine  

Microsoft Academic Search

Objectives: Time series analysis techniques facilitate statistical analysis of variables in the course of time. Continuous monitoring of the critically ill in intensive care offers an especially wide range of applications. In an open clinical study time series analysis was applied to the monitoring of lab vari- ables after liver surgery, and to support clinical decision making in the treatment

Michael Imhoff; Marcus Bauer; Ursula Gather

1997-01-01

183

Heterogeneous Time Series Learning for Crisis Monitoring  

Microsoft Academic Search

A very important application of time series learning is online diagnosis, or monitoring, to detect and classify hazardous conditions in a physical system. Examples of crisis monitoring in the industrial, military, agricultural and environmental sciences are numerous. This paper first defines heterogeneous time series, those containing different types of embedded, statistical patterns. Next, it surveys basic techniques for acquiring several

William H. Hsu; Nathan D. Gettings; Victoria E. Lease; Yu Pan; David C. Wilkins

184

Innovations Algorithm for Periodically Stationary Time Series  

Microsoft Academic Search

Abstract Periodic ARMA, or PARMA, time series are used to model periodically stationary time series. In this paper we develop the innovations algorithm for periodically stationary processes. We then show how the algorithm can be used to obtain parameter estimates for the PARMA model. These estimates are proven to be weakly consistent for PARMA processes whose underlying noise sequence has

Paul L. Anderson; Mark M. Meerschaert; Aldo V. Vecchia

185

Innovations algorithm for periodically stationary time series  

Microsoft Academic Search

Periodic ARMA, or PARMA, time series are used to model periodically stationary time series. In this paper we develop the innovations algorithm for periodically stationary processes. We then show how the algorithm can be used to obtain parameter estimates for the PARMA model. These estimates are proven to be weakly consistent for PARMA processes whose underlying noise sequence has either

Paul L. Anderson; Mark M. Meerschaert; Aldo V. Vecchia

1999-01-01

186

Intelligent techniques for forecasting multiple time series  

E-print Network

Intelligent techniques for forecasting multiple time series in real-world systems Neal Wagner. Originality/value ­ This paper provides a case study of a real-world system that employs a novel hybrid model of many real-world systems. Some systems require the forecasting of a very large portfolio of time series

Michalewicz, Zbigniew

187

ARMA Model identification of hydrologic time series  

Microsoft Academic Search

In recent years, ARMA models have become popular for modeling geophysical time series in general and hydrologic time series 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

J. D. Salas; J. T. B. Obeysekera

1982-01-01

188

Nonlinear dynamical models from time series  

E-print Network

We present an optimization process to estimate parameters in systems of ordinary differential equations from chaotic time series. The optimization technique is based on a variational approach, and numerical studies on noisy time series demonstrate that it is very robust and appropriate to reduce the complexity of the model. The proposed process also allows to discard the parameters with scanty influence on the dynamic.

Jose-Maria Fullana

2014-07-30

189

Trend assessment of water quality time series  

Microsoft Academic Search

A general methodology is described for identifying and statistically modeling trends which may be contained in water quality time series. A range of useful exploratory data analysis tools are suggested for discovering important patterns and statistical characteristics of the data such as trends caused by external interventions. To estimate the entries in an evenly spaced time series when data are

A. Ian McLeod; Keith W. Hipel; Fernando Comancho

1983-01-01

190

Web quantlets for time series analysis  

Microsoft Academic Search

New and advanced methods for nonlinear time series analysis are in general not available in standard software packages. Their implementation requires substantial time, computing power as well as programming skills. In time series analysis such a scenario is given by a recently suggested nonparametric lag selection procedure for univariate nonlinear autoregressive models which is based on the Cor- rected Asymptotic

W. Härdle; Torsten Kleinow; Rolf Tschernig

2000-01-01

191

Web Quantlets for Time Series Analysis  

Microsoft Academic Search

New and advanced methods for nonlinear time series analysis are in general not available in standard software packages. Their implementation requires substantial time, computing power as well as programming skills. In time series analysis such a scenario is given by a recently suggested nonparametric lag selection procedure for univariate nonlinear autoregressive models which is based on the Corrected Asymptotic Final

Wolfgang Härdle; Torsten Kleinow; Rolf Tschernig

2001-01-01

192

INNOVATIVE SATELLITE IMAGE MAP OF R.ALKHABRTA AREA, SAUDI ARABIA USING HIGH RESOLUTION IMAGE  

Microsoft Academic Search

ABSTRACT: Satellite remote sensing can provide a variety of useful data for various type of research. Satellite image map,is one of the products that aim to promote remote sensing. In this study, a high resolution satellite image was used to create a high resolution satellite image map over AlKhabra, Saudi Arabia. The objective of this project is to produce a

Sultan AlSultan; K. Abdullah; N. Mohd

2002-01-01

193

Star sightings by satellite for image navigation  

NASA Technical Reports Server (NTRS)

Stars are sensed by one or more instruments (1, 2) on board a three-axis stabilized satellite, for purposes of assisting in image navigation. A star acquistion computer (64), which may be located on the earth, commands the instrument mirror (33, 32) to slew just outside the limb of the earth or other celestial body around which the satellite is orbiting, to look for stars that have been cataloged in a star map stored within the computer (64). The instrument (1, 2) is commanded to dwell for a period of time equal to a star search window time, plus the maximum time the instrument (1, 2) takes to complete a current scan, plus the maximum time it takes for the mirror (33, 32) to slew to the star. When the satellite is first placed in orbit, and following first stationkeeping and eclipse, a special operation is performed in which the star-seeking instrument (1, 2) FOV is broadened. The elevation dimension can be broadened by performing repetitive star seeks; the azimuth dimension can be broadened by lengthening the commanded dwell times.

Kamel, Ahmed A. (Inventor); Ekman, Donald E. (Inventor); Savides, John (Inventor); Zwirn, Gerald J. (Inventor)

1988-01-01

194

Estimating GATE rainfall with geosynchronous satellite images  

NASA Technical Reports Server (NTRS)

A method of estimating GATE rainfall from either visible or infrared images of geosynchronous satellites is described. Rain is estimated from cumulonimbus cloud area by the equation R = a sub 0 A + a sub 1 dA/dt, where R is volumetric rainfall, A cloud area, t time, and a sub 0 and a sub 1 are constants. Rainfall, calculated from 5.3 cm ship radar, and cloud area are measured from clouds in the tropical North Atlantic. The constants a sub 0 and a sub 1 are fit to these measurements by the least-squares method. Hourly estimates by the infrared version of this technique correlate well (correlation coefficient of 0.84) with rain totals derived from composited radar for an area of 100,000 sq km. The accuracy of this method is described and compared to that of another technique using geosynchronous satellite images. It is concluded that this technique provides useful estimates of tropical oceanic rainfall on a convective scale.

Stout, J. E.; Martin, D. W.; Sikdar, D. N.

1979-01-01

195

Dynamics extraction in multivariate biomedical time series.  

PubMed

A nonlinear analysis of the underlying dynamics of a biomedical time series is proposed by means of a multi-dimensional testing of nonlinear Markovian hypotheses in the observed time series. The observed dynamics of the original N-dimensional biomedical time series is tested against a hierarchy of null hypotheses corresponding to N-dimensional nonlinear Markov processes of increasing order, whose conditional probability densities are estimated using neural networks. For each of the N time series, a measure based on higher order cumulants quantifies the independence between the past of the N-dimensional time series, and its value r steps ahead. This cumulant-based measure is used as a discriminating statistic for testing the null hypotheses. Experiments performed on artificial and real world examples, including autoregressive models, noisy chaos, and nonchaotic nonlinear processes, show the effectiveness of the proposed approach in modeling multivariate systems, predicting multidimensional time series, and characterizing the structure of biological systems. Electroencephalogram (EEG) time series and heart rate variability trends are tested as biomedical signal examples. PMID:9742674

Silipo, R; Deco, G; Vergassola, R; Bartsch, H

1998-07-01

196

Long sequence time series analysis of Moroccan ecosystem dynamics  

NASA Astrophysics Data System (ADS)

The principal technique used in this investigation was a Principal Components-based time series analysis (TSA). Using a set of 240 monthly composite multi-band AVHRR images for Morocco, a 20-year time series of monthly NDVI images 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 satellites. 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.

Marzouk, Abdelkrim

197

Automatic identification of oil spills on satellite images  

Microsoft Academic Search

Abstract A fully automated,system for the identification of possible oil spills present on Synthetic Aperture Radar (SAR) satellite images based on artificial intelligence fuzzy logic has been developed. Oil spills are recognized,by experts as dark patterns of characteristic shape, in particular context. The system analyzes the satellite images and assigns the probability of a dark image shape to be an

Iphigenia Keramitsoglou; Constantinos Cartalis; Chris T. Kiranoudis

2006-01-01

198

Distributed Geo-rectification of Satellite Images using Grid Computing  

E-print Network

with a defined array of coordinates [25]. Figure 1 illustrates the geo-rectification process. A satellite image1 Distributed Geo-rectification of Satellite Images using Grid Computing Y.M. Teo* , S.C. Tay** , and J.P. Gozali* * Department of Computer Science ** Centre for Remote Imaging, Sensing and Processing

Teo, Yong-Meng

199

Change Detection in Satellite Images Using a Genetic Algorithm Approach  

Microsoft Academic Search

In this letter, we propose a novel method for unsupervised change detection in multitemporal satellite images by minimizing a cost function using a genetic algorithm (GA). The difference image computed from the multitemporal satellite images is partitioned into two distinct regions, namely, ??changed?? and ??unchanged,?? according to the binary change detection mask realization from the GA. For each region, the

Turgay Celik

2010-01-01

200

Bayesian Time Series: Models and Computations for the Analysis of Time Series in the Physical Sciences  

Microsoft Academic Search

. This articles discusses developments in Bayesian time series modellingand analysis relevant in studies of time series in the physical and engineeringsciences. With illustrations and references, we discuss: Bayesian inferenceand computation in various state-space models, with examples in analysingquasi-periodic series; isolation and modelling of various components of error intime series; decompositions of time series into significant latent subseries; nonlineartime series

Mike West

1995-01-01

201

Time Series Classification Using Compression Distance of Recurrence Plots  

E-print Network

Time Series Classification Using Compression Distance of Recurrence Plots Diego F. Silva, Vin between recurrence plots using Campana-Keogh (CK-1) distance, a Kolmogorov complexity- based distance that uses video compression algorithms to estimate image similarity. We show that recurrence plots allied

Batista, Gustavo

202

Time Series of the Biscuit Fire with Smoke  

NSDL National Science Digital Library

This animation contains a time series of print resolution still images showing the progression of the Biscuit fire with smoke plumes in Oregon during 2002. Fire locations are represented as particles that change color as the fire ages. The Biscuit fire burned 500,000 acres of forest in Oregon and Northern California during the summer and fall of 2002.

Starr, Cindy; Justice, Chris; Sohlberg, Robert; Gunther, Fred; North, William

2003-08-04

203

Time series of a CME blasting out from the Sun  

E-print Network

#12;Time series of a CME blasting out from the Sun Composite image of the Sun in UV light with the naked eye, the Sun seems static, placid, constant. From the ground, the only notice- able variations in the Sun are its location (where will it rise and set today?) and its color (will clouds cover

Christian, Eric

204

Deriving 250m LAI time series by non-linear temporal regression  

NASA Astrophysics Data System (ADS)

The leaf area index (LAI) forms part of the 13 terrestrial essential climate variables and is key ingest to many vegetation productivity, hydrology and biogeochemistry models. LAI is modeled from satellite images including MODIS and SPOT VGT data in a consistent and operational manner that allows for time series generation. With approximately 1km spatial resolution these products are useful for global analysis but lack the necessary spatial detail for national and regional studies. This study aims at improving the spatial resolution of existing LAI data by relating their temporal course to time series of vegetation indices (VI). MODIS data are particular appropriate providing the LAI at 1km and VI at 1km and 250m spatial resolution. The study area (1100x500km) in central Mexico represents all major biomes and vegetation types of the country and a land surface heterogeneity beyond 1km cell size. Previous to model building LAI and VI time series are generated using appropriate tools (TiSeG) for filtering low-quality data and interpolation of data gaps. Plots show a good temporal correspondence between LAI and VI time series, and temporal cross-correlation indicates high coefficients with no or minor lag. For each pixel linear and non-linear regression models are built at the 1km resolution using the temporal domain and applied to 250m VI data. In addition, multiple regression models with spectral information will be tested. The resulting 250m LAI time series introduces the spatial detail of the 250m VI to the LAI and retains the high temporal consistency. To evaluate the modeled results 250m LAI time series are coarsened to 1km spatial resolution using an empirically-derived aggregation model that takes into account the MODIS-specific spatial point spread function. Error maps of the correlation coefficient and RMSE indicate regions of higher errors that correspond to specific biomes used in MODIS LAI retrieval. For instance, while the vast majority of the study site depicts mean correlation coefficients of 0.85 and an RMSE of 0.3 the mountainous regions that correspond to the evergreen broadleaf forest biome show higher errors (r=0.6, RMSE 0.7) that are also related remaining artifacts in the time series.

Colditz, R.; Llamas, R.

2012-04-01

205

Entropic Analysis of Electromyography Time Series  

NASA Astrophysics Data System (ADS)

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) time series. 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 time series with 60,000 entries. We characterize the complexity of time series by computing the Shannon entropy time dependence. The analysis of the time series 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.

Kaufman, Miron; Sung, Paul

2005-03-01

206

Nonlinear Analysis of Surface EMG Time Series  

NASA Astrophysics Data System (ADS)

Applications of nonlinear analysis of surface electromyography time series of patients with and without low back pain are presented. Limitations of the standard methods based on the power spectrum are discussed.

Zurcher, Ulrich; Kaufman, Miron; Sung, Paul

2004-04-01

207

Knowledge discovery in time series databases.  

PubMed

Adding the dimension of time to databases produces time series 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 time series data, identifying the most important predicting attributes, and extracting a set of association rules that can be used to predict the time series 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 time series: stock-market data and weather data. PMID:18244779

Last, M; Klein, Y; Kandel, A

2001-01-01

208

Digital cyphering system using chaos time series  

NASA Astrophysics Data System (ADS)

A voltage-mode CMOS looped circuit generates complex chaos time series, and it is digitized by an AD converter. The digitized time series of internal state shows an irreversible multiple complexity in the past, due to bifurcation. The multiple complexity of internal states in chaos time series is utilized as a scramble code in a digital ciphering system. A binary coded information is bit-serially converted into a corresponding scramble code. An average conversion rate of the ciphering system using 8-bit data base is 102 k bit/sec. On the other hand, the internal states in the future time series are quite deterministic, even if it has multiple internal states in the past. The scramble code can be decoded by the deterministic phenomenon.

Takakubo, Hajime; Shono, Katsufusa

1995-12-01

209

Time series change detection: Algorithms for land cover change  

NASA Astrophysics Data System (ADS)

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 satellites, 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 satellite 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 satellite images acquired on different dates. Thus, a technological solution that detects global land cover change using high temporal resolution time series 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 time series 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 satellite data sets; and (3) Spatio-temporal analysis techniques to identify the scale and scope of disturbance events.

Boriah, Shyam

210

Network analysis methods of heliorelated time series  

NASA Astrophysics Data System (ADS)

In this work, we present the diagnostics results of the similarity between different temperature paleoreconstructions using network approaches. The correlation patterns of time series are transformed into the geometry of the corresponding graph, which can be analyzed geometrically. To detect a possible nonlinear connection between climatic series and solar activity, we use networks constructed by embedding time series in the space of an appropriate dimension. Finally, we present Markov networks for climatic reconstructions and annual Wolf numbers.

Knyazeva, I. S.; Makarenko, N. G.

2012-12-01

211

A Time Series Analysis of Microarray Data  

Microsoft Academic Search

As the capture and analysis of single-time-point microar- ray expression data becomes routine, investigators are turn- ing to time-series 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 time-series behaviors observed. Although traditional clus- tering techniques have shown to

Selnur Erdal; Ozgur Ozturk; David L. Armbruster; Hakan Ferhatosmanoglu; William C. Ray

2004-01-01

212

Handling forecasting problems using fuzzy time series  

Microsoft Academic Search

In [6–9], Song et al. proposed fuzzy time-series models to deal with forecasting problems. In [10], Sullivan and Woodall reviewed the first-order time-invariant fuzzy time series model and the first-order time-variant model proposed by Song and Chissom [6–8], where the models are compared with each other and with a time-invariant Markov model using linguistic labels with probability distributions. In this

Jeng-Ren Hwang; Shyi-Ming Chen; Chia-Hoang Lee

1998-01-01

213

Scaling Behavior of Hydrologic Time Series  

NASA Astrophysics Data System (ADS)

An important area of research in hydrologic modeling is the issue of scaling of certain deterministic properties at various spatial and temporal scales. The complexity for modeling of most systems is because hydrologic processes scale nonlinearly; that is, the moments (e.g. the mean and variance) obtained at one scale may be significantly different from those obtained at a larger or smaller scale. Improvements in hydrologic modeling that include the tenants of scaling in the relevant processes would be novel, and likely lead to a stronger predictive approach than are currently available. Fractal-based scale invariant approach for analyzing long-term time series data can provide insight into the scaling issue as a quantitative approach for evaluating temporal scale in hydrologic time series. The main objective of this research is to study the effects of deterministic trends, mainly seasonality of hydrologic time series on scaling parameter. Different hydrologic time series (rainfall and runoff) from various locations are investigated. Two hydrologic time series, one with the raw hydrologic time series data and another by removing the seasonality are compared. The comparison of untransformed and deseasonalized data series showed that there is no statistically significant value to deseasonalize the data, although the data series appears to shift toward random scaling after deseasonalization.

Koirala, S. R.

2012-12-01

214

Studies of soundings and imagings measurements from geostationary satellites  

NASA Technical Reports Server (NTRS)

Soundings and imaging measurements from geostationary satellites are presented. The subjects discussed are: (1) meteorological data processing techniques, (2) sun glitter, (3) cloud growth rate study, satellite stability characteristics, and (4) high resolution optics. The use of perturbation technique to obtain the motion of sensors aboard a satellite is described. The most conditions, and measurement errors. Several performance evaluation parameters are proposed.

Suomi, V. E.

1973-01-01

215

Satellite image processing using cellular array processor (CAP)  

Microsoft Academic Search

Since its successful launch in February of 1992, the Japan Earth Resources Satellite-1 (JERS-1) has been sending back high resolution images of the Earth for various studies, including the investigation of Earth resources, the preservation of environments and the observation of coastal lines. Currently, received images are processed using the Earth Resources Satellite Data Information System (ERSDIS). The ERSDIS is

M. Ajiro; H. Miyata; T. Kan; M. Ono

1993-01-01

216

Ship Detection and Recognitionin High-resolution Satellite Images  

Microsoft Academic Search

Nowadays, the availability of high-resolution images taken from satellites, like Quickbird, Orbview, and others, offers the remote sensing community the possibility of monitoring and surveying vast areas of the Earth for different purposes, e.g. monitoring forest regions for ecological reasons. A particular application is the use of satellite images to survey the bottom of the seas around the Iberian peninsula

Jose Antelo; Gregorio Ambrosio; Javier Gonzalez; Cipriano Galindo

2009-01-01

217

Prospects of application of survey satellite image for meteorology  

Microsoft Academic Search

The maximal interest is represented with the information from geostationary satellites. These satellites repeat shootings the chosen territories, allowing to study dynamics of images. Most interesting shootings in IR a range. Studying of survey image is applied to studying linear elements of clouds (LEC). It is established, that \\

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

2004-01-01

218

SATELLITE IMAGING OF TEMPORAL PHENOMENA Because the World is Watching  

E-print Network

SATELLITE IMAGING OF TEMPORAL PHENOMENA Because the World is Watching For Further Information out, providing good approximations to the data actually collected. Detailed analysis of the satellite, and other movement over water. Previously imaged targets rotate with frequencies on the order of 1 Hz

219

Intelligent Mining in Image Databases, With Applications to Satellite Imaging and to Web  

E-print Network

Intelligent Mining in Image Databases, With Applications to Satellite Imaging and to Web Search analysis; text in web images; mosaicing satellite images 1 Introduction 1.1 It is necessary to apply data by adding new ideas to the main idea of FFT-based image processing. In this paper, we show how the existing

Kreinovich, Vladik

220

Intelligent Mining in Image Databases, With Applications to Satellite Imaging and to Web  

E-print Network

Intelligent Mining in Image Databases, With Applications to Satellite Imaging and to Web Search analysis; text in web images; mosaicing satellite images 1 Introduction 1.1 It is necessary to apply data by adding new ideas to the main idea of FFT­based image processing. In this paper, we show how the existing

Kreinovich, Vladik

221

ARMA Model Identification of Hydrologic Time Series  

NASA Astrophysics Data System (ADS)

In recent years, ARMA models have become popular for modeling geophysical time series in general and hydrologic time series 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 time series. 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.

Salas, J. D.; Obeysekera, J. T. B.

1982-08-01

222

Learning time series for intelligent monitoring  

NASA Technical Reports Server (NTRS)

We address the problem of classifying time series according to their morphological features in the time domain. In a supervised machine-learning framework, we induce a classification procedure from a set of preclassified examples. For each class, we infer a model that captures its morphological features using Bayesian model induction and the minimum message length approach to assign priors. In the performance task, we classify a time series in one of the learned classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. We report results from experiments in a monitoring domain of interest to NASA.

Manganaris, Stefanos; Fisher, Doug

1994-01-01

223

Sliced Inverse Regression for Time Series Analysis  

Microsoft Academic Search

In this thesis, general nonlinear models for time series 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 time series 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.

Li-Sue Chen

1995-01-01

224

Building Chaotic Model From Incomplete Time Series  

NASA Astrophysics Data System (ADS)

This paper presents a number of novel techniques for building a predictive chaotic model from incomplete time series. A predictive chaotic model is built by reconstructing the time-delayed phase space from observed time series and the prediction is made by a global model or adaptive local models based on the dynamical neighbors found in the reconstructed phase space. In general, the building of any data-driven models depends on the completeness and quality of the data itself. However, the completeness of the data availability can not always be guaranteed since the measurement or data transmission is intermittently not working properly due to some reasons. We propose two main solutions dealing with incomplete time series: using imputing and non-imputing methods. For imputing methods, we utilized the interpolation methods (weighted sum of linear interpolations, Bayesian principle component analysis and cubic spline interpolation) and predictive models (neural network, kernel machine, chaotic model) for estimating the missing values. After imputing the missing values, the phase space reconstruction and chaotic model prediction are executed as a standard procedure. For non-imputing methods, we reconstructed the time-delayed phase space from observed time series with missing values. This reconstruction results in non-continuous trajectories. However, the local model prediction can still be made from the other dynamical neighbors reconstructed from non-missing values. We implemented and tested these methods to construct a chaotic model for predicting storm surges at Hoek van Holland as the entrance of Rotterdam Port. The hourly surge time series is available for duration of 1990-1996. For measuring the performance of the proposed methods, a synthetic time series with missing values generated by a particular random variable to the original (complete) time series is utilized. There exist two main performance measures used in this work: (1) error measures between the actual and missing value estimates; and (2) the accuracy of the built chaotic model predictions. The model results indicate that the proposed methods are able to build a chaotic model from incomplete time series and to provide reliable and accurate predictions.

Siek, Michael; Solomatine, Dimitri

2010-05-01

225

Trend change detection in vegetation greenness time series: Contrasting methodologies, data sets and global vegetation models  

NASA Astrophysics Data System (ADS)

Newly developed satellite datasets and time series analysis methods allow the quantification of changes in vegetation greenness. However, the estimation of trends and trend changes depend often on the applied time series analysis method and the used satellite dataset. Thus, the environmental plausibility of the estimated trends and trend breakpoints is often questionable. We compared four trend and trend change detection methods to assess their performance. We applied the methods to NDVI and FAPAR time series from global satellite datasets and from global vegetation models. We generated surrogate time series with known trends and breakpoints and applied the methods to re-detect the known trends and trend changes. Our results demonstrate that the performance of methods decrease with increasing inter-annual variability of the time series. An overestimation of breakpoints in NDVI time series can result in wrong or even opposite trend estimates. Trend slope estimates based on annual aggregated time series or based on a seasonal-trend model show better performances than methods that remove the seasonal cycle of the time series. The application of the trend change detection methods to real time series allows assessing the multi-method ensemble of trend estimates. Nevertheless, the interpretation of the environmental plausibility of these trend estimates is challenging. For example, some methods suggest a weakening of greening trends in the Tundra after the early 2000s while other methods suggest an ongoing greening. Comparison with vegetation model simulations suggest that this weakening is not an artefact of the satellite dataset or of the applied trend change detection method but might be caused by real changes in environmental conditions. Our results demonstrate the need for a critical appraisal of trend change detection methods. All methods require a careful assessment of the environmental plausibility of detected trend changes in vegetation greenness time series.

Forkel, Matthias; Carvalhais, Nuno; Verbesselt, Jan; Mahecha, Miguel; Neigh, Christopher; Thonicke, Kirsten; Reichstein, Markus

2014-05-01

226

Collection and simulation analysis of moored fluorometer time series from the mid-Atlantic and south Atlantic Bights. Appendix I. Satellite detection of phytoplankton export from the mid-Atlantic Bight during the 1979 spring bloom  

SciTech Connect

Analysis of CZCS imagery confirms shipboard and aircraft observations of resuspension of near-bottom chlorophyll within surface water (1 to 10 m) by northwesterly wind events in the mid-Atlantic Bight. As much as 8 to 16 ..mu..g Chl l/sup -1/ are found during these wind events from March to May, with a seasonal increase of algal biomass until onset of stratificationn of the water column. Rapid sinking apparently occurs after cessation of the wind events such that the predominant surface chlorophyll pattern is approx.0.5 to 1.5 ..mu..g l/sup -1/ over the continental shelf during the spring bloom. Without enhanced primary production during a wind event, the annual photosynthetic input of carbon would be approx.270 g C m/sup -2/ yr/sup -1/. Perhaps half of the chlorophyll increase observed by satellite during a wind event represents in situ production of that 4 to 5 day time interval, with the remainder attributed to accumulation of algal biomass previously produced, sunk out, resuspended, and enroute to the shelf break during these offshore transport events. At least 16 to 40 g C m/sup -2/ yr/sup -1/ may be exported as ungrazed phytoplankton carbon from shelf waters to continental slope sediments. 32 refs., 37 figs., 3 tabs.

Walsh, J.J.; Esaias, W.E.

1985-01-01

227

Robust Copyright Protection of Satellite Images Using a Novel Digital Image-In-Image Watermarking Algorithm  

E-print Network

. The performance of any digital watermarking algorithms depends on the tradeoff between data integrity of digital multimedia content on the Internet and other media has led to recent interest and researchRobust Copyright Protection of Satellite Images Using a Novel Digital Image-In-Image Watermarking

Doran, Simon J.

228

Automatic Curvilinear Structure detection from Satellite Images using Multiresolution GMM  

Microsoft Academic Search

This paper presents a multi-resolution based framework for detecting curvilinear structures from satellite images. Curvilinear structure detection finds its application in remote-sensed images for the extraction of networks such as roads, rivers, and highways. In the proposed methodology, curvilinear segments from the satellite images are extracted using multi-resolution GMM approach. The extracted curvilinear segments can be used for the detection

Mirnalinee Dhinesh; Koshy Varghese

2008-01-01

229

Modeling MIDI Music as Multivariate Time Series  

Microsoft Academic Search

A method of modeling music using multivariate time series models is described. The models are generated using a hybrid neural networks\\/discrete particle swarm optimization technique. Such models capture the essence of a piece of music, capable of generating new music sequences. The degree of similarity of the new sequence to the original piece can be controlled by adjusting fitness parameters.

Alex Kalos

2006-01-01

230

Integrated method for chaotic time series analysis  

DOEpatents

Methods and apparatus for automatically detecting differences between similar but different states in a nonlinear process monitor nonlinear data are disclosed. Steps include: acquiring the data; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; and determining by comparison whether differences between similar but different states are indicated. 8 figs.

Hively, L.M.; Ng, E.G.

1998-09-29

231

Confidence interval estimation using standardized time series  

Microsoft Academic Search

Observations of a stationary stochastic process can be transformed into a standardized time series. This paper presents a lemma giving the asymptotic properties of this standardized series under quite general conditions. In particular, the conditions are satisfied by stationary discrete-event simulations. Confidence intervals can be constructed using this lemma. For illustration, we develop two easily computed interval estimators for the

Lee W. Schruben

1983-01-01

232

Using Image Tour to Explore Multiangle, Multispectral Satellite Image  

NASA Technical Reports Server (NTRS)

This viewgraph presentation reviews the use of Image Tour to explore the multiangle, multispectral satellite imagery. Remote sensing data are spatial arrays of p-dimensional vectors where each component corresponds to one of p variables. Applying the same R(exp p) to R(exp d) projection to all pixels creates new images, which may be easier to analyze than the original because d < p. Image grand tour (IGT) steps through the space of projections, and d=3 outputs a sequence of RGB images, one for each step. In this talk, we apply IGT to multiangle, multispectral data from NASA's MISR instrument. MISR views each pixel in four spectral bands at nine view angles. Multiple views detect photon scattering in different directions and are indicative of physical properties of the scene. IGT allows us to explore MISR's data structure while maintaining spatial context; a key requirement for physical interpretation. We report results highlighting the uniqueness of multiangle data and how IGT can exploit it.

Braverman, Amy; Wegman, Edward J.; Martinez, Wendy; Symanzik, Juergen; Wallet, Brad

2006-01-01

233

Time Series Analysis Model for Rainfall Data in Jordan: Case Study for Using Time Series Analysis  

Microsoft Academic Search

Problem statement: Time series 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 time series 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

Naill M. Momani

2009-01-01

234

Can biomass time series be reliably assessed from CPUE time series data Francis Lalo1  

E-print Network

1 Can biomass time series be reliably assessed from CPUE time series data only? Francis Laloë1 to abundance. This means (i) that catchability is constant and (ii) that all the biomass is catchable. If so, relative variations in CPUE indicate the same relative variations in biomass. Myers and Worm consider

Hawai'i at Manoa, University of

235

Time series A time series is a stochastic process {Yt : t =  

E-print Network

Time series A time series is a stochastic process {Yt : t = 0, ±1, ±2, . . .}, where the index t represents time. Often the random variables occur at evenly spaced points in time, a condition that we as to be "regular" over time. There are many definitions of stationarity, but perhaps the most common is covariance

236

A 25 Years Long Reference Frame Time Series from LAGEOS  

NASA Astrophysics Data System (ADS)

Based on LAGEOS-1 and -2 Satellite Laser Ranging (SLR) data a 25 year long time series of station coordinates, low degree harmonics, and Earth Orientation Parameters (EOPs) were generated adopting state of the art GRACE release 4 standards. Therefore also atmospheric and oceanic mass variations as provided by the so-called GRACE Atmosphere and Ocean De-aliasing (AOD) products are taken into account. The solution compiles weekly resolved station coordinates and low degree harmonics, and daily resolved EOPs in recent times, in the early periods it obeys some relaxed resolution. The results are presented with focus on origin and scale of the reference frame.

Koenig, R.; Vei, M.

2009-04-01

237

Biological Visual Attention Guided Automatic Image Segmentation with Application in Satellite Imaging  

E-print Network

Biological Visual Attention Guided Automatic Image Segmentation with Application in Satellite to the improvement of the performance of computational image processing systems. Computational models of visual a wide range of image content, characteristics and scales such as those encountered in satellite imaging

Payeur, Pierre

238

Evaluation of Urban Environmental Quality with High Resolution Satellite Images  

Microsoft Academic Search

It can serve for the city planning scientifically and improve the people's daily life level actively to evaluate the urban environment status efficiently from the meter resolution satellite images such as IKONOS images and QUICKBIRD images. We can obtain the environment information such as vegetation type and its cover area, water body area and water pollution status, the air pollution

Meichun Yan; Liliang Ren; Xiufeng He; Wengang Sang

2008-01-01

239

Learning reduced models for motion estimation on ocean satellite images  

E-print Network

Learning reduced models for motion estimation on ocean satellite images Isabelle Herlin1 in the reduced models that make it feasible to process in quasi-real time image acqui- sitions. Twin experiments been intensively studied since the be- ginning of image processing (Horn and Schunk, 1981; Isambert et

Paris-Sud XI, Université de

240

Fully Automatic Road Network Extraction from Satellite Images  

Microsoft Academic Search

In this paper a fully automatic road detection algorithm is introduced. It comprises of pre-processing the image via a series of wavelet based filter banks and reducing the yielding data into a single image which is of the same size as the original optical grayscale satellite image, then utilizing a fuzzy inference algorithm to carry out the road detection which

O. Tuncer

2007-01-01

241

Wavelet analysis of satellite images for coastal watch  

Microsoft Academic Search

The two-dimensional wavelet transform is a very efficient bandpass filter, which can be used to separate various scales of processes and show their relative phase\\/location. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite imagery employing wavelet analysis are developed. The wavelet transform has been applied to satellite images, such as those from

Antony K. Liu; Chich Y. Peng; S. Y.-S. Chang

1997-01-01

242

Satellite Image Processing on a Grid-Based Platform  

Microsoft Academic Search

Satellite image processing is both data and computing intensive, and, therefore, it raises several difficulties or even impossibilities while being using one single computer. Moreover, the analysis and sharing of the huge amount of data provided daily by the space satellites is a major challenge for the remote sensing community. Recently, Gridbased platforms were built to address these issues. This

Dana Petcu; Dorian Gorgan; textbfFlorin Pop; Dacian Tudor; Daniela Zaharie

2008-01-01

243

Radiative transfer model for simulating high-resolution satellite images  

Microsoft Academic Search

A simulator of high spatial resolution satellite images is introduced. It is based on the coupling of two radiative transfer models: discrete anisotropic radiative transfer (DART) for terrestrial landscapes and second simulation of the satellite signal in the solar spectrum (6S) for the atmosphere. It works in the visible, near infrared, and midinfrared domains. The simulation procedure involves four steps:

Ferran Gascon; Jean-Philippe Gastellu-Etchegorry; Marie-José Lefèvre

2001-01-01

244

Finding Stationary Subspaces in Multivariate Time Series  

NASA Astrophysics Data System (ADS)

Identifying temporally invariant components in complex multivariate time series 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 time series 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.

von Bünau, Paul; Meinecke, Frank C.; Király, Franz C.; Müller, Klaus-Robert

2009-11-01

245

A CCD Time-Series Photometer  

E-print Network

We describe a high speed time-series CCD photometer for the prime focus of the 82-in (2.1 m) telescope at McDonald Observatory, and summarize the observational results we have obtained since it was placed into regular use in February, 2002. We compare this instrument with the three-channel time-series photometers we have previously used in the asteroseismological study of pulsating white dwarf stars, which used photomultiplier tubes (PMT) as the detectors. We find the CCD instrument is about 9 times more sensitive than the PMT instruments used on the same telescope for the same exposure time. We can therefore find and measure variable white dwarf stars some 2.4 magnitudes fainter than before, significantly increasing the number of such objects available for study.

R. E. Nather; Anjum. S. Mukadam

2003-06-01

246

Regularization of Nutation Time Series at GSFC  

NASA Astrophysics Data System (ADS)

VLBI is unique in its ability to measure all five Earth orientation parameters. In this paper we focus on the two nutation parameters which characterize the orientation of the Earth's rotation axis in space. We look at the periodicities and the spectral characteristics of these parameters for both R1 and R4 sessions independently. The study of the most significant periodic signals for periods shorter than 600 days is common for these four time series (period of 450 days), and the type of noise determined by the Allan variance is a white noise for the four series. To investigate methods of regularizing the series, we look at a Singular Spectrum Analysis-derived method and at the Kalman filter. The two methods adequately reproduce the tendency of the nutation time series, but the resulting series are noisier using the Singular Spectrum Analysis-derived method.

Le Bail, K.; Gipson, J. M.; Bolotin, S.

2012-12-01

247

Random Matrix Spectra as a Time Series  

E-print Network

Spectra of ordered eigenvalues of finite Random Matrices are interpreted as a time series. Dataadaptive techniques from signal analysis are applied to decompose the spectrum in clearly differentiated trend and fluctuation modes, avoiding possible artifacts introduced by standard unfolding techniques. The fluctuation modes are scale invariant and follow different power laws for Poisson and Gaussian ensembles, which already during the unfolding allows to distinguish the two cases.

Ruben Fossion; Gamaliel Torres Vargas; Juan Carlos López Vieyra

2013-11-21

248

Turbulencelike Behavior of Seismic Time Series  

SciTech Connect

We report on a stochastic analysis of Earth's vertical velocity time series 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.

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)

2009-01-09

249

Revisiting algorithms for generating surrogate time series  

E-print Network

The method of surrogates is one of the key concepts of nonlinear data analysis. Here, we demonstrate that commonly used algorithms for generating surrogates often fail to generate truly linear time series. Rather, they create surrogate realizations with Fourier phase correlations leading to non-detections of nonlinearities. We argue that reliable surrogates can only be generated, if one tests separately for static and dynamic nonlinearities.

C. Raeth; M. Gliozzi; I. E. Papadakis; W. Brinkmann

2011-11-06

250

Calibration of infrared satellite images using high altitude aircraft measurements  

NASA Technical Reports Server (NTRS)

The use of infrared radiance measurements made from high altitude aircraft for satellite image validation is discussed. Selected examples are presented to illustrate the techniques and the potentials of such validation studies.

Hammer, Philip D.; Gore, Warren J. Y.; Valero, Francisco P. J.

1989-01-01

251

Satellite Image Processing Applications in MedioGRID  

Microsoft Academic Search

This paper presents a high level architectural specification of MedioGRID, a research project aiming at implementing a real-time satellite image 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 satellite image processing system, highlighting the technologies for each of the major components. An essential part

Ovidiu Muresan; textbfFlorin Pop; Dorian Gorgan; Valentin Cristea

2006-01-01

252

Near-real-time satellite image processing: metacomputing in CC++  

Microsoft Academic Search

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 satellite images. The application processes the satellite images by using Compositional C++ (CC++)-a simple, yet powerful extension of C++-and its runtime system, Nexus, to integrate specialized resources,

Craig A. Lee; Carl Kesselman; Stephen Schwab

1996-01-01

253

Rapid Calibration of Operational and Research Meteorological Satellite Imagers. Part I: Evaluation of Research Satellite Visible Channels as References  

Microsoft Academic Search

Operational meteorological satellites generally lack reliable onboard calibration systems for solar-imaging channels. Current methods for calibrating these channels and for normalizing similar channels on contempo- raneous satellite imagers typically rely on a poorly calibrated reference source. To establish a more reliable reference instrument for calibration normalization, this paper examines the use of research satellite imagers that maintain their solar-channel calibrations

Patrick Minnis; Louis Nguyen; David R. Doelling; David F. Young; Walter F. Miller; David P. Kratz

2002-01-01

254

Diffraction-limited imaging of satellites using bispectral speckle interferometry  

SciTech Connect

We have developed and implemented a new technology for removing the effects of atmospheric turbulence from telescope images. This technology, bispectral speckle interferometry, permits imaging of astronomical objects and satellites to the diffraction limit of the collecting telescope. We have successfully applied this technique to speckle images 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 satellites, including the Hubble Space Telescope. This technology should have a positive impact on both astronomical and defense imaging problems. 18 ref., 4 figs.

Lawrence, T.W.; Goodman, D.M.; Fitch, J.P.; Johansson, E.M.

1990-11-21

255

Wavelet-based multifractal analysis of fMRI time series  

Microsoft Academic Search

Functional magnetic resonance imaging (fMRI) time series are investigated with a multifractal method based on the Wavelet Modulus Maxima (WTMM) method to extract local singularity (“fractal”) exponents. The spectrum of singularity exponents of each fMRI time series is quantified by spectral characteristics including its maximum and the corresponding dimension. We found that the range of Hölder exponents in voxels with

Yu Shimizu; Markus Barth; Christian Windischberger; Ewald Moser; Stefan Thurner

2004-01-01

256

RECENT DEVELOPMENTS IN HYDROWEB DATABASE Water level time series on lakes and reservoirs (Invited)  

NASA Astrophysics Data System (ADS)

We present the current state of the Hydroweb database as well as developments in progress. It provides offline water level time series on rivers, reservoirs and lakes based on altimetry data from several satellites (Topex/Poseidon, ERS, Jason-1&2, GFO and ENVISAT). The major developments in Hydroweb concerns the development of an operational data centre with automatic acquisition and processing of IGDR data for updating time series in near real time (both for lakes & rivers) and also use of additional remote sensing data, like satellite imagery allowing the calculation of lake's surfaces. A lake data centre is under development at the Legos in coordination with Hydrolare Project leaded by SHI (State Hydrological Institute of the Russian Academy of Science). It will provide the level-surface-volume variations of about 230 lakes and reservoirs, calculated through combination of various satellite images (Modis, Asar, Landsat, Cbers) and radar altimetry (Topex / Poseidon, Jason-1 & 2, GFO, Envisat, ERS2, AltiKa). The final objective is to propose a data centre fully based on remote sensing technique and controlled by in situ infrastructure for the Global Terrestrial Network for Lakes (GTN-L) under the supervision of WMO and GCOS. In a longer perspective, the Hydroweb database will integrate data from future missions (Jason-3, Jason-CS, Sentinel-3A/B) and finally will serve for the design of the SWOT mission. The products of hydroweb will be used as input data for simulation of the SWOT products (water height and surface variations of lakes and rivers). In the future, the SWOT mission will allow to monitor on a sub-monthly basis the worldwide lakes and reservoirs bigger than 250 * 250 m and Hydroweb will host water level and extent products from this

Cretaux, J.; Arsen, A.; Calmant, S.

2013-12-01

257

An IMAGE Satellite Guide to Exploring the Earth's Magnetic Field 1 An IMAGE Satellite Guide to Exploring the Earth's Magnetic Field 2  

E-print Network

An IMAGE Satellite Guide to Exploring the Earth's Magnetic Field 1 #12;An IMAGE Satellite Guide to Exploring the Earth's Magnetic Field 2 Dr. James Burch IMAGE Principal Investigator Dr. William Taylor Dr Spring, Maryland #12;An IMAGE Satellite Guide to Exploring the Earth's Magnetic Field 3 Chapter 1: What

258

Bermuda Atlantic Time-series Study  

NSDL National Science Digital Library

The Bermuda Atlantic Time-series 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.

2007-09-21

259

Nonparametric sequential prediction of time series  

E-print Network

Time series prediction covers a vast field of every-day statistical applications in medical, environmental and economic domains. In this paper we develop nonparametric prediction strategies based on the combination of a set of 'experts' and show the universal consistency of these strategies under a minimum of conditions. We perform an in-depth analysis of real-world data sets and show that these nonparametric strategies are more flexible, faster and generally outperform ARMA methods in terms of normalized cumulative prediction error.

Biau, Gérard; Györfi, László; Ottucsák, György

2008-01-01

260

Assessment of temporal variations of water quality in inland water bodies using atmospheric corrected satellite remotely sensed image data.  

PubMed

Although there have been many studies conducted on the use of satellite remote sensing for water quality monitoring and assessment in inland water bodies, relatively few studies have considered the problem of atmospheric intervention of the satellite signal. The problem is especially significant when using time series multi-spectral satellite data to monitor water quality surveillance in inland waters such as reservoirs, lakes, and dams because atmospheric effects constitute the majority of the at-satellite reflectance over water. For the assessment of temporal variations of water quality, the use of multi-date satellite images is required so atmospheric corrected image data must be determined. The aim of this study is to provide a simple way of monitoring and assessing temporal variations of water quality in a set of inland water bodies using an earth observation- based approach. The proposed methodology is based on the development of an image-based algorithm which consists of a selection of sampling area on the image (outlet), application of masking and convolution image processing filter, and application of the darkest pixel atmospheric correction. The proposed method has been applied in two different geographical areas, in UK and Cyprus. Mainly, the method has been applied to a series of eight archived Landsat-5 TM images acquired from March 1985 up to November 1985 of the Lower Thames Valley area in the West London (UK) consisting of large water treatment reservoirs. Finally, the method is further tested to the Kourris Dam in Cyprus. It has been found that atmospheric correction is essential in water quality assessment studies using satellite remotely sensed imagery since it improves significantly the water reflectance enabling effective water quality assessment to be made. PMID:19067211

Hadjimitsis, Diofantos G; Clayton, Chris

2009-12-01

261

Analyzing Satellite Images Of The Ocean  

NASA Technical Reports Server (NTRS)

PC-SEAPAK is user-interactive software package specifically developed for analysis of data from satellites in oceanographic research. Program used to process and interpret data obtained from Nimbus-7/Coastal Zone Color Scanner (CZCS) and NOAA Advanced Very High Resolution Radiometer (AVHRR). PC-SEAPAK copyrighted product with all copyright vested in National Aeronautics and Space Administration.

Mcclain, Charles R.

1992-01-01

262

Noise characteristics of LCOGT time series photometry  

NASA Astrophysics Data System (ADS)

The Las Cumbres Observatory Global Telescope (LCOGT) facility consists of a network of robotic telescopes located at multiple sites in both the northern and southern hemispheres. We have deployed and commissioned nine 1.0m telescopes. Eight of these are distributed longitudinally at three sites to provide continuous night-time coverage in the south. LCOGT's unique capabilities can contribute to a wide range of research in the field of time-domain astronomy. To ensure optimal data quality for individual as well as combined multi-telescope time series, it is essential that we understand and correct - whenever possible - the instrument systematics affecting LCOGT network observations. We identify physical sources of noise present in LCOGT 1.0m photometry, and we use singular value decomposition (SVD) to filter correlated noise patterns common to an ensemble of stars in a given time series data set. We quantify and compare the levels of uncorrelated and correlated noise before and after SVD filtering using power spectral analysis. Finally, we discuss the properties of and methods to reduce any remaining post-SVD red noise that is due to instrumental systematics.

Dragomir, Diana; Brown, T. M.

2014-01-01

263

Radar Interferometry Time Series Analysis and Tools  

NASA Astrophysics Data System (ADS)

We consider the use of several multi-interferogram analysis techniques for identifying transient ground motions. Our approaches range from specialized InSAR processing for persistent scatterer and small baseline subset methods to the post-processing of geocoded displacement maps using a linear inversion-singular value decomposition solution procedure. To better understand these approaches, we have simulated sets of interferograms spanning several deformation phenomena, including localized subsidence bowls with constant velocity and seasonal deformation fluctuations. We will present results and insights from the application of these time series analysis techniques to several land subsidence study sites with varying deformation and environmental conditions, e.g., arid Phoenix and coastal Houston-Galveston metropolitan areas and rural Texas sink holes. We consistently find that the time invested in implementing, applying and comparing multiple InSAR time series approaches for a given study site is rewarded with a deeper understanding of the techniques and deformation phenomena. To this end, and with support from NSF, we are preparing a first-version of an InSAR post-processing toolkit to be released to the InSAR science community. These studies form a baseline of results to compare against the higher spatial and temporal sampling anticipated from TerraSAR-X as well as the trade-off between spatial coverage and resolution when relying on ScanSAR interferometry.

Buckley, S. M.

2006-12-01

264

Edge Detection in Satellite Image Using Cellular Neural Network  

Microsoft Academic Search

The present paper proposes a novel approach for edge detection in satellite images based on cellular neural networks. CNN based edge detector in used conjunction with image enhancement and noise removal techniques, in order to deliver accurate edge detection results, compared with state of the art approaches. Thus, considering the obtained results, a comparison with optimal Canny edge detector is

Osama Basil Gazi; Mohamed Belal; Hala Abdel-Galil

2014-01-01

265

Retrieving Multispectral Satellite Images Using Physics-Based Invariant Representations  

Microsoft Academic Search

We present a set of algorithms and a search strategy for the robust content-based retrieval of multispectral satellite images. Since the property of interest in these images is usually the physical characteristics of ground cover, we use representations and methods that are invariant to illumination and atmospheric conditions. The representations and algorithms are derived for this application from a physical

Glenn Healey; Amit Jain

1996-01-01

266

Ice sheet change detection by satellite image differencing  

Microsoft Academic Search

Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes

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

2010-01-01

267

Multispectral Satellite Image Processing on a Platform FPGA Engine  

Microsoft Academic Search

Multi-spectral satellite image sets present a storage and transmission problem. These image sets can also contain line features that typical detection methods do not resolve sharply enough for some purposes. The Karhunen-Lo eve transform (KLT) presents a solution to both these prob- lems. Firstly, the KLT can be used as a form of lossy data compression, only retaining the higher-

M. Fleury; R. P. Self; A. C. Downton

268

A Solution for Satellite Image Processing on Grids  

Microsoft Academic Search

Remote sensing image processing is both data and computing intensive. Grid technologies currently provides powerful tools for remote sensing data sharing and processing. After an overview of the recent initiatives of gridifying satellite image processing, two specific usage scenarios are analyzed. The solution that is proposed is based on freely distributed and general-purpose software: latest versions of Globus Toolkit, GIMP

DANA PETCU

2006-01-01

269

The qualitative analyses of cloud cover on optical satellite image  

NASA Astrophysics Data System (ADS)

The remote sensing technology has become the important information source in environment investigation, Moreover, optical satellite images are the most important information source. Although the optical satellite images may provides high resolution, multi-spectral images and better vision images than active satellite, the disadvantage is affected by the atmospheric condition easily. In general, the cloud cover is the most common noise, may decrease the image information abundantly and has impact on the environmental monitoring application seriously. According to the cloud imaging model, add defilade manually with different reflection coefficient to simulate different thickness of cloud. Then utilize GIS analytical method and cooperate with histogram calculation to extraction different reflection coefficients boundary. In this research, we get the upper threshold limitation value for haze and lower threshold limitation value for thick heavy cloud. So, we change the classification level from 2 ordinal levels into 3 qualitative levels. We change the thick and haze cover classification into threshold limitation value heavy, haze and fuzzy could cover classification by using the Formosat-2 satellite images. Make use of therefore way, can change the description yardstick into the quantitative yardstick that is we change the ordinal scale into interval scale in the image of cloud cover efficiency.

Liu, Chih-Heng; Yeh, Mei-Ling; Chou, Tine-Yin; Yang, Lung-Shih

2008-10-01

270

Cassini Imaging of Jupiter's Atmosphere, Satellites, and Rings  

E-print Network

Cassini Imaging of Jupiter's Atmosphere, Satellites, and Rings Carolyn C. Porco,1 * Robert A. West Science Subsystem acquired about 26,000 images 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

271

Unsupervised Change Detection of Satellite Images Using Local Gradual Descent  

Microsoft Academic Search

In this paper, we propose a novel technique for unsupervised change detection of multitemporal satellite images using Gaussian mixture model (GMM), local gradual descent, and $k$ -means clustering. Data distribution of the difference image is first modeled by bimodal GMM with “changed” and “unchanged” components. The neighborhood data around each pixel form a sample and are modified by the so-called

Zeki Yetgin

2012-01-01

272

Saliency and Gist Features for Target Detection in Satellite Images  

Microsoft Academic Search

Reliably detecting objects in broad-area overhead or satellite images has become an increasingly pressing need, as the capabilities for image acquisition are growing rapidly. The problem is particularly difficult in the presence of large in- traclass variability, e.g., finding \\

Zhicheng Li; Laurent Itti

2011-01-01

273

Ship Detection Using Texture Statistics from Optical Satellite Images  

Microsoft Academic Search

This paper presents a method for ship detection using texture statistics from optical satellite images. The proposed method focuses on the extraction of ship candidates. First, a structural texture descriptor derived from local multiple patterns is introduced to describe image texture features, and then two statistical histograms are generated by quantizing texture features to describe the texture difference between sea

Gaopan Huang; Yanqing Wang; Yushuang Zhang; Yuan Tian

2011-01-01

274

SEM algorithm and unsupervised statistical segmentation of satellite images  

Microsoft Academic Search

The work addresses Bayesian unsupervised satellite image segmentation, using contextual methods. It is shown, via a simulation study, that the spatial or spectral context contribution is sensitive to image parameters such as homogeneity, means, variances, and spatial or spectral correlations of the noise. From this one may choose the best context contribution according to the estimated values of the above

Pascale Masson; Wojciech Pieczynski

1993-01-01

275

Cassini imaging of Jupiter's atmosphere, satellites, and rings.  

PubMed

The Cassini Imaging Science Subsystem acquired about 26,000 images 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 images of the satellite Himalia, circumstantial evidence for a causal relation between the satellites Metis and Adrastea and the main jovian ring, and information on the nature of the ring particles. PMID:12624258

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

2003-03-01

276

The McIDAS system. [for meteorological satellite image processing  

NASA Technical Reports Server (NTRS)

The man-computer interactive data access system (McIDAS) hardware and software design is outlined, with emphasis on meteorological applications. The McIDAS system features a flexible digital image enhancement device. Theory of operation, the McIDAS language, the McIDAS executive monitor, image acquisition, image parameters, image display, graphics, image navigation, and image massaging are explained. The WINDCO/CLDHGT system, developed to align time sequences of geosynchronous satellite pictures and to determine the motion and height of selected cloud targets, is also described.

Smith, E. A.

1975-01-01

277

Comparing ODAC and Hierarchical algorithm using time series data streams  

Microsoft Academic Search

Mining Time Series data has a tremendous growth of interest in today's world. Clustering time series is a trouble that has applications in an extensive assortment of fields and has recently attracted a large amount of researchers. Time series data are frequently large and may contain outliers. In addition, time series are a special type of data set where elements

V. Kavitha; M. Punithavalli

2010-01-01

278

Detecting Forest Disturbance in the Pacific Northwest From MODIS Time Series Using Temporal Segmentation  

NASA Astrophysics Data System (ADS)

Changes to the land surface of the Earth are occurring at unprecedented rates with significant implications for surface energy balance and regional to global scale cycles of carbon and water. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellite platforms provide over 11 years of consistent, synoptic observations of the biosphere. New methods have recently emerged to analyze time series of remote sensing images, thereby providing ecologically important information about disturbance and succession over large regions. In particular, the Landtrendr algorithm was developed to characterize long-term trends, including punctual and gradual disturbance events and subsequent vegetation regrowth, in dense time series of Landsat imagery. While this approach has shown to be useful and robust in a wide range of ecosystems, its application is limited to areas with sufficient Landsat archive depth and relatively cloud-free periods. Additionally, the approach requires significant effort in atmospheric correction and normalization steps, increasing the cost for large-area application. Here we present an adaptation of the Landtrendr algorithm to an 11-year time series of MODIS Normalized BRDF-Adjusted Reflectance (NBAR) data to detect forest disturbance in the Northwest Forest Plan (NWFP) area of Washington, Oregon, and California. The NWFP area represents a dynamic zone of forest management with an active disturbance regime that includes insect defoliation, wildfires, and logging. This work aims to explore how the size and severity of disturbance events influence detection and characterization of such events using MODIS data. We sampled disturbance events across gradients of size and severity that occurred during the MODIS era (2000-present) using a high-quality database of forest disturbance information derived from Landsat. One-third of these disturbance records were used to calibrate the model using MODIS NBAR time series, and the remaining two-thirds were kept aside for assessment of model performance. The results demonstrate how the Landtrendr approach can be expanded for use at continental and global scales with data of moderate spatial resolution such as MODIS.

Sulla-Menashe, D. J.; Yang, Z.; Braaten, J.; Krankina, O. N.; Kennedy, R. E.; Friedl, M. A.

2011-12-01

279

Nonlinear Processing of Large Scale Satellite Images via Unsupervised Clustering and Image Segmentation  

Microsoft Academic Search

For large scale satellite images, it is evitable that images will be affected by various uncertain factors, especially those from atmosphere. To minimize the impact of atmosphere medium dispersing, image segmentation is an essential procedure. As one of the most critical means of image processing and data analysis approach, segmentation is to classify an image into parts that have a

JIECAI LUO; ZHENGMAO YE; PRADEEP BHATTACHARYA

2005-01-01

280

Improved satellite image compression and reconstruction via genetic algorithms  

NASA Astrophysics Data System (ADS)

A wide variety of signal and image processing applications, including the US Federal Bureau of Investigation's fingerprint compression standard [3] and the JPEG-2000 image 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 satellite image 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 satellite photographs of strategic urban areas. Test results show that a dramatic reduction in the error present in reconstructed satellite images 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 satellite images do not perform quite as well when subsequently tested against images 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 images represented in the training population.

Babb, Brendan; Moore, Frank; Peterson, Michael; Lamont, Gary

2008-10-01

281

Time Series Analysis of SOLSTICE Measurements  

NASA Astrophysics Data System (ADS)

Solar radiation is the major energy source for the Earth's biosphere and atmospheric and ocean circulations. Variations of solar irradiance have been a major concern of scientists both in solar physics and atmospheric sciences. A number of missions have been carried out to monitor changes in total solar irradiance (TSI) [see Fröhlich and Lean, 1998 for review] and spectral solar irradiance (SSI) [e.g., SOLSTICE on UARS and VIRGO on SOHO]. Observations over a long time period reveal the connection between variations in solar irradiance and surface magnetic fields of the Sun [Lean1997]. This connection provides a guide to scientists in modeling solar irradiances [e.g., Fontenla et al., 1999; Krivova et al., 2003]. Solar spectral observations have now been made over a relatively long time period, allowing statistical analysis. This paper focuses on predictability of solar spectral irradiance using observed SSI from SOLSTICE . Analysis of predictability is based on nonlinear dynamics using an artificial neural network in a reconstructed phase space [Abarbanel et al., 1993]. In the analysis, we first examine the average mutual information of the observed time series and a delayed time series. The time delay that gives local minimum of mutual information is chosen as the time-delay for phase space reconstruction [Fraser and Swinney, 1986]. The embedding dimension of the reconstructed phase space is determined using the false neighbors and false strands method [Kennel and Abarbanel, 2002]. Subsequently, we use a multi-layer feed-forward network with back propagation scheme [e.g., Haykin, 1994] to model the time series. The predictability of solar irradiance as a function of wavelength is considered. References Abarbanel, H. D. I., R. Brown, J. J. Sidorowich, and L. Sh. Tsimring, Rev. Mod. Phys. 65, 1331, 1993. Fraser, A. M. and H. L. Swinney, Phys. Rev. 33A, 1134, 1986. Fontenla, J., O. R. White, P. Fox, E. H. Avrett and R. L. Kurucz, The Astrophysical Journal, 518, 480-499, 1999. Fröhlich, C. and J. Lean, IAU Symposium 185: New Eyes to See Inside the Sun and Stars, edited by F. L. Deubner, 82-102, Kluwer Academic Publ., Dordrecht, The Netherland, 1998. Haykin, S., 696 pp, Macmillan, New York, 1994. Kennel, M. B. and H. D. I. Abarbanel, Phys. Rev. E 66, 026209, 2002. Krivova, N. A., S. K. Solanki, M. Fligge, and Y. C. Unruh, 399, L1-L4, 2003. Lean, J., Annu. Rev. Astron. Astrophys., 35, 33-67, 1997.

Wen, G.; Cahalan, R. F.

2003-12-01

282

Workshop on Satellite Meteorology. Part 2; Satellite Image Analysis and Interpretation  

NASA Technical Reports Server (NTRS)

The Workshop on Satellite Meteorology is co-sponsored by the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University and the American Meteorological Society's Committee on Meteorological Aspects of Aerospace Systems. The workshop covers uses of satellite data in atmospheric science. It provides state-of-the-art information to those in Universities, research groups, and other users. One area of primary focus is to provide source material to university personnel for developing and augmenting courses in satellite meteorology and the atmospheric sciences. The items in the program include information on meteorological satellites and data sources, uses of satellite imagery for all scales of weather analysis and forecasting, uses of sounding data and other radiance information and research opportunities on interactive systems. Each session is presented by a group of experts in the field and includes an open discussion of the state-of-the-art and promising areas for future development. This pre-print volume is one of three parts on the workshop. The three parts are: PART I. Satellites and Their Data; PART II. Satellite Image Analysis and Interpretation; PART III. Satellite Soundings and Their Uses.

1982-01-01

283

Automatic Traffic Monitoring from Satellite Images Using Artificial Immune System  

Microsoft Academic Search

\\u000a Automatic and intelligence Road traffic monitoring is a new research issue for high resolution satellite imagery application\\u000a in transportation. One of the results of this research was to control the traffic jam in roads and to recognize the traffic\\u000a density quickly and accurately. This article presents a new approach for recognizing the vehicle and the road in satellite\\u000a high-resolution images

Mehrad Eslami; Karim Faez

2010-01-01

284

Structural damage detection using bi-temporal optical satellite images  

Microsoft Academic Search

Multi-temporal satellite imagery is now available at sub-metre accuracy and has been found to be very useful for performing rapid damage assessment on human settlement areas affected by large-scale disasters. In this article, a method of formulating structural damage detection measures based on pre- and post-disaster satellite images is proposed. To validate the proposed damage measures, building-based structural damage assessment

Zhiqiang Chen; Tara C. Hutchinson

2011-01-01

285

Managing distribution changes in time series prediction  

NASA Astrophysics Data System (ADS)

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 time series 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.

Matias, J. M.; Gonzalez-Manteiga, W.; Taboada, J.; Ordonez, C.

2006-07-01

286

Multifractal analysis of polyalanines time series  

NASA Astrophysics Data System (ADS)

Multifractal properties of the energy time series of short ?-helix structures, specifically from a polyalanine family, are investigated through the MF-DFA technique ( multifractal detrended fluctuation analysis). Estimates for the generalized Hurst exponent h(q) and its associated multifractal exponents ?(q) are obtained for several series generated by numerical simulations of molecular dynamics in different systems from distinct initial conformations. All simulations were performed using the GROMOS force field, implemented in the program THOR. The main results have shown that all series exhibit multifractal behavior depending on the number of residues and temperature. Moreover, the multifractal spectra reveal important aspects of the time evolution of the system and suggest that the nucleation process of the secondary structures during the visits on the energy hyper-surface is an essential feature of the folding process.

Figueirêdo, P. H.; Nogueira, E.; Moret, M. A.; Coutinho, Sérgio

2010-05-01

287

Automatic tracking of crevasses on satellite images  

Microsoft Academic Search

Measurements of glacier motion and deformation are obtained by automatically matching features, such as crevasses, on repeat images. A computer-based method identifies and tracks groups of features on successive images, and calculates their displacement, and the rotation and distortion of the ice. Ice deformation within each matched area is permitted and calculated using a least-squares method within each area. The

Ian M. Whillans; Yi-Hsing Tseng

1995-01-01

288

OPTIMAL TIME-SERIES SELECTION OF QUASARS  

SciTech Connect

We present a novel method for the optimal selection of quasars using time-series 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 time-series 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.

Butler, Nathaniel R.; Bloom, Joshua S. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States)

2011-03-15

289

Weighted statistical parameters for irregularly sampled time series  

NASA Astrophysics Data System (ADS)

Unevenly spaced time series 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 satellites 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 time series 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.

Rimoldini, Lorenzo

2014-01-01

290

A Multiscale Approach to InSAR Time Series Analysis  

NASA Astrophysics Data System (ADS)

We present a technique to constrain time-dependent deformation from repeated satellite-based InSAR observations of a given region. This approach, which we call MInTS (Multiscale InSAR Time Series analysis), relies on a spatial wavelet decomposition to permit the inclusion of distance based spatial correlations in the observations while maintaining computational tractability. As opposed to single pixel InSAR time series techniques, MInTS takes advantage of both spatial and temporal characteristics of the deformation field. We use a weighting scheme which accounts for the presence of localized holes due to decorrelation or unwrapping errors in any given interferogram. We represent time-dependent deformation using a dictionary of general basis functions, capable of detecting both steady and transient processes. The estimation is regularized using a model resolution based smoothing so as to be able to capture rapid deformation where there are temporally dense radar acquisitions and to avoid oscillations during time periods devoid of acquisitions. MInTS also has the flexibility to explicitly parametrize known time-dependent processes that are expected to contribute to a given set of observations (e.g., co-seismic steps and post-seismic transients, secular variations, seasonal oscillations, etc.). We use cross validation to choose the regularization penalty parameter in the inversion of for the time-dependent deformation field. We demonstrate MInTS using a set of 63 ERS-1/2 and 29 Envisat interferograms for Long Valley Caldera.

Hetland, E. A.; Muse, P.; Simons, M.; Lin, N.; Dicaprio, C. J.

2010-12-01

291

Advances in time-series InSAR  

NASA Astrophysics Data System (ADS)

The need to measure temporally-evolving geophysical processes has spurred the development of precise geodetic Earth surface imaging methods using InSAR time series. The sequences of interferograms analyzed with these techniques not only reveal how the surface deforms with time, but permit unprecendented (1 mm/yr or less) accuracy over wide areas. Here we highlight several recent directions in the continuing improvement of the technology: a more comprehensive model of decorrelation that includes partially coherent pixels used in persistent scattering (PS) analysis, the use of information-theoretic tools to describe and optimize PS selection, phase retrieval, and extrapolation, and the development of 3D displacement imaging with PS and SBAS (small baseline subset analysis) methods. In addition, InSAR data collected as time series can be processed spatially for volume imaging of the surface cover. Such applications as forest canopy structure or ice volume effects benefit from this approach. Here we present each of these developments, both in theory and with examples from the current constellation of airborne and spaceborne radar systems to show the accuracies achievable today.

Zebker, H. A.; Wortham, C.; Lien, J.; Agram, P. S.

2011-12-01

292

Ground-Truthing Moderate Resolution Satellite Imagery with Near-Surface Canopy Images in Hawai'i's Tropical Cloud Forests  

NASA Astrophysics Data System (ADS)

Phenological studies are gaining importance globally as the onset of climate change is impacting the timing of green up and senescence in forest canopies and agricultural regions. Many studies use and analyze land surface phenology (LSP) derived from satellite vegetation index time series (VI's) such as those from Moderate Resolution Imaging Spectroradiometer (MODIS) to monitor changes in phenological events. Seasonality is expected in deciduous temperate forests, while tropical regions are predicted to show more static reflectance readings given their stable and steady state. Due to persistent cloud cover and atmospheric interference in tropical regions, satellite VI time series are often subject to uncertainties and thus require near surface vegetation monitoring systems for ground-truthing. This study has been designed to assess the precision of MODIS phenological signatures using above-canopy, down-looking digital cameras installed on flux towers on the Island of Hawai'i. The cameras are part of the expanding Phenological Eyes Network (PEN) which has been implementing a global network of above-canopy, hemispherical digital cameras for forest and agricultural phenological monitoring. Cameras have been installed at two locations in Hawaii - one on a flux tower in close proximity to the Thurston Lave Tube (HVT) in Hawai'i Volcanoes National Park and the other on a weather station in a section of the Hawaiian Tropical Experimental Forest in Laupaphoehoe (LEF). HVT consists primarily of a single canopy species, ohi'a lehua (Metrosideros polymorpha), with an understory of hapu'u ferns (Cibotium spp), while LEF is similarly comprised with an additional dominant species, Koa (Acacia Koa), included in the canopy structure. Given these species' characteristics, HVT is expected to show little seasonality, while LEF has the potential to deviate slightly during periods following dry and wet seasons. MODIS VI time series data are being analyzed and will be compared to images from the cameras which will have VI's extracted from their RGB image planes and will be normalized to be comparable with MODIS VI's. Given Hawai'i's susceptibility to invasion and delicacy of its endemic species, results from this study will provide necessary site specific detail in determining the reliability of satellite based inference in similar tropical phenology studies. Should satellite images provide adequate information, results from this study will allow for extrapolation across similar understudied tropical forests.

Bergstrom, R.; Miura, T.; Lepczyk, C.; Giambelluca, T. W.; Nullet, M. A.; Nagai, S.

2012-12-01

293

Indexing of satellite images with different resolutions by wavelet features.  

PubMed

Space agencies are rapidly building up massive image databases. A particularity of these databases is that they are made of images with different, but known, resolutions. In this paper, we introduce a new scheme allowing us to compare and index images with different resolutions. This scheme relies on a simplified acquisition model of satellite images and uses continuous wavelet decompositions. We establish a correspondence between scales which permits us to compare wavelet decompositions of images having different resolutions. We validate the approach through several matching and classification experiments, and we show that taking the acquisition process into account yields better results than just using scaling properties of wavelet features. PMID:18632354

Luo, Bin; Aujol, Jean-François; Gousseau, Yann; Ladjal, Saïd

2008-08-01

294

Fusion of Multispectral and Panchromatic Satellite Images Using the Curvelet Transform  

Microsoft Academic Search

A useful technique in various applications of remote sensing involves the fusion of different types of satellite images, namely multispectral (MS) satellite images with a high spectral and low spatial resolution and panchromatic (Pan) satellite image with a low spectral and high spatial resolution. Recent studies show that wavelet-based image fusion provides high-quality spectral content in fused images. However, the

Myungjin Choi; Rae Young Kim; Myeong-Ryong Nam; Hong Oh Kim

2005-01-01

295

Extracting the Geometry of Buildings from Satellite Images Extracting the Geometry  

E-print Network

) and image processing. The goal is to create a CAAD system that detects buildings from satellite images and satellite images in image processing has been researched and developed since the 1980's and the applicationExtracting the Geometry of Buildings from Satellite Images 1 Extracting the Geometry of Buildings

296

Highly comparative, feature-based time-series classification  

E-print Network

A highly comparative, feature-based approach to time series classification is introduced that uses an extensive database of algorithms to extract thousands of interpretable features from time series. These features are derived from across the scientific time-series analysis literature, and include summaries of time series in terms of their correlation structure, distribution, entropy, stationarity, scaling properties, and fits to a range of time-series models. After computing thousands of features for each time series in a training set, those that are most informative of the class structure are selected using greedy forward feature selection with a linear classifier. The resulting feature-based classifiers automatically learn the differences between classes using a reduced number of time-series properties, and circumvent the need to calculate distances between time series. Representing time series in this way results in orders of magnitude of dimensionality reduction, allowing the method to perform well on ve...

Fulcher, Ben D

2014-01-01

297

Multispectral inverse problems in satellite image processing S. A. Starks and V. Kreinovich  

E-print Network

Multi­spectral inverse problems in satellite image processing S. A. Starks and V. Kreinovich NASA, TX 79968, USA ABSTRACT Satellite imaging is nowadays one of the main sources of geophysical image. This case corresponds to a single satellite photo. Existing satellites (e.g., Landsat) take

Kreinovich, Vladik

298

Two satellite image sets for the training and validation of image processing systems for defense applications  

Microsoft Academic Search

Many image processing algorithms utilize the discrete wavelet transform (DWT) to provide efficient compression and near-perfect reconstruction of image data. Defense applications often require the transmission of data at high levels of compression over noisy channels. In recent years, evolutionary algorithms (EAs) have been utilized to optimize image transform filters that outperform standard wavelets for bandwidth-constrained compression of satellite images.

Michael R. Peterson; Shawn Aldridge; Britny Herzog; Frank Moore

2010-01-01

299

Comparative Analysis on Time Series with Included Structural Break  

NASA Astrophysics Data System (ADS)

The time series analysis (ARIMA models) is a good approach for identification of time series. But, if we have structural break in the time series, we cannot create only one model of time series. Further more, if we don't have enough data between two structural breaks, it's impossible to create valid time series models for identification of the time series. 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.

Andreeski, Cvetko J.; Vasant, Pandian

2009-08-01

300

Parametric model for intra-annual reflectance time series  

Microsoft Academic Search

Imaging and sensing technologies are constantly evolving so that, now, the latest generations of satellites commonly provide with earth snapshots at very short sampling periods (daily images). It is unquestionable that this tendency towards continuous time observation will broaden up the scope of remote sensing activities: not only will it enable real-time detection of abrupt changes (e.g. forest fires, natural

P. Goncalves; H. Carrao; M. Caetano

301

Simultaneous Fusion and Denoising of Panchromatic and Multispectral Satellite Images  

NASA Astrophysics Data System (ADS)

To identify objects in satellite images, multispectral (MS) images with high spectral resolution and low spatial resolution, and panchromatic (Pan) images 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 images with both high spectral and spatial resolutions. In this paper, a hybrid fusion method for satellite images 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 image as possible. A comparison study between the proposed hybrid method and the traditional methods is presented in this paper. Different MS and Pan images from Landsat-5, Spot, Landsat-7, and IKONOS satellites 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.

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.

2012-12-01

302

Characterization of noisy symbolic time series  

NASA Astrophysics Data System (ADS)

The 0-1 test for chaos is a recently developed time series characterization algorithm that can determine whether a system is chaotic or nonchaotic. While the 0-1 test was designed for deterministic series, in real-world measurement situations, noise levels may not be known and the 0-1 test may have difficulty distinguishing between chaos and randomness. In this paper, we couple the 0-1 test for chaos with a test for determinism and apply these tests to noisy symbolic series generated from various model systems. We find that the pairing of the 0-1 test with a test for determinism improves the ability to correctly distinguish between chaos and randomness from a noisy series. Furthermore, we explore the modes of failure for the 0-1 test and the test for determinism so that we can better understand the effectiveness of the two tests to handle various levels of noise. We find that while the tests can handle low noise and high noise situations, moderate levels of noise can lead to inconclusive results from the two tests.

Kulp, Christopher W.; Smith, Suzanne

2011-02-01

303

Spectrophotometric Time Series of ? Carinae's Great Eruption  

NASA Astrophysics Data System (ADS)

? Carinae (? Car) serves as our most important template for understanding non-SN transients from massive stars in external galaxies. However, until recently, no spectra were available because its historic ``Great Eruption'' (GE) occurred before the invention of the astronomical spectrograph. Now we can also obtain a spectral sequence of the eruption through echoes, which will be of great value since spectra are our most important tool for inferring physical properties of extragalactic transients. ? Car was seen as the second brightest star in the sky during its 1800s GE, but only visual estimates of its brightness were recorded teSF11. In 2011 we discovered several light echoes (LEs) which appear to be from the 1838- 1858 ? Car eruptions teRest12_eta. Subsequent spectroscopic follow-up revealed that its outburst spectral type was most similar to those of G-type supergiants, rather than reported LBV outburst spectral types of F-type (or earlier) teRest12_eta. These differences between the GE and the extragalactic transients presumed to be its analogues raise questions about traditional scenarios for the outburst. We propose to obtain a spectrophotometric time series of the GE from different directions, allowing the original eruption of ? Car to be studied as a function of time as well as latitude. A detailed spectroscopic study of the LEs of ? Car would help us understand (episodic) mass-loss in the most massive evolved stars and their connection to the most energetic core-collapse SNe.

Rest, Armin; Bianco, Federica; Chornock, Ryan; Matheson, Thomas; Prieto, Jose Luis; Smith, Chris; Smith, Nathan; Walborn, Nolan; Welch, Doug

2014-02-01

304

Extraction of stochastic dynamics from time series  

NASA Astrophysics Data System (ADS)

We present a method for the reconstruction of the dynamics of processes with discrete time. The time series 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.

Petelczyc, M.; ?ebrowski, J. J.; Gac, J. M.

2012-07-01

305

Evolutionary factor analysis of replicated time series.  

PubMed

In this article, we develop a novel method that explains the dynamic structure of multi-channel electroencephalograms (EEGs) recorded from several trials in a motor-visual task experiment. Preliminary analyses of our data suggest two statistical challenges. First, the variance at each channel and cross-covariance between each pair of channels evolve over time. Moreover, the cross-covariance profiles display a common structure across all pairs, and these features consistently appear across all trials. In the light of these features, we develop a novel evolutionary factor model (EFM) for multi-channel EEG data that systematically integrates information across replicated trials and allows for smoothly time-varying factor loadings. The individual EEGs series share common features across trials, thus, suggesting the need to pool information across trials, which motivates the use of the EFM for replicated time series. We explain the common co-movements of EEG signals through the existence of a small number of common factors. These latent factors are primarily responsible for processing the visual-motor task which, through the loadings, drive the behavior of the signals observed at different channels. The estimation of the time-varying loadings is based on the spectral decomposition of the estimated time-varying covariance matrix. PMID:22364516

Motta, Giovanni; Ombao, Hernando

2012-09-01

306

Time series analysis of syphilis surveillance data.  

PubMed

To manage a public health programme effectively it is necessary to set objectives and priorities according to the resources available. To utilize available resources optimally in a disease control programme we should both estimate the present and predict the future magnitude of the health problem. The CDC has an effective programme to control syphilis, a sexually transmitted disease. To keep track of control activities, CDC receives the number of syphilis cases from all states every three months. Primary and secondary syphilis cases declined from an all time high of 106,539 cases in 1947 to 6399 cases in 1956. Since then, syphilis cases increased to 27,921 in 1986. Congenital syphilis cases declined from 17,600 in 1941 to 239 in 1983, but increased to 408 in 1986. We built time series models for primary and secondary syphilis cases in men and women and congenital syphilis cases in children under one year of age. These models were used to forecast syphilis cases in all three categories. This analysis suggests that no change in the trend of male syphilis cases has occurred, but syphilis cases in women and congenital syphilis cases in children under one year of age during 1987 have increased. PMID:2711066

Zaidi, A A; Schnell, D J; Reynolds, G H

1989-03-01

307

Correcting and combining time series forecasters.  

PubMed

Combined forecasters have been in the vanguard of stochastic time series modeling. In this way it has been usual to suppose that each single model generates a residual or prediction error like a white noise. However, mostly because of disturbances not captured by each model, it is yet possible that such supposition is violated. The present paper introduces a two-step method for correcting and combining forecasting models. Firstly, the stochastic process underlying the bias of each predictive model is built according to a recursive ARIMA algorithm in order to achieve a white noise behavior. At each iteration of the algorithm the best ARIMA adjustment is determined according to a given information criterion (e.g. Akaike). Then, in the light of the corrected predictions, it is considered a maximum likelihood combined estimator. Applications involving single ARIMA and artificial neural networks models for Dow Jones Industrial Average Index, S&P500 Index, Google Stock Value, and Nasdaq Index series illustrate the usefulness of the proposed framework. PMID:24239986

Firmino, Paulo Renato A; de Mattos Neto, Paulo S G; Ferreira, Tiago A E

2014-02-01

308

Spectrophotometric Time Series of ? Carinae's Great Eruption  

NASA Astrophysics Data System (ADS)

? Car serves as our most important template for understanding non-SN transients from massive stars in external galaxies. However, until recently, no spectra were available because its historic ``Great Eruption'' (GE) occurred from 1838-1858, before the invention of the astronomical spectrograph, and only visual estimates of its brightness were recorded teSF11. Now we can also obtain a spectral sequence of the eruption through its light echoes we discovered, which will be of great value since spectra are our most important tool for inferring physical properties of extragalactic transients. Subsequent spectroscopic follow-up revealed that its outburst was most similar to those of G-type supergiants, rather than reported LBV outburst spectral types of F-type (or earlier) teRest12_eta. These differences between the GE and the extragalactic transients presumed to be its analogues raise questions about traditional scenarios for the outburst. We propose to obtain a spectrophotometric time series of the GE from different directions, allowing the original eruption of ? Car to be studied as a function of time as well as latitude, something only possible with light echoes. This unique detailed spectroscopic study of the light echoes of ? Car will help us understand (episodic) mass- loss in the most massive evolved stars and their connection to the most energetic core-collapse SNe.

Rest, Armin; Bianco, Federica; Chornock, Ryan; Clocchiatti, Alejandro; James, David; Margheim, Steve; Matheson, Thomas; Prieto, Jose Luis; Smith, Chris; Smith, Nathan; Walborn, Nolan; Welch, Doug; Zenteno, Alfredo

2014-08-01

309

The cradle of pyramids in satellite images  

E-print Network

We propose the use of image processing to enhance the Google Maps of some archaeological areas of Egypt. In particular we analyse that place which is considered the cradle of pyramids, where it was announced the discovery of a new pyramid by means of an infrared remote sensing.

Sparavigna, Amelia Carolina

2011-01-01

310

A Grid Environment Based Satellite Images Processing  

Microsoft Academic Search

With the presentation of massive remotely sensed data, it is one of the biggest challenges how to process and analyze these data as soon as possible. Owing to Grid conformity heterogeneous computing sources, a Grid environment is built for the processing of remotely sensed images. In this study, CSF4 is taken as meta-scheduler in the collective layer in such a

X. Zhang; S. Chen; J. Fan; X. Wei

2009-01-01

311

Satellite Image Processing on Computational Grids  

Microsoft Academic Search

Remote sensing image processing is a very demanding procedure in terms of data manipulation and computing power. Grid computing is a possible solution when the required computing performance or data sharing is not available at the user's site. Two scenarios of using Service Grids were analyzed in our papers (17, 18). This paper discusses another scenario of using Computational Grids.

DANA PETCU; SILVIU PANICA; ANDREI ECKSTEIN

2007-01-01

312

Satellite Image Atlas of Glaciers of the World  

USGS Publications Warehouse

In 1978, the USGS began the preparation of the 11-chapter USGS Professional Paper 1386, 'Satellite Image Atlas of Glaciers of the World'. Between 1979 and 1981, optimum satellite images were distributed to a team of 70 scientists, representing 25 nations and 45 institutions, who agreed to author sections of the Professional Paper concerning either a geographic area (chapters B-K) or a glaciological topic (included in Chapter A). The scientists used Landsat 1, 2, and 3 multispectral scanner (MSS) images and Landsat 2 and 3 return beam vidicon (RBV) images to inventory the areal occurrence of glacier ice on our planet within the boundaries of the spacecrafts' coverage (between about 82? north and south latitudes). Some later contributors also used Landsat 4 and 5 MSS and Thematic Mapper, Landsat 7 Enhanced Thematic Mapper-Plus (ETM+), and other satellite images. In addition to analyzing images of a specific geographic area, each author was asked to summarize up-to-date information about the glaciers within each area and compare their present-day areal distribution with reliable historical information (from published maps, reports, and photographs) about their past extent. Because of the limitations of Landsat images for delineating or monitoring small glaciers in some geographic areas (the result of inadequate spatial resolution, lack of suitable seasonal coverage, or absence of coverage), some information on the areal distribution of small glaciers was derived from ancillary sources, including other satellite images. Completion of the atlas will provide an accurate regional inventory of the areal extent of glaciers on our planet during a relatively narrow time interval (1972-1981).

Williams, Richard S., Jr.; Ferrigno, Jane G.

2005-01-01

313

Numbers to Pictures: How Satellite Images are Created  

NSDL National Science Digital Library

This activity introduces the primary colors of light. Satellites transmit images to us as a series of numbers, and this activity is designed to show how numbers are combined to create images using the primary colors of light. Students work in groups to create different colors using flashlights with red, blue, and green theatrical gels. Students create a numerical code to represent colors of light, experiment with building colors using the code, and complete a color mixing table.

314

Learning to transform time series with a few examples  

E-print Network

I describe a semi-supervised regression algorithm that learns to transform one time series into another time series given examples of the transformation. I apply this algorithm to tracking, where one transforms a time ...

Rahimi, Ali, 1976-

2006-01-01

315

Multitaper spectrum estimation for time series with gaps  

Microsoft Academic Search

Gaps in time series can produce spurious features in power spectrum estimates. These artifacts can be suppressed by averaging spectrum estimates obtained by first windowing the time series with a collection of orthogonal tapers. Such \\

Imola K. Fodor; Philip B. Stark

2000-01-01

316

Time Series of Trace Element Concentrations Calculated from  

E-print Network

Time Series of Trace Element Concentrations Calculated from Time Series of Suspended Solids Concentrations and RMP Water Samples Dr. David H. Schoellhamer US Geological Survey 2800 Cottage Way, Room W-2233.............................................................................................................................4 CALCULATED LCTEC DURING WATER YEAR 1995

317

Characterizing Pseudoperiodic Time Series through Complex Network Approach  

E-print Network

Characterizing Pseudoperiodic Time Series through Complex Network Approach Jie Zhang a Junfeng Sun proposed to explore the dynamics of pseudope- riodic time series by constructing a complex network [Phys; Complex network transformation; Unstable periodic orbits; Chaos Email address: enzhangjie

Wu, Dekai

318

What do Satellite Images Tell Us About Mars?  

NSDL National Science Digital Library

Learners will compare satellite images of Mars and Earth to look for similar features. Then they brainstorm a list of forces or events that could have caused some of these features to form on Mars. This is activity 3 of 9 in Mars and Earth: Science Learning Activities for After School.

319

Mapping from space — cartographic applications of satellite image data  

Microsoft Academic Search

Digital as well as photographic satellite image data offer a high potential of topographic and thematic information. The paper discusses the application of such data for mapping purposes. For the compilation of conventionalTopographic Maps the requirements concerning the geometrical accuracy can easily be met for 1 : 50,000 or even 1 : 25,000. However, the interpretability of the features that

Joerg Albertz; Ruediger Tauch

1994-01-01

320

Urban road extraction from high-resolution optical satellite images  

Microsoft Academic Search

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 satellite images is present. Firstly, a multi-scale greylevel morphological cleaning algorithm is proposed to reduce the grey deviation of

Hui Long; Zhongming Zhao

2005-01-01

321

Soft-Change Detection in Optical Satellite Images  

Microsoft Academic Search

In this letter, we propose a novel approach for un- supervised change detection in multitemporal optical satellite images. Unlike the traditional methods, the proposed method, called the soft-change detection, models the change detection as a transparency computation problem and assigns to each pixel a set of soft labels. In order to extract the pixel opacity, we optimize an objective function

Wang Luo; Hongliang Li

2011-01-01

322

Satellite Image Analysis for Disaster and Crisis-Management Support  

Microsoft Academic Search

This paper describes how multisource satellite data and efficient image 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 \\

Stefan Voigt; Thomas Kemper; Torsten Riedlinger; Ralph Kiefl; Klaas Scholte; Harald Mehl

2007-01-01

323

Automatic Red Tide Detection using MODIS Satellite Images  

Microsoft Academic Search

Red tides pose a significant economic and environmental threat in the Gulf of Mexico. Detecting red tide is important for understanding this phenomenon. In this thesis, machine learning approaches based on Random Forests, Support Vector Machines and K-Nearest Neighbors have been evaluated for red tide detection from MODIS satellite images. Detection results using machine learning algorithms were compared to ship

Wijian Cheng

2009-01-01

324

[Satellite Image of New Mexico Fires May 2000  

NSDL National Science Digital Library

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 satellite image (.jpg format) of fires in New Mexico from May 17, including the Cerro Grande fire.

2000-01-01

325

IMAGE GUIDED RESPIRATORY MOTION TIME SERIES AND IMAGE REGISTRATION  

E-print Network

¯glu, from whom I appreciated the professionalism, ambition and passion for truth of a young scientist. I fun place for my last year of Ph.D work, and its activities constitutes much of my healthy breaks from the freedom of exploration and owe my confidence to perform independent research to his encouragement

Fessler, Jeffrey A.

326

Optical Flow and Phase Portrait Methods for Environmental Satellite Image Sequences  

E-print Network

and oceanographic processes with image sequence processing. In this paper we focus on dynamic satellite imageOptical Flow and Phase Portrait Methods for Environmental Satellite Image Sequences Isaac COHEN framework for oceanographic satellite images. This framework is based on the use of a non quadratic

Cohen, Issac

327

ASSIMILATION OF SST SATELLITE IMAGES FOR ESTIMATION OF OCEAN CIRCULATION VELOCITY  

E-print Network

velocity can be estimated by image processing techniques applied to sequences of satellite imagesASSIMILATION OF SST SATELLITE IMAGES FOR ESTIMATION OF OCEAN CIRCULATION VELOCITY E. Huot1,2,3 I oceanographic satellite acquisitions. The problem of apparent motion estimation from a sequence of images has

Boyer, Edmond

328

Predictive Mining of Time Series Data  

NASA Astrophysics Data System (ADS)

All-sky monitors are a relatively new development in astronomy, and their data represent a largely untapped resource. Proper utilization of this resource could lead to important discoveries not only in the physics of variable objects, but in how one observes such objects. We discuss the development of a Java toolbox for astronomical time series data. Rather than using methods conventional in astronomy (e.g., power spectrum and cross-correlation analysis) we employ rule discovery techniques commonly used in analyzing stock-market data. By clustering patterns found within the data, rule discovery allows one to build predictive models, allowing one to forecast when a given event might occur or whether the occurrence of one event will trigger a second. We have tested the toolbox and accompanying display tool on datasets (representing several classes of objects) from the RXTE All Sky Monitor. We use these datasets to illustrate the methods and functionality of the toolbox. We have found predictive patterns in several ASM datasets. We also discuss problems faced in the development process, particularly the difficulties of dealing with discretized and irregularly sampled data. A possible application would be in scheduling target of opportunity observations where the astronomer wants to observe an object when a certain event or series of events occurs. By combining such a toolbox with an automatic, Java query tool which regularly gathers data on objects of interest, the astronomer or telescope operator could use the real-time datastream to efficiently predict the occurrence of (for example) a flare or other event. By combining the toolbox with dynamic time warping data-mining tools, one could predict events which may happen on variable time scales.

Java, A.; Perlman, E. S.

2002-05-01

329

Privacy Preserving Similarity Evaluation of Time Series Data  

E-print Network

Privacy Preserving Similarity Evaluation of Time Series Data Haohan Zhu Department of Computer@cs.bu.edu ABSTRACT Privacy preserving issues of time series databases in finan- cial, medical and transportation.3 [Clustering]: Similarity measures Keywords Time Series Database, Similarity, Privacy Preserving (c) 2014

Kollios, George

330

APPARENT WATER OPTICAL PROPERTIES AT THE CARIBBEAN TIME SERIES STATION  

E-print Network

APPARENT WATER OPTICAL PROPERTIES AT THE CARIBBEAN TIME SERIES STATION Roy A. Armstrong, Jose M of Orinoco River water reaching the CaTS station. Multi-year time series recorded at CaTS depict seasonal of Puerto Rico Mayagüez, Puerto Rico 00681 ABSTRACT The Caribbean Time Series, located 28 nautical miles

Gilbes, Fernando

331

FORECASTING HYDROLOGIC TIME SERIES USING ARTIFICIAL NEURAL NETWORKS  

Microsoft Academic Search

Forecasting a hydrologic time series has been one of the most complicated tasks owing to the wid e range of data, the uncertainties in the parameters influencing the time series and also due to the non availability of adequate data. Recently Artificial Neural Networks (ANN) have become quite popular in time series forecasting i n various fields. This paper demonstrates

D. Nagesh Kumar; T. Sathish

332

Statistics 598K: Financial Time Series Purdue University  

E-print Network

Statistics 598K: Financial Time Series Dr. Levine Purdue University Fall 2012 Time series models Dr. Levine Purdue University Fall 2012 Why do we need to consider data over time if there's a time Page 2 #12;Statistics 598K: Financial Time Series Dr. Levine Purdue University Fall 2012 Example II

Levine, Michael "Mihail"

333

Statistics 520: Time Series and Applications Purdue University  

E-print Network

Statistics 520: Time Series and Applications Dr. Levine Purdue University Spring 2013 Introduction Shumway and Stoffer: 1.1-1.7 Jan, 2012 Page 1 #12;Statistics 520: Time Series and Applications Dr. Levine="Global Temperature Deviations") Jan, 2012 Page 2 #12;Statistics 520: Time Series and Applications Dr. Levine Purdue

Levine, Michael "Mihail"

334

Statistics 598K: Financial Time Series Purdue University  

E-print Network

Statistics 598K: Financial Time Series Dr. Levine Purdue University Fall 2012 General moving)Zt Sept, 2012 Page 1 #12;Statistics 598K: Financial Time Series Dr. Levine Purdue University Fall 2012 of MA(1) cuts off at the lag 1 Sept, 2012 Page 2 #12;Statistics 598K: Financial Time Series Dr. Levine

Levine, Michael "Mihail"

335

Comparison of GPS station position and loading displacement model time series. What can we learn?  

Microsoft Academic Search

The International GNSS service (IGS) analysis centers have started to reanalyze GPS data to deliver to the scientific community fully self-consistent and improved products: station positions, satellites orbits, clocks and Earth Rotation parameters. After removing the linear trend mostly due to tectonic motion from the time series of GPS station positions, we suggest to compare the remaining non-linear part to

X. Collilieux; T. van Dam; L. Métivier; Z. Altamimi; J. Ray

2009-01-01

336

Hydroxyl time series and recirculation in turbulent nonpremixed swirling flames  

SciTech Connect

Time-series measurements of OH, as related to accompanying flow structures, are reported using picosecond time-resolved laser-induced fluorescence (PITLIF) and particle-imaging 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 time-series 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)

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)

2006-10-15

337

High spatial resolution water level time series in the Florida Everglades wetlands using multi-track ALOS PALSAR data  

NASA Astrophysics Data System (ADS)

Wetland InSAR (Interferometric Synthetic Aperture Radar) observations provide very high-resolution maps of water level changes that cannot be obtained by any terrestrial technique. We recently developed the Small Temporal Baseline Subset (STBAS) approach, which combines single-track InSAR and stage (water level) observations to generate high-resolution absolute water level time series maps. However, the temporal resolution of produced time series is coarse compared with in-situ stage observation and, hence, the usefulness of these maps is rather limited. To compensate for the low temporal resolution weakness of space-based water level time series, we propose using a multi-track STBAS technique, which utilizes all available Synthetic Aperture Radar (SAR) observations acquired over a certain wetland area. We use a four-year long L-band ALOS PALSAR dataset acquired during 2007-2011 to test the proposed method over the Water Conservation Area 1 (WCA1) in the Everglades wetlands, south Florida (USA). A total of 37 images acquired with four tracks were collected. Daily water level data at 12 stage stations, which are monitored by the Everglades Depth Estimation Network (EDEN) in WCA1 area, were used to calibrate the InSAR-derived water level data. The proposed multi-track approach yielded a significant improvement of temporal resolution, which is dependent on the SAR satellite revisit cycle. Instead of the 46-day repeat orbit of ALOS, the multi-track method produces water level maps with temporal resolution of only 7 days. A quality control analysis of the methods indicates that the average root mean square error (RMSE) of the differences between stage water level and retrieved water level by InSAR technique is 4.0 cm. The end products of absolute water level time series with improved temporal and very high spatial resolutions can be used as excellent constraints for high-resolution wetland flow models. Furthermore, the next generation of SAR satellites has been designed with shorter revisit cycles, which will provide temporally denser maps of water level changes. Fig. 1. Comparison between stage (solid line) and InSAR (circle: 148 track, cross: 149 track, diamond: 464 track and square: 465 track) determined water level time series.

Hong, S.; Wdowinski, S.

2013-05-01

338

High-Resolution Imaging of Asteroids/Satellites  

NASA Astrophysics Data System (ADS)

We propose to make high-resolution observations of asteroids using two separate observational paths. We request LGS AO on Keck, as part of our ongoing program to measure size, 3D shape, and pole position, and to search for satellites. Second, we wish to make use of the new capability for speckle imaging on Gemini-N. We have demonstrated that AO imaging allows determination of the pole/dimensions in 1 or 2 nights, rather than the years of observations with lightcurve inversion techniques that only yield poles and axial ratios, not true dimensions. Detection of new satellites allows an accurate mass determination. Accurately determining the volume from the often-irregular shape allows us to derive densities to greater precision in cases where the mass is known. Satellites also provide a real-life lab for testing collisional models. We have demonstrated the tremendous fidelity of our shape/sizes of asteroids, and have pioneered asteroid satellite detection. The new DSSI instrument provides a potentially game-changing opportunity by pushing diffraction-limited imaging into the visible region, where the resolution will be roughly twice what we can get at Keck in the NIR. We will apply both techniques to determination of sizes of asteroids and search for binaries, particularly among understudied populations such as the NEOs and Trojans.

Merline, William J.; Tamblyn, Peter M.; Carry, Benoit; Drummond, Jack; Conrad, Al; Howell, Steve B.; Christou, Julian; Chapman, Clark R.; Dumas, Christophe

2013-08-01

339

Using Progressive Resolution to Visualize large Satellite Image dataset  

NASA Astrophysics Data System (ADS)

Unidata's Integrated Data Viewer (IDV) is a Java-based software application that provides new and innovative ways of displaying satellite imagery, gridded data, and surface, upper air, and radar data within a unified interface. Progressive Resolution (PR) is a advanced feature newly developed in the IDV. When loading a large satellite dataset with PR turned on, the IDV calculates the resolution of the view window, sets the magnification factors dynamically, and loads a sufficient amount of the data to generate an image at the correct resolution. A rubber band box (RBB) interface allows the user to zoom in/out or change the projection, forcing the IDV to recalculate the magnification factors and get higher/lower resolution data. This new feature improves the IDV memory usage significantly. In the preliminary test, loading 100 time steps of GOES-East 1 km 0.65 visible image data (100 X 10904 X 6928) with PR, both memory and CPU usage are comparable to generating a single time-step display at full resolution (10904 X 6928), and the quality of the resulting image is not compromised. The PR feature is currently available for both satellite imagery and gridded datasets, and will be expanded to other datasets. In this presentation we will present examples of PR usage with large satellite datasets for academic investigations and scientific discovery.

ho, yuan; ramanmurthy, mohan

2014-05-01

340

Unsupervised Feature Learning for High-Resolution Satellite Image Classification  

SciTech Connect

The rich data provided by high-resolution satellite imagery allow us to directly model geospatial neighborhoods by understanding their spatial and structural patterns. In this paper we explore an unsupervised feature learning approach to model geospatial neighborhoods for classification purposes. While pixel and object based classification approaches are widely used for satellite image analysis, often these approaches exploit the high-fidelity image data in a limited way. In this paper we extract low-level features to characterize the local neighborhood patterns. We exploit the unlabeled feature measurements in a novel way to learn a set of basis functions to derive new features. The derived sparse feature representation obtained by encoding the measured features in terms of the learned basis function set yields superior classification performance. We applied our technique on two challenging image datasets: ORNL dataset representing one-meter spatial resolution satellite imagery representing five land-use categories and, UCMERCED dataset consisting of 21 different categories representing sub-meter resolution overhead imagery. Our results are highly promising and, in the case of UCMERCED dataset we outperform the best results obtained for this dataset. We show that our feature extraction and learning methods are highly effective in developing a detection system that can be used to automatically scan large-scale high-resolution satellite imagery for detecting large-facility.

Cheriyadat, Anil M [ORNL

2013-01-01

341

Multifractal modelling of rainfall time series  

NASA Astrophysics Data System (ADS)

The literature produced in the last thirty years about the high space-time variability of rainfall deals with the development of stochastic models capable of representing the non-linearity and intermittence of rainfall to downscale information on rainfall fields to spatial and temporal scales useful for hydrological models, i.e. transferring to finer scales the information on rainfall observed or forecasted at large scales. Traditionally, these models are based upon point processes (e.g. Waymire and Gupta, 1981, Rodriguez-Iturbe et al., 1986). However, this approach may involve a large number of parameters in modelling the process, leading to several problems in parameter estimation. Another approach to this problem is based on the empirical detection of some regularities in hydrological observations, such as the scale-invariance properties of rainfall (e.g. Lovejoy and Schertzer, 1985). These models assume a power law dependence of all statistical moments on the scale of aggregation. Scaling properties can provide simple relationships to link the statistical distribution of the rainfall process at different spatial and temporal scales, in the ranges of which the power-low assumption can be verified (Marani, 2003). This work focuses on the analysis of the scaling properties of rainfall time series from a high density rain gauge network covering the Rome's urban area. The network consists of 24 sites, and the gauge record at each site has 10-minute time resolution and about 16-year length (1992-2007). The aim of the study is the identification of temporal scaling regimes, their ranges of validity, and the evaluation of the corresponding scaling properties. REFERENCES Lovejoy S. and Schertzer D. Generalized scale invariance in the atmosphere and fractal models of rain. Water Resour. Res., 21(8), 1233-1250, 1985. Marani, M. (2003) On the correlation structure of continuous and discrete point rainfall, Water Resour. Res., 39(5), 1128, doi:10.1029/2002WR001456. Rodriguez-Iturbe I., Cox D. and Eagleson P.S. Spatial modelling of total storm rainfall. Proc. R. Soc. London, A403, 27-50, 1986. Waymire E. and Gupta V.K. The mathematical structure of rainfall representations. Water Resour. Res., 17 (5), 1261-1294, 1981.

Volpi, E.; Lombardo, F.; Napolitano, F.

2009-09-01

342

High performance image processing of satellite images using graphics processing units  

Microsoft Academic Search

This paper presents preliminary results of studies concerning possibilities of high performance processing of satellite images using graphics processing units. Even if numerical procedures used for this kind of computation are not complicated and fast, size of typical satellite scene makes them time consuming. This problem is especially troublesome when many, sometimes hundredths of scenes, have to be processed in

Michal Rumanek; Tomasz Danek; Andrzej Lesniak

2011-01-01

343

Generation of long-term time series of remote sensing data using ESA's GPOD system  

NASA Astrophysics Data System (ADS)

Several authors have shown that the analysis of time series of remote sensing data is able to characterize the properties of different earth systems. They have used different techniques, ARIMA, Fourier Analysis and others, to estimate cyclical and trend variations from the information stored in the time series. Most systems in earth cycle due to seasonal changes in the flow of energy and/or matter, ecosystems cycle due to seasonal changes in evapotranspiration, day length and temperature. Time series analysis can characterized the period, amplitude and offset of the cycle. Trend analysis, on the other hand, can be used to detect permanent changes in certain systems. Changes in sea surface temperature or the artic ice pack due to climate change would belong to this category. Performing this analysis requires data with a good temporal resolution, usually in the range of days and a good temporal extent, usually in the multiyear timescale. As a result users have to process a big set of satellite images, sometimes in the order of thousands, to extract the information required. This processing consumes a great amount of time and resources due to the big amount of data and computer power involved. To facilitate the generation of long-term time series of remote sensing data the European Space Agency has developed a system able to extract all the information available for a small area from the MEdium Resolution Imaging Spectrometer (MERIS) onboard ENVISAT in an easily accessible format. This service allows the user to specify an area of interest of rectangular or circular shape giving its geographical location and its size, specify the period of time that he is interested in and obtain several files with all the information available from the MERIS sensor for this location. For each MERIS product the information is given in two formats. One is highly portable following the XML standard. Output is also given in Google Earth and Excel formats allowing for a fast and easy analysis of the data recovered. The service generates also several summaries of all the products processed and stores them in easily usable formats. This service is able to generate year long time series processing several terabytes of data in the order of a couple of hours. It has already been used by several research groups proving its utility. The European Southern Observatory (ESO) used it to survey potential sites for the deploying of ESO's next generation of very large telescopes (E-ELT). Currently it's being used by the Max Planck Institute to characterize their two telescope sites at Mount Graham (US) and Calar Alto (Spain) The system is powered by ESA's GRID Processing on Demand infrastructure. This is a GRID-based operational environment able to process large amounts of remote sensing data in an efficient way. The access to ESA data catalogue coupled with high-performance and sizeable computing resources managed by GRID technologies, enables the user to develop applications that were not feasible till now.

Rubio, M. A.; Colin, O.; Mathot, E.

2009-04-01

344

MISR Browse Images: Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS)  

MISR Browse Images: Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) These MISR Browse images provide ... the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) field campaign. CLAMS focused on understanding pieces of the ...

2013-03-22

345

IMAGE DEBLURRING, SPECTRUM INTERPOLATION AND APPLICATION TO SATELLITE IMAGING  

Microsoft Academic Search

This paper deals with two complementary methods in noisy image deblurring: a nonlinear shrinkage of wavelet-packets coecients called FCNR and Rudin-Osher-Fatemi's variational method. The FCNR has for objective to obtain a restored image with a white noise. It will prove to be very ecient to restore an image after an invertible blur but limited in the opposite situation. Whereas the

Sylvain Durand; Bernard Roug

2000-01-01

346

Flood Identification from Satellite Images Using Artificial Neural Networks  

NASA Astrophysics Data System (ADS)

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 satellite; hence, the most appropriate way for investigating flooding extent is to use Synthetic Aperture Radar (SAR) satellite. In this study, back-propagation neural network (BPNN) model and multivariate linear regression (MLR) model are built to identify the flooding extent from SAR satellite images. 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 images of the non-flooding and flooding periods, and The inputs are the difference between the RCS values of two images 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 image 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 satellite images has been improved a lot and the correct percentages increases up to more than 90%.

Chang, L.; Kao, I.; Shih, K.

2011-12-01

347

Assessment of InSAR time series quality using MODIS data  

NASA Astrophysics Data System (ADS)

Observations of ground motion from InSAR are complicated by error sources that are well documented by the user community. One significant source is correlated noise due to signal propagation delays through the stratified and turbulent atmosphere. In many cases, atmospheric-induced phase delays may be as large as 3cm or more and are often correlated with short- and long-wavelength topographic features. The correlation of atmospheric noise with topography is especially problematic investigations of tectonic signals that often also mimic topography, such as anticlinal uplift or interseismic motion across basin-bounding faults. Theoretically, InSAR time series techniques reduce the influence of correlated atmospheric noise - the sign of atmospheric noise should be random and cancel out when many independent SAR acquisitions are used to build a time series. In most locations, however, InSAR observation histories are not ideal, with unevenly spaced acquisitions in time, seasonal biases, and insufficient numbers (< 50 acquisitions) to fully characterize or average out the noise. In this work, we use independent observations of precipitable water vapor in the atmosphere to characterize atmospheric noise and how it propagates into InSAR time series. We use the Moderate Resolution Imaging Spectroradiometer (MODIS) precipitable water vapor product, which is acquired daily worldwide. We show that while time series techniques do reduce the impact of correlated atmospheric noise, apparent signals over both long- (>100 km) and short-wavelengths (>100 km) are expected to propagate into the final time series for several examples of real InSAR data acquisition histories. We show that in some cases, abrupt changes in InSAR-derived time series can be correlated to individual storm events apparent in both the MODIS imagery and final InSAR time series product. We present a stochastic approach to estimate the magnitude of errors in time series caused by correlated atmospheric noise, based on MODIS observations during the same time frame. Using a Monte Carlo approach, we generate multiple MODIS time series with acquisition date histories similar to that of the InSAR time series. We then use the population of MODIS time series to assess the variability in apparent signal at each SAR acquisition date. The variability is then used to assign error bounds to the time series. This method captures variability in signals induced by both seasonal weather fluctuations and individual, multi-day storm events. We explore examples of time series spanning the Mojave Desert, California, and the southern Zagros Mountains of Iran.

Lohman, R.; Barnhart, W. D.

2012-12-01

348

Optimized satellite image compression and reconstruction via evolution strategies  

NASA Astrophysics Data System (ADS)

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 satellite image 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 satellite images by an average of 33.78% (1.79 dB), while maintaining the average information entropy (IE) of compressed images 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 images 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 images without substantial loss of compression capability over a broad range of image classes.

Babb, Brendan; Moore, Frank; Peterson, Michael

2009-05-01

349

SATELLITE IMAGE REGISTRATION FOR ATTITUDE ESTIMATION WITH A CONSTRAINED POLYNOMIAL MODEL  

E-print Network

, pushbroom camera, piecewise polynomial model 1. INTRODUCTION Satellite image processing has been widelySATELLITE IMAGE REGISTRATION FOR ATTITUDE ESTIMATION WITH A CONSTRAINED POLYNOMIAL MODEL R, EADS Astrium 655 avenue de l'Europe, 38330 Montbonnot, France ABSTRACT Satellite image registration

Paris-Sud XI, Université de

350

SELECTION OF THE MOST SUITABLE SIZES OF GROUND CONTROL POINTS IN THE SATELLITE IMAGES  

Microsoft Academic Search

Nowadays, satellite images have been used for many applications intensively. Using of the digital satellite images in relevant approaches may give more accurate ideas about the researched fields. Besides, different methods could be used for derivation of maps from relevant digital data in many scientific disciplines. One of these methods is to use satellite images. The most important reason of

H. M. Yilmaz; M. Yakar; O. Mutluoglu; F. Yildiz

351

Classification of multi-spectral satellite image data using improved NRBF neural networks  

E-print Network

, classification, satellite image processing 1. INTRODUCTION An efficient technique for improvingClassification of multi-spectral satellite image data using improved NRBF neural networks Xiaoli that this new model may be an effective method for classification of multi- spectral satellite image data

Michel, Howard E.

352

A New System to Perform Unsupervised and Supervised Classification of Satellite Images from Google Maps  

E-print Network

A New System to Perform Unsupervised and Supervised Classification of Satellite Images from Google of satellite images from Google Maps. The system has been developed using the SwingX-WS library Systems ENVI package. Keywords: Satellite image classification, Google Maps. 1. INTRODUCTION The wealth

Plaza, Antonio J.

353

PREDICTING GROUND-BASED AEROSOL OPTICAL DEPTH WITH SATELLITE IMAGES VIA GAUSSIAN PROCESSES  

E-print Network

PREDICTING GROUND-BASED AEROSOL OPTICAL DEPTH WITH SATELLITE IMAGES VIA GAUSSIAN PROCESSES Goo Jun satellite multispectral images, and to select the most informative ground-based sites by active learning. Satellite images provide spatial and temporal information in addition to the spectral features

Obradovic, Zoran

354

A Multi-Scale Detection Technique for Anomaly on Ocean Surface Using Optical Satellite Images  

Microsoft Academic Search

Using satellite images for monitoring oceanic surface has become popular recently. One of the striking feature can be detected from satellite image is the anomalous phenomenon on oceanic surface. In general, it is easy to observe the diversified anomalies, caused by abrupt change of the reflectance on oceanic surface, on the optical satellite images. Among them, the anomaly caused by

Chi-Farn Chen; Li-Yu Chang

355

Spacecraft design project: High temperature superconducting infrared imaging satellite  

NASA Technical Reports Server (NTRS)

The High Temperature Superconductor Infrared Imaging Satellite (HTSCIRIS) is designed to perform the space based infrared imaging and surveillance mission. The design of the satellite follows the black box approach. The payload is a stand alone unit, with the spacecraft bus designed to meet the requirements of the payload as listed in the statement of work. Specifications influencing the design of the spacecraft bus were originated by the Naval Research Lab. A description of the following systems is included: spacecraft configuration, orbital dynamics, radio frequency communication subsystem, electrical power system, propulsion, attitude control system, thermal control, and structural design. The issues of testing and cost analysis are also addressed. This design project was part of the course Advanced Spacecraft Design taught at the Naval Postgraduate School.

1991-01-01

356

A Near Lossless Wavelet-Based Compression Scheme for Satellite Images  

Microsoft Academic Search

In this paper, a near lossless image compression algorithm is presented for high quality satellite image compression. The proposed algorithm makes use of the recommendation for image data compression from the Consultative Committee for Space Data Systems (CCSDS) and specific residue image bit-plane compensation. Comparing with the recommendation for satellite image compression from CCSDS, the proposed algorithm can reconstruct near

Chien-wen Chen; Tsung-ching Lin; Shi-huang Chen; Trieu-kien Truong

2009-01-01

357

Segmentation of Multispectral Satellite Images Based on Watershed Algorithm  

Microsoft Academic Search

In this paper, a two-step segmentation algorithm is proposed based on watershed transform to segment multi-spectral satellite images. The first step is to use watershed segmentation to gain the initial over-segmented regions and the next one is region merging using a strategy of minimizing the overall heterogeneity increased within segments at each merging step. Textural, color and shape information of

Sheng Chen; Jiancheng Luo; Zhanfeng Shen; Xiaodong Hu; Lijing Gao

2008-01-01

358

Automatic analysis of stereoscopic image pairs from GOES satellites  

NASA Technical Reports Server (NTRS)

An algorithm for automatic analysis of stereoscopic images is applied to stereo pairs of severe local storms and hurricanes observed by two GOES satellites. The automatically derived height fields and manual analyses are compared. It is found that the automatic analysis produces a more detailed structure in less time than manual analysis, although the two methods have similar quality. In areas where the features are very small, however, it is suggested that manual analysis is superior.

Hasler, A. F.; Strong, J.; Morris, R.; Pierce, H.

1988-01-01

359

Short time information in GPS time series  

NASA Astrophysics Data System (ADS)

This paper presents adjustment's results of the Polish Active Geodetic Network (ASG-EUPOS). ASG-EUPOS is the multifunctional precise satellite positioning system established by the Head Office of Geodesy and Cartography in 2008. It consists of 84 Polish sites with GPS module, 14 Polish sites with GPS/GLONASS module and 20 foreign sites. The adjusted network consisted of over 100 stations, the period covered observations collected from June 2008. The method of adjustment elaborated in the CAG, which is the newest, seventeenth EPN LAC (EPN Local Analysis Centre) established at the end of 2009, is similar with applied in EPN. It is based on the Bernese 5.0 software. The difference to the EPN's solutions lies in the resolution time of adjustment. In the presented research the 1-hour sampling rate with 3-hour windowing is applied. This allows us to make the interpretations concerning short time information in GPS coordinates series. The time span (over 1.5 year) permits the separation between the pure dynamic phenomena (tides) and thermal oscillations in the diurnal and sub-diurnal frequency bands. The presentation contains also the plans for multidimensional applications of the dense national active GNSS networks.

Araszkiewicz, Andrzej; Bogusz, Janusz; Figurski, Mariusz

2010-05-01

360

State estimation and absolute image registration for geosynchronous satellites  

NASA Technical Reports Server (NTRS)

Spacecraft state estimation and the absolute registration of Earth images acquired by cameras onboard geosynchronous satellites are described. The basic data type of the procedure consists of line and element numbers of image points called landmarks whose geodetic coordinates, relative to United States Geodetic Survey topographic maps, are known. A conventional least squares process is used to estimate navigational parameters and camera pointing biases from observed minus computed landmark line and element numbers. These estimated parameters along with orbit and attitude dynamic models are used to register images, using an automated grey level correlation technique, inside the span represented by the landmark data. In addition, the dynamic models can be employed to register images outside of the data span in a near real time mode. An important application of this mode is in support of meteorological studies where rapid data reduction is required for the rapid tracking and predicting of dynamic phenomena.

Nankervis, R.; Koch, D. W.; Sielski, H.

1980-01-01

361

The geostationary operational environmental satellite /GOES/ imaging communication system  

NASA Technical Reports Server (NTRS)

The SMS/GOES Satellite obtains day and night weather information from synchronous geostationary orbit by means of (1) earth imaging, (2) collection of environmental data from ground based sensors, platforms, and (3) monitoring of the space environment. SMS-1 and SMS-2 have been in orbit for 17 months and 8 months, respectively, and are presently taking full earth disk images in the visible and infrared every 30 minutes. SMS-1 is positioned to cover the eastern portion of the U.S. while SMS-2 is positioned to cover the western portion. This paper provides a general overview of the imaging communication portions of the SMS/GOES, related to the image data encoding and transmission as well as the method of the data time multiplexing and the manner in which the scan line to line synchronization is achieved.

Baker, W. L.; Savides, J.

1975-01-01

362

GOES-R ABI: Next Generation Satellite Imaging  

NSDL National Science Digital Library

This extension of the COMET module âGOES-R: Benefits of Next Generation Environmental Monitoringâ focuses on the ABI instrument, the satellite's 16-channel imager. With increased spectral coverage, greater spatial resolution, more frequent imaging, and improved image pixel geolocation and radiometric performance, the ABI will bring significant advancements to forecasting, numerical weather prediction, and climate and environmental monitoring. The first part of the module introduces the ABI's key features and improvements over earlier GOES imagers. The second section lets users interactively explore the ABI's 16 channels. The third section contains movies that show the advancements that the ABI will bring to the following application areas: convection, flooding, wildfires, land cover, hurricanes, climate, air quality, aviation, fog and low visibility, and coastal and marine. The final section contains additional resources pertaining to the ABI. The module has numerous takeaways, including ten application movies and an interactive spectrum.

Comet

2013-02-19

363

Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images  

NASA Astrophysics Data System (ADS)

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

Chiang, Y.; Chen, K.

2013-12-01

364

On correlations and fractal characteristics of time series  

E-print Network

Correlation analysis is convenient and frequently used tool for investigation of time series from complex systems. Recently new methods such as the multifractal detrended fluctuation analysis (MFDFA) and the wavelet transform modulus maximum method (WTMM) have been developed. By means of these methods (i) we can investigate long-range correlations in time series and (ii) we can calculate fractal spectra of these time series. But opposite to the classical tool for correlation analysis - the autocorrelation function, the newly developed tools are not applicable to all kinds of time series. The unappropriate application of MFDFA or WTMM leads to wrong results and conclusions. In this article we discuss the opportunities and risks connected to the application of the MFDFA method to time series from a random number generator and to experimentally measured time series (i) for accelerations of an agricultural tractor and (ii) for the heartbeat activity of {\\sl Drosophila melanogaster}. Our main goal is to emphasize ...

Vitanov, N K; Yankulova, E D; Vitanov, Nikolay K.; Sakai, kenschi; Yankulova, Elka D.

2005-01-01

365

Automated analysis of brachial ultrasound time series  

NASA Astrophysics Data System (ADS)

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 imaging 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 image features, to recognize and minimize the noise effect. Experimental results showed the method's potential for clinical usage in the epidemiological studies.

Liang, Weidong; Browning, Roger L.; Lauer, Ronald M.; Sonka, Milan

1998-07-01

366

The determination of physical and dynamical parameters of Pluto/Charon and binary asteroids by least-square formation of a matched filter for a time series of images. I - The operational theory  

NASA Technical Reports Server (NTRS)

A theory is derived for the determination of the masses, radii, and orbital elements of the Pluto/Charon, or similar, system based on the prediction of an image distribution over space and time and its comparison with observation. The comparison may be ultimately through the theory of least squares or the application of a matched filter to the observations as a three-dimensional signal stream at an initial or intermediate state. The theory is an approximation correct to fifth order in the diameters of celestial bodies. The theory of astronomical seeing that is used is based on Kolmogorov turbulence in the long-exposure limit. The images must be photometric. Linear tracking errors that can be removed are preferable to either automatic or manual guiding, in the collection of candidate observations.

Wildey, R. L.

1985-01-01

367

14.384 Time Series Analysis, Fall 2002  

E-print Network

Theory and application of time series methods in econometrics, including representation theorems, decomposition theorems, prediction, spectral analysis, estimation with stationary and nonstationary processes, VARs, unit ...

Kuersteiner, Guido M.

368

Hidden Markov model segmentation of hydrological and enviromental time series  

E-print Network

Motivated by Hubert's segmentation procedure we discuss the application of hidden Markov models (HMM) to the segmentation of hydrological and enviromental time series. We use a HMM algorithm which segments time series of several hundred terms in a few seconds and is computationally feasible for even longer time series. The segmentation algorithm computes the Maximum Likelihood segmentation by use of an expectation / maximization iteration. We rigorously prove algorithm convergence and use numerical experiments, involving temperature and river discharge time series, to show that the algorithm usually converges to the globally optimal segmentation. The relation of the proposed algorithm to Hubert's segmentation procedure is also discussed.

Ath. Kehagias

2002-06-25

369

Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites.  

PubMed

This studypresents a remote sensing application of using time series Landsat satellite images for monitoring the Trail Road and Nepean municipal solid waste (MSW) disposal sites in Ottawa, Ontario, Canada. Currently, the Trail Road landfill is in operation; however, during the 1960s and 1980s, the city relied heavily on the Nepean landfill. More than 400 Landsat satellite images were acquired from the US Geological Survey (USGS) data archive between 1984 and 2011. Atmospheric correction was conducted on the Landsat images in order to derive the landfill sites' land surface temperature (LST). The findings unveil that the average LST of the landfill was always higher than the immediate surrounding vegetation and air temperature by 4 to 10 °C and 5 to 11.5 °C, respectively. During the summer, higher differences of LST between the landfill and its immediate surrounding vegetation were apparent, while minima were mostly found in fall. Furthermore, there was no significant temperature difference between the Nepean landfill (closed) and the Trail Road landfill (active) from 1984 to 2007. Nevertheless, the LST of the Trail Road landfill was much higher than the Nepean by 15 to 20 °C after 2007. This is mainly due to the construction and dumping activities (which were found to be active within the past few years) associated with the expansion of the Trail Road landfill. The study demonstrates that the use of the Landsat data archive can provide additional and viable information for the aid of MSW disposal site monitoring. PMID:25150051

Yan, Wai Yeung; Mahendrarajah, Prathees; Shaker, Ahmed; Faisal, Kamil; Luong, Robin; Al-Ahmad, Mohamed

2014-12-01

370

Image-based derivation of aerosol optical depth to correct the atmospheric effect for satellite image  

Microsoft Academic Search

An image-based atmospheric correction model for a satellite image is proposed. By assuming Junge size distributed aerosol in the atmosphere and feeding back the new Junge parameter, not only the aerosol optical depth but also the Junge parameter, single scattering albedo and phase function can be iteratively derived and converged from digital counts of dense-dark vegetation (DDV) in the green

C. H. Liu; A. J. Chen; G. R. Liu

1995-01-01

371

An image-based retrieval algorithm of aerosol characteristics and surface reflectance for satellite images  

Microsoft Academic Search

An image-based retrieval algorithm of aerosol characteristics and surface reflectance for satellite images is proposed. By assuming the Junge size distributed aerosol in the atmosphere and feeding back the new Junge parameter, not only the aerosol optical depth but also the Junge parameter, single-scattering albedo and phase function can be iteratively derived and converged from digital counts of dense dark

C. H. LIU; A. J. CHEN; G. R. LIU

1996-01-01

372

On the optimization of the satellite imaging Mikael Carlavan, Laure Blanc-Feraud, Marc Antonini, Carole Thiebaut, Christophe Latry  

E-print Network

does not alter the quality of the image. Fig. 1. Processing chain for satellite imaging. Usually1 On the optimization of the satellite imaging chain Mikael Carlavan, Laure Blanc-F´eraud, Marc on the global optimization of the satellite imaging chain. The theoretical analysis of the satellite imaging

Boyer, Edmond

373

MPEG-7 Descriptors for Earth Observation Satellite Images  

NASA Astrophysics Data System (ADS)

The amount of digital multimedia information has experienced a spectacular growth during the last years thanks to the advances on digital systems of image, video and audio acquisition. As a response to the need of organising all this information, ISO/IEC has developed a new standard for multimedia content description called MPEG-7. Among other topics, MPEG-7 defines a set of multimedia descriptors that can be automatically generated using signal processing techniques. Earth Observation Satellites generate large quantities of images stored on enormous databases that can take advantage of the new standard. An automatic indexation of these images using MPEG-7 metadata can improve their contents management as well as simplify interaction between independent databases. This paper gives an overall description on MPEG-7 standard focusing on the low-level Visual Descriptors. These descriptors can be grouped into four categories: color, texture, shape and motion. Visual Color Descriptors represent the colour distribution of an image in terms of a specified colour space. Visual Texture Descriptors define the visual pattern of an image according to its homogenities and non-homogenities. Visual Shape Descriptors describe the shape of 2D and 3D objects being, at the same time, invariant to scaling, rotation and translation. Motion Descriptors give the essential characteristics of objects and camera motions. These descriptors can be used individually or in combination to index and retrieve satellite images of the Earth from a database. For example, oceans and glaciars can be discerned based on their Colour Descriptors, also cities and deserts based on the Texture Descriptors, island images can be grouped using the Shape Descriptors, and cyclone trajectories studied and compared using the Motion Descriptors.

Nieto, X. Giro I.; Marques Acosta, F.

374

Ice Sheet Change Detection by Satellite Image Differencing  

NASA Technical Reports Server (NTRS)

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

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

2010-01-01

375

ERK'2007, Portoroz, B:191-194 191 Motion correction of contrast-enhanced MRI time series of kidney  

E-print Network

ERK'2007, Portoroz, B:191-194 191 Motion correction of contrast-enhanced MRI time series of kidney In this paper we focus on motion correction of contrast enhanced kidney MRI time series, which is an important: motion correction, image registration, contrast-enhanced MRI. 1 Introduction The kidneys maintain normal

Kovacic, Stanislav

376

Use of Geostationary Satellite Images for Interactive Meteorological Analysis.  

NASA Astrophysics Data System (ADS)

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 satellite 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 images. 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 image, 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 satellite image. 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 Satellite Image 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.

van Heerden, Johan

377

Mapping afforestation and deforestation from 1974 to 2012 using Landsat time-series stacks in Yulin District, a key region of the Three-North Shelter region, China.  

PubMed

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 time-series satellite images. In this paper, 30 Landsat MSS/TM/ETM+ epochs from 1974 to 2012 were collected, and the high-quality ground surface reflectance (GSR) time-series images 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 time-series Landsat GSR images 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 time-series of Landsat images for detecting forest changes and estimating tree age for the artificial forest in a semi-arid zone strongly influenced by human activities. PMID:23813096

Liu, Liangyun; Tang, Huan; Caccetta, Peter; Lehmann, Eric A; Hu, Yong; Wu, Xiaoliang

2013-12-01

378

Mapping Canopy Damage from Understory Fires in Amazon Forests Using Annual Time Series of Landsat and MODIS Data  

NASA Technical Reports Server (NTRS)

Understory fires in Amazon forests alter forest structure, species composition, and the likelihood of future disturbance. The annual extent of fire-damaged forest in Amazonia remains uncertain due to difficulties in separating burning from other types of forest damage in satellite data. We developed a new approach, the Burn Damage and Recovery (BDR) algorithm, to identify fire-related canopy damages using spatial and spectral information from multi-year time series of satellite data. The BDR approach identifies understory fires in intact and logged Amazon forests based on the reduction and recovery of live canopy cover in the years following fire damages and the size and shape of individual understory burn scars. The BDR algorithm was applied to time series of Landsat (1997-2004) and MODIS (2000-2005) data covering one Landsat scene (path/row 226/068) in southern Amazonia and the results were compared to field observations, image-derived burn scars, and independent data on selective logging and deforestation. Landsat resolution was essential for detection of burn scars less than 50 ha, yet these small burns contributed only 12% of all burned forest detected during 1997-2002. MODIS data were suitable for mapping medium (50-500 ha) and large (greater than 500 ha) burn scars that accounted for the majority of all fire-damaged forest in this study. Therefore, moderate resolution satellite data may be suitable to provide estimates of the extent of fire-damaged Amazon forest at a regional scale. In the study region, Landsat-based understory fire damages in 1999 (1508 square kilometers) were an order of magnitude higher than during the 1997-1998 El Nino event (124 square kilometers and 39 square kilometers, respectively), suggesting a different link between climate and understory fires than previously reported for other Amazon regions. The results in this study illustrate the potential to address critical questions concerning climate and fire risk in Amazon forests by applying the BDR algorithm over larger areas and longer image time series.

Morton, Douglas C.; DeFries, Ruth S.; Nagol, Jyoteshwar; Souza, Carlos M., Jr.; Kasischke, Eric S.; Hurtt, George C.; Dubayah, Ralph

2011-01-01

379

The Research of Satellite Cloud Image Recognition Base on Variational Method and Texture Feature Analysis  

Microsoft Academic Search

Recently, the development of satellite cloud image processing technology has become very quick; the research aspects concentrate on judge the cloud type and classify the cloud mainly. These image processing methods relate to the subject category like image processing and pattern recognition etc; it has become one of the fields of most quickly development in the research of satellite image

Wei Shangguan; Yanling Hao; Zhizhong Lu; Peng Wu

2007-01-01

380

DETECTION AND EXTRACTION OF ROAD NETWORKS FROM HIGH RESOLUTION SATELLITE IMAGES  

E-print Network

DETECTION AND EXTRACTION OF ROAD NETWORKS FROM HIGH RESOLUTION SATELLITE IMAGES Renaud P of road extraction from new high resolution satellite images. The proposed algo- rithm is divided in two from remotely sensed images has been the purpose of many works in the image processing field

Boyer, Edmond

381

Automatic Registration of Satellite Images LEILA M. G. FONSECA1 MAX H. M. COSTA2  

E-print Network

, satellite image. 1 Introduction Image registration is the process of matching two im- ages soAutomatic Registration of Satellite Images LEILA M. G. FONSECA1 MAX H. M. COSTA2 1National registration is one of the basic image processing operations in remote sensing. With the increase in the number

382

Automatic Registration of Satellite Images LEILA M. G. FONSECA 1 MAX H. M. COSTA 2  

E-print Network

, satellite image. 1 Introduction Image registration is the process of matching two im­ ages soAutomatic Registration of Satellite Images LEILA M. G. FONSECA 1 MAX H. M. COSTA 2 1 National registration is one of the basic image processing operations in remote sensing. With the increase in the number

383

Evaluating the Sensitivity of Image Fusion Quality Metrics to Image Degradation in Satellite Imagery  

Microsoft Academic Search

Referring to the high potential of topographic satellite in collecting high resolution panchromatic imagery and high spectral,\\u000a multi spectral imagery, the purpose of image fusion is to produce a new image data with high spatial and spectral characteristics.\\u000a It is necessary to evaluate the quality of fused image by some quality metrics before using this product in various applications.\\u000a Up

Farhad Samadzadegan; Farzaneh DadrasJavan

384

Multi sensor satellite imagers for commercial remote sensing  

NASA Astrophysics Data System (ADS)

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

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

2005-10-01

385

Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models  

Microsoft Academic Search

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) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying lengths (T = 25, 50, 75, 100, 125)

Larry R. Price

2012-01-01

386

On correlations and fractal characteristics of time series  

Microsoft Academic Search

Correlation analysis is convenient and frequently used tool for investigation of time series from complex systems. Recently new methods such as the multifractal detrended fluctuation analysis (MFDFA) and the wavelet transform modulus maximum method (WTMM) have been developed. By means of these methods (i) we can investigate long-range correlations in time series and (ii) we can calculate fractal spectra of

Nikolay K. Vitanov; kenschi Sakai; Elka D. Yankulova

2005-01-01

387

ANCOVA Procedures in Time-Series Experiments: An Illustrative Example.  

ERIC Educational Resources Information Center

A statistical model for analysis of multiple time-series observation is briefly outlined. The model incorporates a change parameter corresponding to intervention or interruption of the dependent series. The additional time-series are included in the model as covariates. The practical application of the procedure is illustrated with traffic…

Willson, Victor L.

388

The QuakeSim System for GPS Time Series Analysis  

Microsoft Academic Search

We present a system for analysis of GPS time series data available to geosciences users through a web services \\/ web portal interface. The system provides two time series analysis methods, one based on hidden Markov model (HMM) segmentation, the other based on covariance descriptor analysis (CDA). In addition, it provides data pre-processing routines that perform spike noise removal, linear

R. A. Granat; X. Gao; M. Pierce; J. Wang

2010-01-01

389

A Compendium of Reproducible Research about Time Series Analysis  

Microsoft Academic Search

This document can be used as an introductory, interactive case study about Time Series 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 time series into its underlying components (trend,

Patrick Wessa

2008-01-01

390

Recent developments of time series analysis in environmental impact studies  

Microsoft Academic Search

Time series analysis, particularly intervention analysis, is commonly employed in impact studies of environmental data. Environmental time series are susceptible to exogenous variations and often contain various types of outliers. Outliers, depending upon the time of their occurrences and nature, can have substantial impact on the estimates of intervention effects and their test statistics. Hence, outlier detection and adjustment should

Chung Chen

1991-01-01

391

A nearest neighbor bootstrap for resampling hydrologic time series  

Microsoft Academic Search

A nonparametric method for resampling scalar or vector-valued time series 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 time series while bootstrapping (resampling it with replacement). The method is data driven and is preferred where the

Upmanu Lall; Ashish Sharma

1996-01-01

392

Crisis Monitoring: Methods for Heterogeneous Time Series Learning  

Microsoft Academic Search

A very important application of time series learning is online diagnosis, or monitoring, to detect and classify hazardous conditions in a physical system. Examples of crisis monitoring in the industrial, military, agricultural and environmental sciences are numerous. This paper first defines heterogeneous time series, those containing different types of embedded, statistical patterns. Next, it surveys basic techniques for acquiring several

William H. Hsu; Nathan D. Gettings; Victoria E. Lease; Yu Pan; David C. Wilkins

393

Online Discovery and Maintenance of Time Series Motifs Abdullah Mueen  

E-print Network

on activity discovery for humans and animals, with applications in elder care [27], surveillance and sportsOnline Discovery and Maintenance of Time Series Motifs Abdullah Mueen University of California The detection of repeated subsequences, time series motifs, is a problem which has been shown to have great

Zordan, Victor

394

Recurrence Plots in Nonlinear Time Series Analysis: Free Software  

Microsoft Academic Search

Abstract Nonlinear time series analysis has just undertaken a new methodological approach: recurrence analysis. This recent approach,requires new,available software to make its correct implementation,possible. This paper reviews the main available software programs to that aim, and focuses on a detailed presentation of VRA, a free access software which is useful for general nonlinear time series analysis. Resumen

Jorge Belaire Franch; Dulce Contreras Bayarri

395

Dynamic Modelling of Chaotic Time Series with Neural Networks  

E-print Network

Dynamic Modelling of Chaotic Time Series with Neural Networks Jose C. Principe, Jyh-Ming Kuo@synapse.ee.ufl.edu Abstract This paper discusses the use of artificial neural networks for dynamic modelling of time series. We argue that multistep prediction is more appropriate to capture the dynamics of the underlying

Slatton, Clint

396

Application of support vector machines in financial time series forecasting  

Microsoft Academic Search

This paper deals with the application of a novel neural network technique, support vector machine (SVM), in financial time series forecasting. The objective of this paper is to examine the feasibility of SVM in financial time series forecasting by comparing it with a multi-layer back-propagation (BP) neural network. Five real futures contracts that are collated from the Chicago Mercantile Market

Francis E. H. Tay; Lijuan Cao

2001-01-01

397

Instant Trend-Seasonal Decomposition of Time Series with Splines  

E-print Network

Instant Trend-Seasonal Decomposition of Time Series with Splines Luis Francisco Rosales1 Tatyana to decompose a times series into trend, seasonal and remainder components. This fully data-driven technique is based on penalized splines and makes an explicit characterization of the varying seasonality

Krivobokova, Tatyana

398

9 Nonlinear Time Series Analysis in a Nutshell  

E-print Network

Ion Nonlinear time series analysis is a practical spinoff from complex dynamical systems theory and chaos theory125 9 Nonlinear Time Series Analysis in a Nutshell Ralph Gregor Andrzejak 9.1 Introduct. It allows one to characterize dynamical systems in which nonlinearities give rise to a complex temporal

Andrzejak, Ralph Gregor

399

A univariate model of river water nitrate time series  

Microsoft Academic Search

Four time series were taken from three catchments in the North and South of England. The sites chosen included two in predominantly agricultural catchments, one at the tidal limit and one downstream of a sewage treatment works. A time series model was constructed for each of these series as a means of decomposing the elements controlling river water nitrate concentrations

F. Worrall; T. P. Burt

1999-01-01

400

Trajectory Boundary Modeling of Time Series for Anomaly Detection  

E-print Network

compares favorably with anomaly detection algorithms based on Euclidean distance and dynamic time warping on the Space Shuttle Marrotta fuel control valve data set. Keywords Time series anomaly detection, MachineTrajectory Boundary Modeling of Time Series for Anomaly Detection Matthew V. Mahoney and Philip K

Chan, Philip K.

401

Streaming Time Series Summarization Using User-Defined Amnesic Functions  

Microsoft Academic Search

The past decade has seen a wealth of research on time series representations, because the manipulation, storage, and indexing of large volumes of raw time series data is impractical. The vast majority of research has concentrated on representations that are calculated in batch mode and represent each value with approximately equal fidelity. However, the increasing deployment of mobile devices and

Themis Palpanas; Michail Vlachos; Eamonn J. Keogh; Dimitrios Gunopulos

2008-01-01

402

Trajectory Boundary Modeling of Time Series for Anomaly Detection  

Microsoft Academic Search

We a ddress the problem of online detection o f unanticipated modes of mechanical failure given a small set of time series under normal conditions, with the requirement that the anomaly detection model be manually verifiable a nd modifiable. We specify a set of time series features, which are linear combinations of the c urrent and p ast values, and

Matthew V. Mahoney; Philip K. Chan

403

Aligning gene expression time series with time warping algorithms  

Microsoft Academic Search

Motivation: Increasingly, biological processes are being studied through time series 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 time series to be mapped to one another. Results: We present implementations of

John Aach; George M. Church

2001-01-01

404

Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models  

ERIC Educational Resources Information Center

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) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying…

Price, Larry R.

2012-01-01

405

Bayesian Time Series Modelling with LongRange Dependence  

E-print Network

We develop a class of Bayesian time series models for data that may exhibit both structured trends Mellon University and Duke University Summary We present a class of models for trend plus stationary nonparametric Bayesian approach to studying time series models incorporating both deterministic trend and long

406

Discovering Ecosystem Models from Time-Series Data  

E-print Network

Discovering Ecosystem Models from Time-Series Data Dileep George, 1 Kazumi Saito, 2 Pat Langley, 1. Ecosystem models are used to interpret and predict the in- teractions of species and their environment. In this paper, we address the task of inducing ecosystem models from background knowledge and time- series data

Langley, Pat

407

Time Series of Suspended-Solids Concentration, Salinity, Temperature, and  

E-print Network

(RMP) water-quality data can be used to calculate time series of some trace- element concentrationsTime Series of Suspended-Solids Concentration, Salinity, Temperature, and Total Mercury Concentration in San Francisco Bay During Water Year 1998 Prepared by Catherine A. Ruhl and David H. Schoelhamer

408

Statistics 520: Time Series and Applications Purdue University  

E-print Network

Statistics 520: Time Series and Applications Dr. Levine Purdue University Spring 2013 Difference. Levine Purdue University Spring 2013 Homogeneous difference equation of order 1 · The autocorrelation is the root of (z) 1 - z = 0 Jan, 2013 Page 2 #12;Statistics 520: Time Series and Applications Dr. Levine

Levine, Michael "Mihail"

409

Statistics 520: Time Series and Applications Purdue University  

E-print Network

Statistics 520: Time Series and Applications Dr. Levine Purdue University Spring 2012 Yule and Applications Dr. Levine Purdue University Spring 2012 · Thus, the Y-W estimate is ^ = ^-1 p ^p (3) ^2 = ^(0 2 #12;Statistics 520: Time Series and Applications Dr. Levine Purdue University Spring 2012

Levine, Michael "Mihail"

410

Statistics 520: Time Series and Applications Purdue University  

E-print Network

Statistics 520: Time Series and Applications Dr. Levine Purdue University Spring 2012 Introduction and Applications Dr. Levine Purdue University Spring 2012 Cyclical behavior and periodicity · First, consider Page 2 #12;Statistics 520: Time Series and Applications Dr. Levine Purdue University Spring 2012

Levine, Michael "Mihail"

411

Statistics 520: Time Series and Applications Purdue University  

E-print Network

Statistics 520: Time Series and Applications Dr. Levine Purdue University Spring 2012 Periodogram and Applications Dr. Levine Purdue University Spring 2012 Discrete Fourier Transform · The immediate practically March 2012 Page 2 #12;Statistics 520: Time Series and Applications Dr. Levine Purdue University Spring

Levine, Michael "Mihail"

412

Statistics 520: Time Series and Applications Purdue University  

E-print Network

Statistics 520: Time Series and Applications Dr. Levine Purdue University Spring 2013 General ARMA. Levine Purdue University Spring 2013 Introduction to autoregressive models · Autoregression - our earlier;Statistics 520: Time Series and Applications Dr. Levine Purdue University Spring 2013 Some remarks about

Levine, Michael "Mihail"

413

Matching a photograph to satellite images Roger Grosse and Matthew Johnson  

E-print Network

. However, we require all satellite image processing and all comparisons between the ground-based photographMatching a photograph to satellite images Roger Grosse and Matthew Johnson MIT CSAIL and LIDS it to satellite imagery. First, a user labels interest points in the pho- tograph corresponding to stationary

Willsky, Alan S.

414

Deriving Texture Feature Set for Content-Based Retrieval of Satellite Image Database  

Microsoft Academic Search

In this paper, the performance of similarity retrieval from satellite image databases by using different sets of spatial and transformed-based texture features is evaluated and compared. A benchmark consisting of 37 satellite image clips from various satellite instruments is devised for the experiments. We show that although the proposed feature set perform only slightly better with the Brodatz set, its

Chung-sheng Li; Vittorio Clastelli

1997-01-01

415

A FRAMEWORK OF WEB-BASED SERVICE SYSTEM FOR SATELLITE IMAGES AUTOMATIC ORTHORECTIFICATION  

Microsoft Academic Search

The orthorectification of satellite images is a foundational process in satellite applications. With the improvement of the satellite imaging technology and the orthorectification calculation models, the collection of Ground Control Point (GCP) is becoming the key factor restricting the efficiency and precision of orthorectification. At the same time, the services based on web in the geographic information filed have obtained

Jiaojiao Tian; Xinming Tang; Huabin Wang

416

Cyclone Track Forecasting Based on Satellite Images Using Artificial Neural Networks  

E-print Network

the movement direction of cyclones based on satellite images. The trained network produced correct directional1 Cyclone Track Forecasting Based on Satellite Images Using Artificial Neural Networks Rita be developed. The technique presented here uses artificial neural networks to interpret NOAA- AVHRR satellite

Kovordányi, Rita

417

Time series analysis of air pollutants in Beirut, Lebanon.  

PubMed

This study reports for the first time a time series analysis of daily urban air pollutant levels (CO, NO, NO2, O3, PM10, and SO2) in Beirut, Lebanon. The study examines data obtained between September 2005 and July 2006, and their descriptive analysis shows long-term variations of daily levels of air pollution concentrations. Strong persistence of these daily levels is identified in the time series using an autocorrelation function, except for SO2. Time series of standardized residual values (SRVs) are also calculated to compare fluctuations of the time series with different levels. Time series plots of the SRVs indicate that NO and NO2 had similar temporal fluctuations. However, NO2 and O3 had opposite temporal fluctuations, attributable to weather conditions and the accumulation of vehicular emissions. The effects of both desert dust storms and airborne particulate matter resulting from the Lebanon War in July 2006 are also discernible in the SRV plots. PMID:25150052

Farah, Wehbeh; Nakhlé, Myriam Mrad; Abboud, Maher; Annesi-Maesano, Isabella; Zaarour, Rita; Saliba, Nada; Germanos, Georges; Gerard, Jocelyne

2014-12-01

418

Time-series photometry of the O4 I(n)fp star ? Puppis  

NASA Astrophysics Data System (ADS)

We report a time-series analysis of the O4 I(n)fp star ?Pup, based on optical photometry obtained with the SMEI (Solar Mass Ejection Imager) instrument on the Coriolis satellite, 2003-2006. A single astrophysical signal is found, with P = 1.780 938 ± 0.000 093 d and a mean semi-amplitude of 6.9 ± 0.3 mmag. There is no evidence for persistent coherent signals with semi-amplitudes in excess of ˜2 mmag on any of the time-scales previously reported in the literature. In particular, there is no evidence for a signature of the proposed rotation period, ˜5.1 d; ? Pup is therefore probably not an oblique magnetic rotator. The 1.8-d signal varies in amplitude by a factor ˜2 on time-scales of 10-100d (and probably by more on longer time-scales), and exhibits modest excursions in phase, but there is no evidence for systematic changes in period over the 1000-d span of our observations. Rotational modulation and stellar-wind variability appear to be unlikely candidates for the underlying mechanism; we suggest that the physical origin of the signal may be pulsation associated with low-? oscillatory convection modes.

Howarth, Ian D.; Stevens, Ian R.

2014-12-01

419

Portable EDITOR (PEDITOR): A portable image processing system. [satellite images  

NASA Technical Reports Server (NTRS)

The PEDITOR image processing system was created to be readily transferable from one type of computer system to another. While nearly identical in function and operation to its predecessor, EDITOR, PEDITOR employs additional techniques which greatly enhance its portability. These cover system structure and processing. In order to confirm the portability of the software system, two different types of computer systems running greatly differing operating systems were used as target machines. A DEC-20 computer running the TOPS-20 operating system and using a Pascal Compiler was utilized for initial code development. The remaining programmers used a Motorola Corporation 68000-based Forward Technology FT-3000 supermicrocomputer running the UNIX-based XENIX operating system and using the Silicon Valley Software Pascal compiler and the XENIX C compiler for their initial code development.

Angelici, G.; Slye, R.; Ozga, M.; Ritter, P.

1986-01-01

420

Image Processing Algorithms Incorporating Textures for the Segmentation of Satellite Data  

E-print Network

Image Processing Algorithms Incorporating Textures for the Segmentation of Satellite Data based has been intentionally left blank) #12;Abstract In image processing, automated segmentation, as a consequence, enable further image processing to increase segmentation accuracy. #12;Contents 1 Introduction 4

Gugat, Martin

421

Ultrasound RF time series for tissue typing: first in vivo clinical results  

NASA Astrophysics Data System (ADS)

The low diagnostic value of ultrasound in prostate cancer imaging has resulted in an effort to enhance the tumor contrast using ultrasound-based technologies that go beyond traditional B-mode imaging. Ultrasound RF time series, formed by echo samples originating from the same location over a few seconds of imaging, has been proposed and experimentally used for tissue typing with the goal of cancer detection. In this work, for the first time we report the preliminary results of in vivo clinical use of spectral parameters extracted from RF time series in prostate cancer detection. An image processing pipeline is designed to register the ultrasound data to wholemount histopathology references acquired from prostate specimens that are removed in radical prostatectomy after imaging. Support vector machine classification is used to detect cancer in 524 regions of interest of size 5×5 mm, each forming a feature vector of spectral RF time series parameters. Preliminary ROC curves acquired based on RF time series analysis for individual cases, with leave-one-patient-out cross validation, are presented and compared with B-mode texture analysis.

Moradi, Mehdi; Mahdavi, S. Sara; Nir, Guy; Jones, Edward C.; Goldenberg, S. Larry; Salcudean, Septimiu E.

2013-03-01

422

Secure Satellite Images Transmission Scheme Based on Chaos and Discrete Wavelet Transform  

Microsoft Academic Search

\\u000a Many applications based on satellite communication like national defence and security rely on the satellite images as an important\\u000a source of information. It is therefore, mandatory to secure satellite imagery while transmitting them over communication channels\\u000a to protect from unauthorized access and usage. In this paper, chaotic logistic map based satellite image encryption scheme\\u000a is proposed to meet the requirement

Musheer Ahmad; Omar Farooq

423

Outliers detection in multivariate time series by independent component analysis.  

PubMed

In multivariate time series, outlying data may be often observed that do not fit the common pattern. Occurrences of outliers are unpredictable events that may severely distort the analysis of the multivariate time series. For instance, model building, seasonality assessment, and forecasting may be seriously affected by undetected outliers. The structure dependence of the multivariate time series gives rise to the well-known smearing and masking phenomena that prevent using most outliers' identification techniques. It may be noticed, however, that a convenient way for representing multiple outliers consists of superimposing a deterministic disturbance to a gaussian multivariate time series. Then outliers may be modeled as nongaussian time series components. Independent component analysis is a recently developed tool that is likely to be able to extract possible outlier patterns. In practice, independent component analysis may be used to analyze multivariate observable time series and separate regular and outlying unobservable components. In the factor models framework too, it is shown that independent component analysis is a useful tool for detection of outliers in multivariate time series. Some algorithms that perform independent component analysis are compared. It has been found that all algorithms are effective in detecting various types of outliers, such as patches, level shifts, and isolated outliers, even at the beginning or the end of the stretch of observations. Also, there is no appreciable difference in the ability of different algorithms to display the outlying observations pattern. PMID:17521286

Baragona, Roberto; Battaglia, Francesco

2007-07-01

424

Model-free quantification of time-series predictability  

NASA Astrophysics Data System (ADS)

This paper provides insight into when, why, and how forecast strategies fail when they are applied to complicated time series. We conjecture that the inherent complexity of real-world time-series data, which results from the dimension, nonlinearity, and nonstationarity of the generating process, as well as from measurement issues such as noise, aggregation, and finite data length, is both empirically quantifiable and directly correlated with predictability. In particular, we argue that redundancy is an effective way to measure complexity and predictive structure in an experimental time series and that weighted permutation entropy is an effective way to estimate that redundancy. To validate these conjectures, we study 120 different time-series data sets. For each time series, we construct predictions using a wide variety of forecast models, then compare the accuracy of the predictions with the permutation entropy of that time series. We use the results to develop a model-free heuristic that can help practitioners recognize when a particular prediction method is not well matched to the task at hand: that is, when the time series has more predictive structure than that method can capture and exploit.

Garland, Joshua; James, Ryan; Bradley, Elizabeth

2014-11-01

425

Concepts for on-board satellite image registration, volume 1  

NASA Technical Reports Server (NTRS)

The NASA-NEEDS program goals present a requirement for on-board signal processing to achieve user-compatible, information-adaptive data acquisition. One very specific area of interest is the preprocessing required to register imaging sensor data which have been distorted by anomalies in subsatellite-point position and/or attitude control. The concepts and considerations involved in using state-of-the-art positioning systems such as the Global Positioning System (GPS) in concert with state-of-the-art attitude stabilization and/or determination systems to provide the required registration accuracy are discussed with emphasis on assessing the accuracy to which a given image picture element can be located and identified, determining those algorithms required to augment the registration procedure and evaluating the technology impact on performing these procedures on-board the satellite.

Ruedger, W. H.; Daluge, D. R.; Aanstoos, J. V.

1980-01-01

426

Application of Geostatistical Simulation to Enhance Satellite Image Products  

NASA Technical Reports Server (NTRS)

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

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

2004-01-01

427

Modelling road accidents: An approach using structural time series  

NASA Astrophysics Data System (ADS)

In this paper, the trend of road accidents in Malaysia for the years 2001 until 2012 was modelled using a structural time series approach. The structural time series model was identified using a stepwise method, and the residuals for each model were tested. The best-fitted model was chosen based on the smallest Akaike Information Criterion (AIC) and prediction error variance. In order to check the quality of the model, a data validation procedure was performed by predicting the monthly number of road accidents for the year 2012. Results indicate that the best specification of the structural time series model to represent road accidents is the local level with a seasonal model.

Junus, Noor Wahida Md; Ismail, Mohd Tahir

2014-09-01

428

How to use recurrence networks for geophysical time series analysis?  

NASA Astrophysics Data System (ADS)

Recurrence plot based recurrence networks are an approach to analyze time series using complex networks theory. In both approaches, recurrence plot and the recurrence networks, we define a threshold to identify recurrent states. The selection of the threshold is very important for analysing the time series correctly via recurrence networks approach. In this talk we contribute a novel method to choose a threshold adaptively for time series. We show comparison between constant threshold and adaptive threshold cases to study transitions in the dynamics due to a change in the control parameters. This novel methods enables us to identify climate transitions from a lake sediment record.

Eroglu, Deniz; Marwan, Norbert; Prasad, Sushma; Kurths, Jürgen

2014-05-01

429

Application of p-adic analysis to time series  

E-print Network

Time series defined by a p-adic pseudo-differential equation is investigated using the expansion of the time series over p-adic wavelets. Quadratic correlation function is computed. This correlation function shows a degree--like behavior and is locally constant for some time periods. It is natural to apply this kind of models for the investigation of avalanche processes and punctuated equilibrium as well as fractal-like analysis of time series generated by measurement of pressure in oil wells.

A. Yu. Khrennikov; S. V. Kozyrev; K. Oleschko; A. G. Jaramillo; M. de Jesus Correa Lopez

2013-12-13

430

Factorizing Markov Models for Categorical Time Series Prediction  

NASA Astrophysics Data System (ADS)

During the last decade, recommender systems became a popular class of models for many commercial websites. One of the best state-of-the-art methods for recommender systems are Matrix and Tensor Factorization models. Besides, Markov Chain models are common for representing sequential data problems (e.g. categorical time series data). The item recommendation problem of recommender systems in fact is a categorical time series problem where each user represents an individual categorical time series. In this paper we combine factorization models with Markov Chain models. To increase efficiency of parameter estimation we introduce our generalized Factorized Markov Chain model.

Freudenthaler, Christoph; Rendle, Steffen; Schmidt-Thieme, Lars

2011-09-01

431

Assessment of MODIS NDVI time series data products for detecting forest defoliation by gypsy moth outbreaks  

Microsoft Academic Search

This paper discusses an assessment of Moderate Resolution Imaging Spectroradiometer (MODIS) time-series data products for detecting forest defoliation from European gypsy moth (Lymantria dispar). This paper describes an effort to aid the United States Department of Agriculture (USDA) Forest Service in developing and assessing MODIS-based gypsy moth defoliation detection products and methods that could be applied in near real time

Joseph P. Spruce; Steven Sader; Robert E. Ryan; James Smoot; Philip Kuper; Kenton Ross; Donald Prados; Jeffrey Russell; Gerald Gasser; Rodney McKellip; William Hargrove

2011-01-01

432

Forecasting of Chaotic Cloud Absorption Time Series for Meteorological and Plume Dispersion Modeling  

Microsoft Academic Search

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 images was used to predict the behavior of the time series 24 h in advance. The forecast values are then used by a meteorological model for daily prediction of plume transport from the As

V. P EREZ-MUNUZURI

433

Ultrasound radio-frequency time series for finding malignant breast lesions  

E-print Network

to augment the Breast Imaging-Reporting and Data System (BI-RADS). Breast ultrasound is used as a supplement 050 051 052 053 Ultrasound radio-frequency time series for finding malignant breast lesions Anonymous-based solutions for breast lesion characterization to reduce the patient recall rate after mammography screening

de Freitas, Nando

434

Georeferencing of Satellite Linear Array Stereo Images with Quaternion Attitude Kinematics Equation  

Microsoft Academic Search

A quaternion method for georeferencing of satellite linear array stereo images is proposed in this paper. In this method, quaternion is used to describe the exterior orientation parameters (EOPs) of the satellite linear array stereo images, and gain the EOPs of any image line through quaternion attitude kinematics equation. Then the georeferencing results can be obtained after solving the collinearity

Hui Gong; Ting Jiang; Xin Wang; Jianhui Liu; Gangwu Jiang

2011-01-01

435

A Near-Lossless Compression Method Based on CCSDS for Satellite Images  

Microsoft Academic Search

Satellite images have been more and more popularly used in our daily life. For satellite image compression, the Consultative Committee for Space Data Systems (CCSDS) had proposed an image compression standard (CCSDS-ICS) which is so far the most widely implemented in hardware. CCSDS-ICS provides good compression performance under the measure of PSNR. However, PSNR is a concept of average differences

Shen-Chuan Tai; Tse-Ming Kuo; Cheng-Han Ho; Tzu-Wen Liao

2012-01-01

436

Automated Extraction of Control Points for High Spatial Resolution Satellite Images  

Microsoft Academic Search

As IKONOS satellite with 1-m resolution camera has been lunched in 1999, mapping using space-borne images will be a hot issue in computer vision area and photogrammetry. It is o bvious that one of the great challenges to process the high spatial resolution satellite images will be the geometric correction practice. Conventionally, the positioning of the image control points is

Cheng-Yi LIN; Chi-Farn CHEN

437

UPDATING LAND COVER DATABASES USING A SINGLE VERY HIGH RESOLUTION SATELLITE IMAGE  

E-print Network

UPDATING LAND COVER DATABASES USING A SINGLE VERY HIGH RESOLUTION SATELLITE IMAGE Adrien Gressin1 detection, updating, classification, image, 2D topographic database, very high resolution, satellite be subsequently compared with classifications resulting for geospatial image processing. In this paper, we propose

Paris-Sud XI, Université de

438

The use of voting strategy for building extraction from high resolution satellite images  

Microsoft Academic Search

This paper proposes the use of voting strategy for extracting buildings from high resolution satellite images. Previously, the grouping strategy has been proposed and widely used for extraction of man-made features from images. In order to apply grouping we need to extract one complete line per each building side. However, this requirement may not be met for satellite images such

Taejung Kim; Tae-Yoon Lee; Young Jae Lim; Kyung-Ok Kim

2005-01-01

439

On the EM Algorithm and Bootstrap Approach Combination for Improving Satellite Image Fusion  

Microsoft Academic Search

This paper discusses EM algorithm and Bootstrap approach combination applied for the improvement of the satellite image fusion process. This novel satellite image fusion method based on estimation theory EM algorithm and reinforced by Bootstrap approach was successfully implemented and tested. The sensor images are firstly split by a Bayesian segmentation method to determine a joint region map for the

Tijani Delleji; Mourad Zribi; Ahmed Ben

2008-01-01

440

A Copyright Protection Scheme for Satellite Images Using Secret Sharing and Wavelet Transform  

Microsoft Academic Search

This paper considers weather satellite images as the protected host images and proposes a novel copyright protection scheme according to the property of the images. The scheme contains two phases: the share image generation phase and the watermark retrieval phase. In the generation phase, the proposed scheme first generates a cloud image from the host image using gray-level slicing and

Shang-Lin Hsieh; I-Ju Tsai

2006-01-01

441

The extraction of multiple cropping index of China based on NDVI time-series  

NASA Astrophysics Data System (ADS)

Multiple cropping index reflects the intensity of arable land been used by a certain planting system. The bond between multiple cropping index and NDVI time-series 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 time-series for that peaks and valleys on the time-series curve correspond to different periods of crop growth. In this paper, we aim to extract the multiple cropping index of China from NDVI time-series. 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 Time Series) is employed to remove the cloud contamination. The reconstructed NDVI time-series 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 image and then the multiple cropping index of China is extracted from VEGETATION decadal composites NDVI time series 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.

Huang, Haitao; Gao, Zhiqiang

2011-09-01

442

Orthorectified image mosaic of Antarctica from 1963 Argon satellite photography: image processing and glaciological applications  

Microsoft Academic Search

Using the state?of?the?art digital imaging technology, extended block adjustment, orthorectification and mosaicking, individual Declassified Intelligence Satellite Argon photographic images are precisely assembled into a map quality mosaic of coastal Antarctica. The geometric accuracy of the mosaic is estimated to be approximately equivalent to the original resolution of the Argon photography, which is about 140 m. We compare the Argon mosaic with

K. Kim; K. C. Jezek; H. Liu

2007-01-01

443

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

NASA Astrophysics Data System (ADS)

Unmanned Aerial Vehicle or UAV is extensively applied in various fields such as military applications, archaeology, agriculture and scientific research. This study focuses on topographic mapping and map updating. UAV is one of the alternative ways to ease the process of acquiring data with lower operating costs, low manufacturing and operational costs, plus it is easy to operate.