Essential Technology and Application of Jitter Detection and Compensation for High Resolution Satellites

Directory of Open Access Journals (Sweden)

TONG Xiaohua

2017-10-01

Full Text Available Satellite jitter is a common and complex phenomenon for the on-orbit high resolution satellites, which may affect the mapping accuracy and quality of imagery. A framework of jitter detection and compensation integrating data processing of multiple sensors is proposed in this paper. Jitter detection is performed based on multispectral imagery, three-line-array imagery, dense ground control and attitude measurement data, and jitter compensation is conducted both on image and on attitude with the sensor model. The platform jitter of ZY-3 satellite is processed and analyzed using the proposed technology, and the results demonstrate the feasibility and reliability of jitter detection and compensation. The variation law analysis of jitter indicates that the frequencies of jitter of ZY-3 satellite hold in the range between 0.6 and 0.7 Hz, while the amplitudes of jitter of ZY-3 satellite drop from 1 pixel in the early stage to below 0.4 pixels and tend to remain stable in the following stage.

Framework of Jitter Detection and Compensation for High Resolution Satellites

Directory of Open Access Journals (Sweden)

Xiaohua Tong

2014-05-01

Full Text Available Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution satellites. In this paper, a framework of jitter detection and compensation for high resolution satellites is proposed and some preliminary investigation is performed. Three methods for jitter detection are presented as follows. (1 The first one is based on multispectral images using parallax between two different bands in the image; (2 The second is based on stereo images using rational polynomial coefficients (RPCs; (3 The third is based on panchromatic images employing orthorectification processing. Based on the calculated parallax maps, the frequency and amplitude of the detected jitter are obtained. Subsequently, two approaches for jitter compensation are conducted. (1 The first one is to conduct the compensation on image, which uses the derived parallax observations for resampling; (2 The second is to conduct the compensation on attitude data, which treats the influence of jitter on attitude as correction of charge-coupled device (CCD viewing angles. Experiments with images from several satellites, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiaometer, LRO (Lunar Reconnaissance Orbiter and ZY-3 (ZiYuan-3 demonstrate the promising performance and feasibility of the proposed framework.

Convolutional neural network features based change detection in satellite images

Science.gov (United States)

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

2016-07-01

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

Analysis of GPS Satellite Allocation for the United States Nuclear Detonation Detection System (USNDS)

National Research Council Canada - National Science Library

Bell, Aaron

2002-01-01

...) satellites to detect atmospheric nuclear detonations. Though there are currently over 24 operational GPS satellites, USNDS ground based antennas are only capable of actively monitoring 24 satellites at a time...

Combining Satellite and in Situ Data with Models to Support Climate Data Records in Ocean Biology

Science.gov (United States)

Gregg, Watson

2011-01-01

The satellite ocean color data record spans multiple decades and, like most long-term satellite observations of the Earth, comes from many sensors. Unfortunately, global and regional chlorophyll estimates from the overlapping missions show substantial biases, limiting their use in combination to construct consistent data records. SeaWiFS and MODIS-Aqua differed by 13% globally in overlapping time segments, 2003-2007. For perspective, the maximum change in annual means over the entire Sea WiFS mission era was about 3%, and this included an El NinoLa Nina transition. These discrepancies lead to different estimates of trends depending upon whether one uses SeaWiFS alone for the 1998-2007 (no significant change), or whether MODIS is substituted for the 2003-2007 period (18% decline, P less than 0.05). Understanding the effects of climate change on the global oceans is difficult if different satellite data sets cannot be brought into conformity. The differences arise from two causes: 1) different sensors see chlorophyll differently, and 2) different sensors see different chlorophyll. In the first case, differences in sensor band locations, bandwidths, sensitivity, and time of observation lead to different estimates of chlorophyll even from the same location and day. In the second, differences in orbit and sensitivities to aerosols lead to sampling differences. A new approach to ocean color using in situ data from the public archives forces different satellite data to agree to within interannual variability. The global difference between Sea WiFS and MODIS is 0.6% for 2003-2007 using this approach. It also produces a trend using the combination of SeaWiFS and MODIS that agrees with SeaWiFS alone for 1998-2007. This is a major step to reducing errors produced by the first cause, sensor-related discrepancies. For differences that arise from sampling, data assimilation is applied. The underlying geographically complete fields derived from a free-running model is unaffected

Gridded sunshine duration climate data record for Germany based on combined satellite and in situ observations

Science.gov (United States)

Walawender, Jakub; Kothe, Steffen; Trentmann, Jörg; Pfeifroth, Uwe; Cremer, Roswitha

2017-04-01

The purpose of this study is to create a 1 km2 gridded daily sunshine duration data record for Germany covering the period from 1983 to 2015 (33 years) based on satellite estimates of direct normalised surface solar radiation and in situ sunshine duration observations using a geostatistical approach. The CM SAF SARAH direct normalized irradiance (DNI) satellite climate data record and in situ observations of sunshine duration from 121 weather stations operated by DWD are used as input datasets. The selected period of 33 years is associated with the availability of satellite data. The number of ground stations is limited to 121 as there are only time series with less than 10% of missing observations over the selected period included to keep the long-term consistency of the output sunshine duration data record. In the first step, DNI data record is used to derive sunshine hours by applying WMO threshold of 120 W/m2 (SDU = DNI ≥ 120 W/m2) and weighting of sunny slots to correct the sunshine length between two instantaneous image data due to cloud movement. In the second step, linear regression between SDU and in situ sunshine duration is calculated to adjust the satellite product to the ground observations and the output regression coefficients are applied to create a regression grid. In the last step regression residuals are interpolated with ordinary kriging and added to the regression grid. A comprehensive accuracy assessment of the gridded sunshine duration data record is performed by calculating prediction errors (cross-validation routine). "R" is used for data processing. A short analysis of the spatial distribution and temporal variability of sunshine duration over Germany based on the created dataset will be presented. The gridded sunshine duration data are useful for applications in various climate-related studies, agriculture and solar energy potential calculations.

Satellite Climate Data Records: Development, Applications, and Societal Benefits

Directory of Open Access Journals (Sweden)

Wenze Yang

2016-04-01

Full Text Available This review paper discusses how to develop, produce, sustain, and serve satellite climate data records (CDRs in the context of transitioning research to operation (R2O. Requirements and critical procedures of producing various CDRs, including Fundamental CDRs (FCDRs, Thematic CDRs (TCDRs, Interim CDRs (ICDRs, and climate information records (CIRs are discussed in detail, including radiance/reflectance and the essential climate variables (ECVs of land, ocean, and atmosphere. Major international CDR initiatives, programs, and projects are summarized. Societal benefits of CDRs in various user sectors, including Agriculture, Forestry, Fisheries, Energy, Heath, Water, Transportation, and Tourism are also briefly discussed. The challenges and opportunities for CDR development, production and service are also addressed. It is essential to maintain credible CDR products by allowing free access to products and keeping the production process transparent by making source code and documentation available with the dataset.

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

Indian Academy of Sciences (India)

Samik Banerjee

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

Volumetric Forest Change Detection Through Vhr Satellite Imagery

Science.gov (United States)

Akca, Devrim; Stylianidis, Efstratios; Smagas, Konstantinos; Hofer, Martin; Poli, Daniela; Gruen, Armin; Sanchez Martin, Victor; Altan, Orhan; Walli, Andreas; Jimeno, Elisa; Garcia, Alejandro

2016-06-01

Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView - 3, SPOT - 5 HRS, SPOT - 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in

Sustained Satellite Missions for Climate Data Records

Science.gov (United States)

Halpern, David

2012-01-01

Satellite CDRs possess the accuracy, longevity, and stability for sustained moni toring of critical variables to enhance understanding of the global integrated Earth system and predict future conditions. center dot Satellite CDRs are a critical element of a global climate observing system. center dot Satellite CDRs are a difficult challenge and require high - level managerial commitment, extensive intellectual capital, and adequate funding.

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

Science.gov (United States)

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

2017-09-01

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

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

Directory of Open Access Journals (Sweden)

N. M. S. M. Kadhim

2015-03-01

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

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

Science.gov (United States)

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

2015-03-01

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

Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

Science.gov (United States)

Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo

2016-10-01

Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

Tile Drainage Expansion Detection using Satellite Soil Moisture Dynamics

Science.gov (United States)

Jacobs, J. M.; Cho, E.; Jia, X.

2017-12-01

In the past two decades, tile drainage installation has accelerated throughout the Red River of the North Basin (RRB) in parts of western Minnesota, eastern North Dakota, and a small area of northeastern South Dakota, because the flat topography and low-permeability soils in this region necessitated the removal of excess water to improve crop production. Interestingly, streamflow in the Red River has markedly increased and six of 13 major floods during the past century have occurred since the late 1990s. It has been suggested that the increase in RRB flooding could be due to change in agricultural practices, including extensive tile drainage installation. Reliable information on existing and future tile drainage installation is greatly needed to capture the rapid extension of tile drainage systems and to locate tile drainage systems in the north central U.S. including the RRB region. However, there are few reliable data of tile drainage installation records, except tile drainage permit records in the Bois de Sioux watershed (a sub-basin in southern part of the RRB where permits are required for tile drainage installation). This study presents a tile drainage expansion detection method based on a physical principle that the soil-drying rate may increase with increasing tile drainage for a given area. In order to capture the rate of change in soil drying rate with time over entire RRB (101,500 km2), two satellite-based microwave soil moisture records from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and AMSR2 were used during 2002 to 2016. In this study, a sub-watershed level (HUC10) potential tile drainage growth map was developed and the results show good agreement with tile drainage permit records of six sub-watersheds in the Bois de Sioux watershed. Future analyses will include improvement of the potential tile drainage map through additional information using optical- and thermal-based sensor products and evaluation of its

Rain detection over land surfaces using passive microwave satellite data

NARCIS (Netherlands)

Bauer, P.; Burose, D.; Schulz, J.

2002-01-01

An algorithm is presented for the detection of surface rainfall using passive microwave measurements by satellite radiometers. The technique consists of a two-stage approach to distinguish precipitation signatures from other effects: (1) Contributions from slowly varying parameters (surface type and

Satellite skill in detecting extreme episodes in near-surface air quality

Science.gov (United States)

Ruiz, D. J.; Prather, M. J.

2017-12-01

Ozone (O3) contributes to ambient air pollution, adversely affecting public health, agriculture, and ecosystems. Reliable, long-term, densely distributed surface networks are required to establish the scale, intensity and repeatability of major pollution events (designated here in a climatological sense as air quality extremes, AQX as defined in Schnell's work). Regrettably, such networks are only available for North America (NA) and Europe (EU), which does not include many populated regions where the deaths associated with air pollution exposure are alarmingly high. Directly measuring surface pollutants from space without lidar is extremely difficult. Mapping of daily pollution events requires cross-track nadir scanners and these have limited sensitivity to surface O3 levels. This work examines several years of coincident surface and OMI satellite measurements over NA-EU, in combination with a chemistry-transport model (CTM) hindcast of that period to understand how the large-scale AQX episodes may extend into the free troposphere and thus be more amenable to satellite mapping. We show how extreme NA-EU episodes are measured from OMI and then look for such patterns over other polluted regions of the globe. We gather individual high-quality O3 surface site measurements from these other regions, to check on our satellite detection. Our approach with global satellite detection would avoid issues associated with regional variations in seasonality, chemical regime, data product biases; and it does not require defining a separate absolute threshold for each data product (surface site and satellite). This also enables coherent linking of the extreme events into large-scale pollution episodes whose magnitude evolves over 100's of km for several days. Tools used here include the UC Irvine CTM, which shows that much of the O3 surface variability is lost at heights above 2 km, but AQX local events are readily seen in a 0-3 km column average. The OMI data are taken from X

PLASTIC AND GLASS GREENHOUSES DETECTION AND DELINEATION FROM WORLDVIEW-2 SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

D. Koc-San

2016-06-01

Full Text Available Greenhouse detection using remote sensing technologies is an important research area for yield estimation, sustainable development, urban and rural planning and management. An approach was developed in this study for the detection and delineation of greenhouse areas from high resolution satellite imagery. Initially, the candidate greenhouse patches were detected using supervised classification techniques. For this purpose, Maximum Likelihood (ML, Random Forest (RF, and Support Vector Machines (SVM classification techniques were applied and compared. Then, sieve filter and morphological operations were performed for improving the classification results. Finally, the obtained candidate plastic and glass greenhouse areas were delineated using boundary tracing and Douglas Peucker line simplification algorithms. The proposed approach was implemented in the Kumluca district of Antalya, Turkey utilizing pan-sharpened WorldView-2 satellite imageries. Kumluca is the prominent district of Antalya with greenhouse cultivation and includes both plastic and glass greenhouses intensively. When the greenhouse classification results were analysed, it can be stated that the SVM classification provides most accurate results and RF classification follows this. The SVM classification overall accuracy was obtained as 90.28%. When the greenhouse boundary delineation results were considered, the plastic greenhouses were delineated with 92.11% accuracy, while glass greenhouses were delineated with 80.67% accuracy. The obtained results indicate that, generally plastic and glass greenhouses can be detected and delineated successfully from WorldView-2 satellite imagery.

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

Science.gov (United States)

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

2015-12-01

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

Applying Metrological Techniques to Satellite Fundamental Climate Data Records

Science.gov (United States)

Woolliams, Emma R.; Mittaz, Jonathan PD; Merchant, Christopher J.; Hunt, Samuel E.; Harris, Peter M.

2018-02-01

Quantifying long-term environmental variability, including climatic trends, requires decadal-scale time series of observations. The reliability of such trend analysis depends on the long-term stability of the data record, and understanding the sources of uncertainty in historic, current and future sensors. We give a brief overview on how metrological techniques can be applied to historical satellite data sets. In particular we discuss the implications of error correlation at different spatial and temporal scales and the forms of such correlation and consider how uncertainty is propagated with partial correlation. We give a form of the Law of Propagation of Uncertainties that considers the propagation of uncertainties associated with common errors to give the covariance associated with Earth observations in different spectral channels.

Research on the new type of multi-functional satellite system for space debris detection

Science.gov (United States)

Guo, Linghua; Fu, Qiang; Jiang, Huilin; Xu, Xihe

2017-05-01

With the rapid development of space exploration and utilization, orbital debris increases dramatically, leading to great threat to human space activities and spacecraft security. In this paper, a new type of multi-functional space debris satellite system (MSDS) was put forward, which shared main optical system, and possessed functions of multidimensional information detection, polarized remote sensing and high rate transmission. The MSDS system can meet the requirements of detection and identification for the small orbital debris which is 1000km faraway, as well as the requirements of the data transmission by 50 Mbps to 2.5 Gbps@200-1000 km. At the same time, by the method of satellite orbital maneuver and attitude adjusting, the orbital debris information that is real-time, complex and refined, allweather can be acquired and transmitted by the new system. Such new type of multifunctional satellite system can provide important and effective technology for international orbital debris detection.

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

Science.gov (United States)

Champion, Nicolas

2016-06-01

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

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

Directory of Open Access Journals (Sweden)

N. Champion

2016-06-01

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

An Unsupervised Anomalous Event Detection and Interactive Analysis Framework for Large-scale Satellite Data

Science.gov (United States)

LIU, Q.; Lv, Q.; Klucik, R.; Chen, C.; Gallaher, D. W.; Grant, G.; Shang, L.

2016-12-01

Due to the high volume and complexity of satellite data, computer-aided tools for fast quality assessments and scientific discovery are indispensable for scientists in the era of Big Data. In this work, we have developed a framework for automated anomalous event detection in massive satellite data. The framework consists of a clustering-based anomaly detection algorithm and a cloud-based tool for interactive analysis of detected anomalies. The algorithm is unsupervised and requires no prior knowledge of the data (e.g., expected normal pattern or known anomalies). As such, it works for diverse data sets, and performs well even in the presence of missing and noisy data. The cloud-based tool provides an intuitive mapping interface that allows users to interactively analyze anomalies using multiple features. As a whole, our framework can (1) identify outliers in a spatio-temporal context, (2) recognize and distinguish meaningful anomalous events from individual outliers, (3) rank those events based on "interestingness" (e.g., rareness or total number of outliers) defined by users, and (4) enable interactively query, exploration, and analysis of those anomalous events. In this presentation, we will demonstrate the effectiveness and efficiency of our framework in the application of detecting data quality issues and unusual natural events using two satellite datasets. The techniques and tools developed in this project are applicable for a diverse set of satellite data and will be made publicly available for scientists in early 2017.

Sensor fault detection and recovery in satellite attitude control

Science.gov (United States)

Nasrolahi, Seiied Saeed; Abdollahi, Farzaneh

2018-04-01

This paper proposes an integrated sensor fault detection and recovery for the satellite attitude control system. By introducing a nonlinear observer, the healthy sensor measurements are provided. Considering attitude dynamics and kinematic, a novel observer is developed to detect the fault in angular rate as well as attitude sensors individually or simultaneously. There is no limit on type and configuration of attitude sensors. By designing a state feedback based control signal and Lyapunov stability criterion, the uniformly ultimately boundedness of tracking errors in the presence of sensor faults is guaranteed. Finally, simulation results are presented to illustrate the performance of the integrated scheme.

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

DEFF Research Database (Denmark)

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

2007-01-01

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

National Satellite Land Remote Sensing Data Archive

Science.gov (United States)

Faundeen, John L.; Kelly, Francis P.; Holm, Thomas M.; Nolt, Jenna E.

2013-01-01

The National Satellite Land Remote Sensing Data Archive (NSLRSDA) resides at the U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center. Through the Land Remote Sensing Policy Act of 1992, the U.S. Congress directed the Department of the Interior (DOI) to establish a permanent Government archive containing satellite remote sensing data of the Earth's land surface and to make this data easily accessible and readily available. This unique DOI/USGS archive provides a comprehensive, permanent, and impartial observational record of the planet's land surface obtained throughout more than five decades of satellite remote sensing. Satellite-derived data and information products are primary sources used to detect and understand changes such as deforestation, desertification, agricultural crop vigor, water quality, invasive plant species, and certain natural hazards such as flood extent and wildfire scars.

Ship detection in satellite imagery using rank-order greyscale hit-or-miss transforms

Energy Technology Data Exchange (ETDEWEB)

Harvey, Neal R [Los Alamos National Laboratory; Porter, Reid B [Los Alamos National Laboratory; Theiler, James [Los Alamos National Laboratory

2010-01-01

Ship detection from satellite imagery is something that has great utility in various communities. Knowing where ships are and their types provides useful intelligence information. However, detecting and recognizing ships is a difficult problem. Existing techniques suffer from too many false-alarms. We describe approaches we have taken in trying to build ship detection algorithms that have reduced false alarms. Our approach uses a version of the grayscale morphological Hit-or-Miss transform. While this is well known and used in its standard form, we use a version in which we use a rank-order selection for the dilation and erosion parts of the transform, instead of the standard maximum and minimum operators. This provides some slack in the fitting that the algorithm employs and provides a method for tuning the algorithm's performance for particular detection problems. We describe our algorithms, show the effect of the rank-order parameter on the algorithm's performance and illustrate the use of this approach for real ship detection problems with panchromatic satellite imagery.

Satellite-detected fluorescence reveals global physiology of ocean phytoplankton

Directory of Open Access Journals (Sweden)

M. J. Behrenfeld

2009-05-01

Full Text Available Phytoplankton photosynthesis links global ocean biology and climate-driven fluctuations in the physical environment. These interactions are largely expressed through changes in phytoplankton physiology, but physiological status has proven extremely challenging to characterize globally. Phytoplankton fluorescence does provide a rich source of physiological information long exploited in laboratory and field studies, and is now observed from space. Here we evaluate the physiological underpinnings of global variations in satellite-based phytoplankton chlorophyll fluorescence. The three dominant factors influencing fluorescence distributions are chlorophyll concentration, pigment packaging effects on light absorption, and light-dependent energy-quenching processes. After accounting for these three factors, resultant global distributions of quenching-corrected fluorescence quantum yields reveal a striking consistency with anticipated patterns of iron availability. High fluorescence quantum yields are typically found in low iron waters, while low quantum yields dominate regions where other environmental factors are most limiting to phytoplankton growth. Specific properties of photosynthetic membranes are discussed that provide a mechanistic view linking iron stress to satellite-detected fluorescence. Our results present satellite-based fluorescence as a valuable tool for evaluating nutrient stress predictions in ocean ecosystem models and give the first synoptic observational evidence that iron plays an important role in seasonal phytoplankton dynamics of the Indian Ocean. Satellite fluorescence may also provide a path for monitoring climate-phytoplankton physiology interactions and improving descriptions of phytoplankton light use efficiencies in ocean productivity models.

Land use change detection based on multi-date imagery from different satellite sensor systems

Science.gov (United States)

Stow, Douglas A.; Collins, Doretta; Mckinsey, David

1990-01-01

An empirical study is conducted to assess the accuracy of land use change detection using satellite image data acquired ten years apart by sensors with differing spatial resolutions. The primary goals of the investigation were to (1) compare standard change detection methods applied to image data of varying spatial resolution, (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice versa in the registration process, (3) determine if Landsat/Thermatic Mapper or SPOT/High Resolution Visible multispectral data provide more accurate detection of land use changes when registered to historical Landsat/MSS data. It is concluded that image ratioing of multisensor, multidate satellite data produced higher change detection accuracies than did principal components analysis, and that it is useful as a land use change enhancement method.

Wide area change detection with satellite imagery for locating underground nuclear testing

International Nuclear Information System (INIS)

Canty, M.J.; Jasani, B.; Schlittenhardt, J.

2001-01-01

With the advent of high resolution optical imagery from commercial earth observation satellites, the use of remote sensing data for verification of nuclear non-proliferation agreements is becoming increasingly attractive. Non-governmental organizations are routinely publishing high-quality imagery of sensitive nuclear installations round the world, and international verification authorities, such as the International Atomic Energy Agency (IAEA) or the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO), will also want to make use, directly or indirectly, of this additional open source of information. Exact location of the sites of underground nuclear explosions is a task eminently suited to satellite imagery. Here both moderate resolutions for detecting signals in very large testing ranges as well as high resolution images for exact interpretation play important roles. We describe in our paper a particularly sensitive change detection procedure for bitemporal, multispectral satellite imagery which can be used to locate the spall zone of underground nuclear explosions with commercial satellite imagery. The method is based on the multivariate alteration detection (MAD) technique of Nielsen et al. Linear combinations of the spectral channels in two images of the same scene are chosen so as to minimize their positive correlation. This leads to a series of difference images - the so-called MAD components - which are mutually orthogonal (uncorrelated) and ordered according to decreasing variance in their pixel intensities. Since interesting changes in man-made structures may contribute minimally to the overall variance (as the latter may be dominated for instance by seasonal vegetation differences) it is often the case that such changes turn up in a higher order MAD component. This is because they will be uncorrelated with seasonal vegetation changes, stochastic image noise or other major contributions to the overall change signal. This in fact is one of the

Detecting weather radar clutter using satellite-based nowcasting products

DEFF Research Database (Denmark)

Jensen, Thomas B.S.; Gill, Rashpal S.; Overgaard, Søren

2006-01-01

This contribution presents the initial results from experiments with detection of weather radar clutter by information fusion with satellite based nowcasting products. Previous studies using information fusion of weather radar data and first generation Meteosat imagery have shown promising results...... for the detecting and removal of clutter. Naturally, the improved spatio-temporal resolution of the Meteosat Second Generation sensors, coupled with its increased number of spectral bands, is expected to yield even better detection accuracies. Weather radar data from three C-band Doppler weather radars...... Application Facility' of EUMETSAT and is based on multispectral images from the SEVIRI sensor of the Meteosat-8 platform. Of special interest is the 'Precipitating Clouds' product, which uses the spectral information coupled with surface temperatures from Numerical Weather Predictions to assign probabilities...

Long-term Satellite Observations of Cloud and Aerosol Radiative Effects Using the (A)ATSR Satellite Data Record

Science.gov (United States)

Christensen, M.; McGarragh, G.; Thomas, G.; Povey, A.; Proud, S.; Poulsen, C. A.; Grainger, R. G.

2016-12-01

Radiative forcing by clouds, aerosols, and their interactions constitute some of the largest sources of uncertainties in the climate system (Chapter 7 IPCC, 2013). It is essential to understand the past through examination of long-term satellite observation records to provide insight into the uncertainty characteristics of these radiative forcers. As part of the ESA CCI (Climate Change Initiative) we have recently implemented a broadband radiative flux algorithm (known as BUGSrad) into the Optimal Retrieval for Aerosol and Cloud (ORAC) scheme. ORAC achieves radiative consistency of its aerosol and cloud products through an optimal estimation scheme and is highly versatile, enabling retrievals for numerous satellite sensors: ATSR, MODIS, VIIRS, AVHRR, SLSTR, SEVIRI, and AHI. An analysis of the 17-year well-calibrated Along Track Scanning Radiometer (ATSR) data is used to quantify trends in cloud and aerosol radiative effects over a wide range of spatiotemporal scales. The El Niño Southern Oscillation stands out as the largest contributing mode of variability to the radiative energy balance (long wave and shortwave fluxes) at the top of the atmosphere. Furthermore, trends in planetary albedo show substantial decreases across the Arctic Ocean (likely due to the melting of sea ice and snow) and modest increases in regions dominated by stratocumulus (e.g., off the coast of California) through notable increases in cloud fraction and liquid water path. Finally, changes in volcanic activity and biomass burning aerosol over this period show sizeable radiative forcing impacts at local-scales. We will demonstrate that radiative forcing from aerosols and clouds have played a significant role in the identified key climate processes using 17 years of satellite observational data.

Ice Sheet Change Detection by Satellite Image Differencing

Science.gov (United States)

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

2010-01-01

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

LAKE ICE DETECTION IN LOW-RESOLUTION OPTICAL SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

M. Tom

2018-05-01

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

Lake Ice Detection in Low-Resolution Optical Satellite Images

Science.gov (United States)

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

2018-05-01

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

Icing Detection over East Asia from Geostationary Satellite Data Using Machine Learning Approaches

Directory of Open Access Journals (Sweden)

Seongmun Sim

2018-04-01

Full Text Available Even though deicing or airframe coating technologies continue to develop, aircraft icing is still one of the critical threats to aviation. While the detection of potential icing clouds has been conducted using geostationary satellite data in the US and Europe, there is not yet a robust model that detects potential icing areas in East Asia. In this study, we proposed machine-learning-based icing detection models using data from two geostationary satellites—the Communication, Ocean, and Meteorological Satellite (COMS Meteorological Imager (MI and the Himawari-8 Advanced Himawari Imager (AHI—over Northeast Asia. Two machine learning techniques—random forest (RF and multinomial log-linear (MLL models—were evaluated with quality-controlled pilot reports (PIREPs as the reference data. The machine-learning-based models were compared to the existing models through five-fold cross-validation. The RF model for COMS MI produced the best performance, resulting in a mean probability of detection (POD of 81.8%, a mean overall accuracy (OA of 82.1%, and mean true skill statistics (TSS of 64.0%. One of the existing models, flight icing threat (FIT, produced relatively poor performance, providing a mean POD of 36.4%, a mean OA of 61.0, and a mean TSS of 9.7%. The Himawari-8 based models also produced performance comparable to the COMS models. However, it should be noted that very limited PIREP reference data were available especially for the Himawari-8 models, which requires further evaluation in the future with more reference data. The spatio-temporal patterns of the icing areas detected using the developed models were also visually examined using time-series satellite data.

A spatio-temporal autocorrelation change detection approach using hyper-temporal satellite data

CSIR Research Space (South Africa)

Kleynhans, W

2013-07-01

Full Text Available -1 IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia 21-26 July 2013 A SPATIO-TEMPORAL AUTOCORRELATION CHANGE DETECTION APPROACH USING HYPER-TEMPORAL SATELLITE DATA yzW. Kleynhans, yz,B.P Salmon,zK. J. Wessels...

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

Directory of Open Access Journals (Sweden)

Biao Wang

2017-08-01

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

A SERS-active sensor based on heterogeneous gold nanostar core-silver nanoparticle satellite assemblies for ultrasensitive detection of aflatoxinB1.

Science.gov (United States)

Li, Aike; Tang, Lijuan; Song, Dan; Song, Shanshan; Ma, Wei; Xu, Liguang; Kuang, Hua; Wu, Xiaoling; Liu, Liqiang; Chen, Xin; Xu, Chuanlai

2016-01-28

A surface-enhanced Raman scattering (SERS) sensor based on gold nanostar (Au NS) core-silver nanoparticle (Ag NP) satellites was fabricated for the first time to detect aflatoxinB1 (AFB1). We constructed the SERS sensor using AFB1 aptamer (DNA1)-modified Ag satellites and a complementary sequence (DNA2)-modified Au NS core. The Raman label (ATP) was modified on the surface of Ag satellites. The SERS signal was enhanced when the satellite NP was attached to the Au core NS. The AFB1 aptamer on the surface of Ag satellites would bind to the targets when AFB1 was present in the system, Ag satellites were then removed and the SERS signal decreased. This SERS sensor showed superior specificity for AFB1 and the linear detection range was from 1 to 1000 pg mL(-1) with the limit of detection (LOD) of 0.48 pg mL(-1). The excellent recovery experiment using peanut milk demonstrated that the sensor could be applied in food and environmental detection.

Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

Science.gov (United States)

Potter, Christopher S.

2013-01-01

Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

Detection of jet contrails from satellite images

Science.gov (United States)

Meinert, Dieter

1994-02-01

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

Recent history of large-scale ecosystem disturbances in North America derived from the AVHRR satellite record.

Science.gov (United States)

Christopher Potter; Tan Pang-Ning; Vipin Kumar; Chris Kucharik; Steven Klooster; Vanessa Genovese; Warren Cohen; Sean. Healey

2005-01-01

Ecosystem structure and function are strongly affected by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the advanced very high resolution radiometer (AVHRR...

Deep learning for the detection of barchan dunes in satellite images

Science.gov (United States)

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

2017-12-01

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

Integrated fiber optic sensors for hot spot detection and temperature field reconstruction in satellites

International Nuclear Information System (INIS)

Rapp, S; Baier, H

2010-01-01

Large satellites are often equipped with more than 1000 temperature sensors during the test campaign. Hundreds of them are still used for monitoring during launch and operation in space. This means an additional mass and especially high effort in assembly, integration and verification on a system level. So the use of fiber Bragg grating temperature sensors is investigated as they offer several advantages. They are lightweight, small in size and electromagnetically immune, which fits well in space applications. Their multiplexing capability offers the possibility to build extensive sensor networks including dozens of sensors of different types, such as strain sensors, accelerometers and temperature sensors. The latter allow the detection of hot spots and the reconstruction of temperature fields via proper algorithms, which is shown in this paper. A temperature sensor transducer was developed, which can be integrated into satellite sandwich panels with negligible mechanical influence. Mechanical and thermal vacuum tests were performed to verify the space compatibility of the developed sensor system. Proper reconstruction algorithms were developed to estimate the temperature field and detect thermal hot spots on the panel surface. A representative hardware demonstrator has been built and tested, which shows the capability of using an integrated fiber Bragg grating temperature sensor network for temperature field reconstruction and hot spot detection in satellite structures

Feature Detection Systems Enhance Satellite Imagery

Science.gov (United States)

2009-01-01

In 1963, during the ninth orbit of the Faith 7 capsule, astronaut Gordon Cooper skipped his nap and took some photos of the Earth below using a Hasselblad camera. The sole flier on the Mercury-Atlas 9 mission, Cooper took 24 photos - never-before-seen images including the Tibetan plateau, the crinkled heights of the Himalayas, and the jagged coast of Burma. From his lofty perch over 100 miles above the Earth, Cooper noted villages, roads, rivers, and even, on occasion, individual houses. In 1965, encouraged by the effectiveness of NASA s orbital photography experiments during the Mercury and subsequent Gemini manned space flight missions, U.S. Geological Survey (USGS) director William Pecora put forward a plan for a remote sensing satellite program that would collect information about the planet never before attainable. By 1972, NASA had built and launched Landsat 1, the first in a series of Landsat sensors that have combined to provide the longest continuous collection of space-based Earth imagery. The archived Landsat data - 37 years worth and counting - has provided a vast library of information allowing not only the extensive mapping of Earth s surface but also the study of its environmental changes, from receding glaciers and tropical deforestation to urban growth and crop harvests. Developed and launched by NASA with data collection operated at various times by the Agency, the National Oceanic and Atmospheric Administration (NOAA), Earth Observation Satellite Company (EOSAT, a private sector partnership that became Space Imaging Corporation in 1996), and USGS, Landsat sensors have recorded flooding from Hurricane Katrina, the building boom in Dubai, and the extinction of the Aral Sea, offering scientists invaluable insights into the natural and manmade changes that shape the world. Of the seven Landsat sensors launched since 1972, Landsat 5 and Landsat 7 are still operational. Though both are in use well beyond their intended lifespans, the mid

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

Directory of Open Access Journals (Sweden)

G. Máttyus

2013-05-01

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

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

Science.gov (United States)

Máttyus, G.

2013-05-01

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

Asynchronous Processing of a Constellation of Geostationary and Polar-Orbiting Satellites for Fire Detection and Smoke Estimation

Science.gov (United States)

Hyer, E. J.; Peterson, D. A.; Curtis, C. A.; Schmidt, C. C.; Hoffman, J.; Prins, E. M.

2014-12-01

The Fire Locating and Monitoring of Burning Emissions (FLAMBE) system converts satellite observations of thermally anomalous pixels into spatially and temporally continuous estimates of smoke release from open biomass burning. This system currently processes data from a constellation of 5 geostationary and 2 polar-orbiting sensors. Additional sensors, including NPP VIIRS and the imager on the Korea COMS-1 geostationary satellite, will soon be added. This constellation experiences schedule changes and outages of various durations, making the set of available scenes for fire detection highly variable on an hourly and daily basis. Adding to the complexity, the latency of the satellite data is variable between and within sensors. FLAMBE shares with many fire detection systems the goal of detecting as many fires as possible as early as possible, but the FLAMBE system must also produce a consistent estimate of smoke production with minimal artifacts from the changing constellation. To achieve this, NRL has developed a system of asynchronous processing and cross-calibration that permits satellite data to be used as it arrives, while preserving the consistency of the smoke emission estimates. This talk describes the asynchronous data ingest methodology, including latency statistics for the constellation. We also provide an overview and show results from the system we have developed to normalize multi-sensor fire detection for consistency.

A MODIS-Based Robust Satellite Technique (RST for Timely Detection of Oil Spilled Areas

Directory of Open Access Journals (Sweden)

Teodosio Lacava

2017-02-01

Full Text Available Natural crude-oil seepages, together with the oil released into seawater as a consequence of oil exploration/production/transportation activities, and operational discharges from tankers (i.e., oil dumped during cleaning actions represent the main sources of sea oil pollution. Satellite remote sensing can be a useful tool for the management of such types of marine hazards, namely oil spills, mainly owing to the synoptic view and the good trade-off between spatial and temporal resolution, depending on the specific platform/sensor system used. In this paper, an innovative satellite-based technique for oil spill detection, based on the general robust satellite technique (RST approach, is presented. It exploits the multi-temporal analysis of data acquired in the visible channels of the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Aqua satellite in order to automatically and quickly detect the presence of oil spills on the sea surface, with an attempt to minimize “false detections” caused by spurious effects associated with, for instance, cloud edges, sun/satellite geometries, sea currents, etc. The oil spill event that occurred in June 2007 off the south coast of Cyprus in the Mediterranean Sea has been considered as a test case. The resulting data, the reliability of which has been evaluated by both carrying out a confutation analysis and comparing them with those provided by the application of another independent MODIS-based method, showcase the potential of RST in identifying the presence of oil with a high level of accuracy.

Processing Satellite Imagery To Detect Waste Tire Piles

Science.gov (United States)

Skiles, Joseph; Schmidt, Cynthia; Wuinlan, Becky; Huybrechts, Catherine

2007-01-01

A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed

Satellite Detection of Orographic Gravity-wave Activity in the Winter Subtropical Stratosphere over Australia and Africa

Science.gov (United States)

Eckermann, S. D.; Wu, D. L.

2012-01-01

Orographic gravity-wave (OGW) parameterizations in models produce waves over subtropical mountain ranges in Australia and Africa that propagate into the stratosphere during austral winter and deposit momentum, affecting weather and climate. Satellite sensors have measured stratospheric GWs for over a decade, yet find no evidence of these waves. So are parameterizations failing here? Here we argue that the short wavelengths of subtropical OGWs place them near or below the detection limits of satellite sensors. To test this hypothesis, we reanalyze nine years of stratospheric radiances from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite during austral winter, applying new averaging techniques to maximize signal-to-noise and improve thresholds for OGW detection. Deep climatological enhancements in stratospheric OGW variance over specific mountain ranges in Australia and southern Africa are revealed for the first time, which exhibit temporal and vertical variations consistent with predicted OGW responses to varying background winds.

Visual attention based detection of signs of anthropogenic activities in satellite imagery

Energy Technology Data Exchange (ETDEWEB)

Skurikhin, Alexei N [Los Alamos National Laboratory

2010-10-13

With increasing deployment of satellite imaging systems, only a small fraction of collected data can be subject to expert scrutiny. We present and evaluate a two-tier approach to broad area search for signs of anthropogenic activities in high-resolution commercial satellite imagery. The method filters image information using semantically oriented interest points by combining Harris corner detection and spatial pyramid matching. The idea is that anthropogenic structures, such as rooftop outlines, fence corners, road junctions, are locally arranged in specific angular relations to each other. They are often oriented at approximately right angles to each other (which is known as rectilinearity relation). Detecting the rectilinearity provides an opportunity to highlight regions most likely to contain anthropogenic activity. This is followed by supervised classification of regions surrounding the detected corner points as man-made vs. natural scenes. We consider, in particular, a search for anthropogenic activities in uncluttered areas. In this paper, we proposed and evaluated a two-tier approach to broad area search for signs of anthropogenic activities. Results from experiments on high-resolution ({approx}0.6m) commercial satellite image data showed the potential applicability of this approach and its ability of achieving both high precision and recall rates. The main advantage of combining corner-based cueing with general object recognition is that the incorporation of domain specific knowledge even in its more general form, such as presence of comers, provides a useful cue to narrow the focus of search for signs of anthropogenic activities. Combination of comer based cueing with spatial pyramid matching addressed the issue of comer categorization. An important practical issue for further research is optimizing the balance between false positive and false negative rates. While the results presented in the paper are encouraging, the problem of an automated broad area

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

Science.gov (United States)

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

2011-07-01

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

Leveraging GeoTIFF Compatibility for Visualizing a New EASE-Grid 2.0 Global Satellite Passive Microwave Climate Record

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

2016-02-01

The historical record of satellite-derived passive microwave brightness temperatures comprises data from multiple imaging radiometers (SMMR, SSM/I-SSMIS, AMSR-E), spanning nearly 40 years of Earth observations from 1978 to the present. Passive microwave data are used to monitor time series of many climatological variables, including ocean wind speeds, cloud liquid water and sea ice concentrations and ice velocity. Gridded versions of passive microwave data have been produced using various map projections (polar stereographic, Lambert azimuthal equal-area, cylindrical equal-area, quarter-degree Platte-Carree) and data formats (flat binary, HDF). However, none of the currently available versions can be rendered in the common visualization standard, geoTIFF, without requiring cartographic reprojection. Furthermore, the reprojection details are complicated and often require expert knowledge of obscure software package options. We are producing a consistently calibrated, completely reprocessed data set of this valuable multi-sensor satellite record, using EASE-Grid 2.0, an improved equal-area projection definition that will require no reprojection for translation into geoTIFF. Our approach has been twofold: 1) define the projection ellipsoid to match the reference datum of the satellite data, and 2) include required file-level metadata for standard projection software to correctly render the data in the geoTIFF standard. The Calibrated, Enhanced Resolution Brightness Temperature (CETB) Earth System Data Record (ESDR), leverages image reconstruction techniques to enhance gridded spatial resolution to 3 km and uses newly available intersensor calibrations to improve the quality of derived geophysical products. We expect that our attention to easy geoTIFF compatibility will foster higher-quality analysis with the CETB product by enabling easy and correct intercomparison with other gridded and in situ data.

Synthesis of a quarter-century of satellite and airborne altimetry records to resolve long-term ice sheet elevation change

Science.gov (United States)

Nilsson, J.; Paolo, F. S.; Simonsen, S.; Gardner, A. S.

2017-12-01

Satellite and airborne altimetry provide the longest continuous record from which the mass balance of the Antarctic ice sheet can be derived, starting with the launch of ERS-1 in 1992. Accurate knowledge of the long-term mass balance is vital for understanding the geophysical processes governing the ice sheet contribution to present day sea-level rise. However, this record is comprised of several different measurement systems, with different accuracies and varying resolution. This poses a major challenge on the interpretation and reconstruction of consistent elevation-change time series for determining long-term ice sheet trends and variability. Previous studies using data from multiple satellite altimetry missions have relied on a cross-calibration technique based on crossover bias analysis to merge records from different sensors. This methodology, though accurate, limits the spatial coverage to typical resolutions of 10-50 km, restricting the approach to regional or continental-wide studies. In this study, we present a novel framework for seamless integration of heterogeneous altimetry records, using an adaptive least-squares minimization technique. The procedure allows reconstructing time series at fine spatial (sheet, including both data from the European Space Agency (ERS-1, ERS-2, Envisat and CryoSat-2) and NASA (ICESat and Operation IceBridge), with future inclusion of data from NASA's ICESat-2. Mission specific errors, estimated from independent airborne measurements and crossover analysis, are propagated to derive uncertainty bounds for each individual time series. We also perform an extensive analysis of the major corrections applied to raw satellite altimetry data to assess their overall effect on the estimated uncertainty. This methodology will allow us to determine robust long-term changes in the surface elevation of grounded Antarctic ice. Such a dataset will be invaluable to advancing ice sheet assimilation efforts and to disentangle causal

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

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Shaodan Li

2017-11-01

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

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

International Nuclear Information System (INIS)

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

2013-01-01

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

Multitemporal satellite change detection investigations for documentation and valorization of cultural landscape

Science.gov (United States)

Lasaponara, R.; Masini, n.

2012-04-01

archaeological prospection. Int J Remote Sens 27: 3607-3614. Lasaponara R, Masini N (2006b) Identification of archaeological buried remains based on Normalized Difference Vegetation Index (NDVI) from Quickbird satellite data. IEEE Geosci Remote S 3(3): 325-328. Lasaponara R, Masini N (2007a) Detection of archaeological crop marks by using satellite QuickBird multispectral imagery. J Archaeol Sci 34: 214-21. Lasaponara R, Masini N (2007b) Improving satellite Quickbird - based identification of landscape archaeological features trough tasselled cup transformation and PCA. 21st CIPA Symposium, Atene, 1-6 giugno 2007. Lasaponara R, Masini N (2010) Facing the archaeological looting in Peru by local spatial autocorrelation statistics of Very high resolution satellite imagery. In: Taniar D et al (Eds), Proceedings of ICSSA, The 2010 International Conference on Computational Science and its Application (Fukuoka-Japan, March 23 - 26, 2010), Springer, Berlin, 261-269. Lasaponara R, Masini N (2011) Satellite Remote Sensing in Archaeology : past, present and future. J Archaeol Sc 38: 1995-2002. Lasaponara R, Masini N, Rizzo E, Orefici G (2011) New discoveries in the Piramide Naranjada in Cahuachi (Peru) using satellite, Ground Probing Radar and magnetic investigations. J Archaeol Sci 38: 2031-2039. Lasaponara R, Masini N, Scardozzi G (2008) Satellite based archaeological research in ancient territory of Hierapolis. 1st International EARSeL Workshop. Advances in Remote Sensing for Archaeology and Cultural Heritage Management", CNR, Rome, September 30-October 4, Aracne, Rome, pp.11-16. Lillesand T M, Kiefer R W (2000) Remote Sensing and Image interpretation. John Wiley and Sons, New York. Masini N, Lasaponara R (2006) Satellite-based recognition of landscape archaeological features related to ancient human transformation. J Geophys Eng 3: 230-235, doi:10.1088/1742-2132/3/3/004. Masini N, Lasaponara R (2007) Investigating the spectral capability of QuickBird data to detect archaeological

Detection of movement artifact in recorded pulse oximeter saturation.

Science.gov (United States)

Poets, C F; Stebbens, V A

1997-10-01

Movement artifact (MA) must be detected when analysing recordings of pulse oximeter saturation (SpO2). Visual analysis of individual pulse waveforms is the safest, but also the most tedious, method for this purpose. We wanted to test the reliability of a computer algorithm (Edentec Motion Annotation System), based on a comparison between pulse and heart rate, for MA detection. Ten 12-h recordings of SpO2, pulse waveforms and heart rate from ten preterm infants were analysed for the presence of MA on the pulse waveform signal. These data were used to determine the sensitivity and specificity of the computer algorithm, and of the oximeter itself, in detecting MA. Recordings were divided into segments of 2.5 s duration to compare the movement identification methods. Of the segments 31% +/- 6% (mean +/- SD) contained MA. The computer algorithm identified 95% +/- 3% of these segments, the pulse oximeter only 18% +/- 11%. Specificity was 85% +/- 4% and 99% +/- 0%, respectively. SpO2 was signal showed MA during this time, leaving a significant potential for erroneous identification of hypoxaemia. Recordings of SpO2 do not allow a reliable identification of MA. Without additional information about movement artifact, a significant proportion of recording time of pulse oximeter signal may be regarded as demonstrating hypoxaemia which, in fact, simply reflects poor measurement conditions. The computer algorithm used in this study identified periods of movement artifact reliably.

Enhanced-Resolution Satellite Microwave Brightness Temperature Records for Mapping Boreal-Arctic Landscape Freeze-Thaw Heterogeneity

Science.gov (United States)

Kim, Y.; Du, J.; Kimball, J. S.

2017-12-01

The landscape freeze-thaw (FT) status derived from satellite microwave remote sensing is closely linked to vegetation phenology and productivity, surface energy exchange, evapotranspiration, snow/ice melt dynamics, and trace gas fluxes over land areas affected by seasonally frozen temperatures. A long-term global satellite microwave Earth System Data Record of daily landscape freeze-thaw status (FT-ESDR) was developed using similar calibrated 37GHz, vertically-polarized (V-pol) brightness temperatures (Tb) from SMMR, SSM/I, and SSMIS sensors. The FT-ESDR shows mean annual spatial classification accuracies of 90.3 and 84.3 % for PM and AM overpass retrievals relative surface air temperature (SAT) measurement based FT estimates from global weather stations. However, the coarse FT-ESDR gridding (25-km) is insufficient to distinguish finer scale FT heterogeneity. In this study, we tested alternative finer scale FT estimates derived from two enhanced polar-grid (3.125-km and 6-km resolution), 36.5 GHz V-pol Tb records derived from calibrated AMSR-E and AMSR2 sensor observations. The daily FT estimates are derived using a modified seasonal threshold algorithm that classifies daily Tb variations in relation to grid cell-wise FT thresholds calibrated using ERA-Interim reanalysis based SAT, downscaled using a digital terrain map and estimated temperature lapse rates. The resulting polar-grid FT records for a selected study year (2004) show mean annual spatial classification accuracies of 90.1% (84.2%) and 93.1% (85.8%) for respective PM (AM) 3.125km and 6-km Tb retrievals relative to in situ SAT measurement based FT estimates from regional weather stations. Areas with enhanced FT accuracy include water-land boundaries and mountainous terrain. Differences in FT patterns and relative accuracy obtained from the enhanced grid Tb records were attributed to several factors, including different noise contributions from underlying Tb processing and spatial mismatches between Tb

Comparison of semiautomated bird song recognition with manual detection of recorded bird song samples

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Lisa A. Venier

2017-12-01

Full Text Available Automated recording units are increasingly being used to sample wildlife populations. These devices can produce large amounts of data that are difficult to process manually. However, the information in the recordings can be summarized with semiautomated sound recognition software. Our objective was to assess the utility of the semiautomated bird song recognizers to produce data useful for conservation and sustainable forest management applications. We compared detection data generated from expert-interpreted recordings of bird songs collected with automated recording units and data derived from a semiautomated recognition process. We recorded bird songs at 109 sites in boreal forest in 2013 and 2014 using automated recording units. We developed bird-song recognizers for 10 species using Song Scope software (Wildlife Acoustics and each recognizer was used to scan a set of recordings that was also interpreted manually by an expert in birdsong identification. We used occupancy models to estimate the detection probability associated with each method. Based on these detection probability estimates we produced cumulative detection probability curves. In a second analysis we estimated detection probability of bird song recognizers using multiple 10-minute recordings for a single station and visit (35-63, 10-minute recordings in each of four one-week periods. Results show that the detection probability of most species from single 10-min recordings is substantially higher using expert-interpreted bird song recordings than using the song recognizer software. However, our results also indicate that detection probabilities for song recognizers can be significantly improved by using more than a single 10-minute recording, which can be easily done with little additional cost with the automate procedure. Based on these results we suggest that automated recording units and song recognizer software can be valuable tools to estimate detection probability and

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

Science.gov (United States)

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

2012-07-01

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

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

Directory of Open Access Journals (Sweden)

J.-M. Kang

2012-07-01

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

DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES

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M. A. Azzaoui

2016-06-01

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

Overview of intercalibration of satellite instruments

Science.gov (United States)

Chander, G.; Hewison, T.J.; Fox, N.; Wu, X.; Xiong, X.; Blackwell, W.J.

2013-01-01

Inter-calibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be inter-operable, the instruments must be cross-calibrated. To meet the stringent needs of such applications requires that instruments provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d'unités (SI) traceable Calibration and Validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stability monitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Inter-calibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Inter-calibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated inter-calibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms

Digital herbarium archives as a spatially extensive, taxonomically discriminate phenological record; a comparison to MODIS satellite imagery

Science.gov (United States)

Park, Isaac W.

2012-11-01

This study demonstrates that phenological information included in digital herbarium archives can produce annual phenological estimates correlated to satellite-derived green wave phenology at a regional scale (R = 0.183, P = 0.03). Thus, such records may be utilized in a fashion similar to other annual phenological records and, due to their longer duration and ability to discriminate among the various components of the plant community, hold significant potential for use in future research to supplement the deficiencies of other data sources as well as address a wide array of important issues in ecology and bioclimatology that cannot be addressed easily using more traditional methods.

Detection and retrieval of multi-layered cloud properties using satellite data

Science.gov (United States)

Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jianping; Nguyen, Louis; Khaiyer, Mandana M.

2005-10-01

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

Detecting the effects of hydrocarbon pollution in the Amazon forest using hyperspectral satellite images

International Nuclear Information System (INIS)

Arellano, Paul; Tansey, Kevin; Balzter, Heiko; Boyd, Doreen S.

2015-01-01

The global demand for fossil energy is triggering oil exploration and production projects in remote areas of the world. During the last few decades hydrocarbon production has caused pollution in the Amazon forest inflicting considerable environmental impact. Until now it is not clear how hydrocarbon pollution affects the health of the tropical forest flora. During a field campaign in polluted and pristine forest, more than 1100 leaf samples were collected and analysed for biophysical and biochemical parameters. The results revealed that tropical forests exposed to hydrocarbon pollution show reduced levels of chlorophyll content, higher levels of foliar water content and leaf structural changes. In order to map this impact over wider geographical areas, vegetation indices were applied to hyperspectral Hyperion satellite imagery. Three vegetation indices (SR, NDVI and NDVI 705 ) were found to be the most appropriate indices to detect the effects of petroleum pollution in the Amazon forest. - Highlights: • Leaf biochemical alterations in the rainforest are caused by petroleum pollution. • Lower levels of chlorophyll content are symptom of vegetation stress in polluted sites. • Increased foliar water content was found in vegetation near polluted sites. • Vegetation stress was detected by using vegetation indices from satellite images. • Polluted sites and hydrocarbon seepages in rainforest can be identified from space. - Hydrocarbon pollution in the Amazon forest is observed for first time from satellite data

Calibration Uncertainty in Ocean Color Satellite Sensors and Trends in Long-term Environmental Records

Science.gov (United States)

Turpie, Kevin R.; Eplee, Robert E., Jr.; Franz, Bryan A.; Del Castillo, Carlos

2014-01-01

Launched in late 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft is being evaluated by NASA to determine whether this sensor can continue the ocean color data record established through the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the MODerate resolution Imaging Spectroradiometer (MODIS). To this end, Goddard Space Flight Center generated evaluation ocean color data products using calibration techniques and algorithms established by NASA during the SeaWiFS and MODIS missions. The calibration trending was subjected to some initial sensitivity and uncertainty analyses. Here we present an introductory assessment of how the NASA-produced time series of ocean color is influenced by uncertainty in trending instrument response over time. The results help quantify the uncertainty in measuring regional and global biospheric trends in the ocean using satellite remote sensing, which better define the roles of such records in climate research.

Fetal beat detection in abdominal ECG recordings: global and time adaptive approaches

International Nuclear Information System (INIS)

Rodrigues, Rui

2014-01-01

We present a method for location of fetal QRS in maternal abdominal ECG recordings. This method’s initial, global approach was proposed in the context of the 2013 PhysioNet/Computing in Cardiology Challenge where it was tested on the 447 four channel one-minute recordings. The first step is filtering to eliminate baseline wander and high frequency noise. Upon detection, maternal QRS is removed on each channel using a filter applied to the other three channels. Next we locate fetal QRS on each channel and select the channel with the best set of detections. The method was awarded the third-best score in the Challenge event 1 with 278.755 (beats/minute) and the fourth-best score on event 2 with 28.201 ms. The 5 min long recordings of the Abdominal and Direct Fetal ECG Database were used to further test the method. This database contains five recordings obtained from women in labor. Results in these longer recordings were not satisfactory. This appears to be particularly the case in recordings with a more clearly non-stationary nature. In a new approach to our method, some changes are introduced. Two features are updated over time: the filter used to eliminate maternal QRS and the channel used to detect fetal beats. These changes significantly improved the QRS detection performance on longer recordings, but the scores on the 1 minute Challenge recordings were degraded. (paper)

Detecting robust signals of interannual variability of gross primary productivity in Asia from multiple terrestrial carbon cycle models and long-term satellite-based vegetation data

Science.gov (United States)

Ichii, K.; Kondo, M.; Ueyama, M.; Kato, T.; Ito, A.; Sasai, T.; Sato, H.; Kobayashi, H.; Saigusa, N.

2014-12-01

Long term record of satellite-based terrestrial vegetation are important to evaluate terrestrial carbon cycle models. In this study, we demonstrate how multiple satellite observation can be used for evaluating past changes in gross primary productivity (GPP) and detecting robust anomalies in terrestrial carbon cycle in Asia through our model-data synthesis analysis, Asia-MIP. We focused on the two different temporal coverages: long-term (30 years; 1982-2011) and decadal (10 years; 2001-2011; data intensive period) scales. We used a NOAA/AVHRR NDVI record for long-term analysis and multiple satellite data and products (e.g. Terra-MODIS, SPOT-VEGETATION) as historical satellite data, and multiple terrestrial carbon cycle models (e.g. BEAMS, Biome-BGC, ORCHIDEE, SEIB-DGVM, and VISIT). As a results of long-term (30 years) trend analysis, satellite-based time-series data showed that approximately 40% of the area has experienced a significant increase in the NDVI, while only a few areas have experienced a significant decreasing trend over the last 30 years. The increases in the NDVI were dominant in the sub-continental regions of Siberia, East Asia, and India. Simulations using the terrestrial biosphere models also showed significant increases in GPP, similar to the results for the NDVI, in boreal and temperate regions. A modeled sensitivity analysis showed that the increases in GPP are explained by increased temperature and precipitation in Siberia. Precipitation, solar radiation, CO2fertilization and land cover changes are important factors in the tropical regions. However, the relative contributions of each factor to GPP changes are different among the models. Year-to-year variations of terrestrial GPP were overall consistently captured by the satellite data and terrestrial carbon cycle models if the anomalies are large (e.g. 2003 summer GPP anomalies in East Asia and 2002 spring GPP anomalies in mid to high latitudes). The behind mechanisms can be consistently

Using Satellite Data to Monitor the Impacts of CyanoHAB Events on Drinking Water: A Texas Case Study

Science.gov (United States)

Overview of CYAN and it's mission to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying algal blooms and related water quality using satellite data records.

Forest fires detection in Indonesia using satellite Himawari-8 (case study: Sumatera and Kalimantan on august-october 2015)

Science.gov (United States)

Fatkhuroyan; Wati, Trinah; Panjaitan, Andersen

2017-01-01

Forest fires in Indonesia are serious problem affecting widely in material losses, health and environment. Himawari-8 as one of meteorological satellites with high resolution 0,5 km x 0,5 km can be used for forest fire monitoring and detection. Combination between 3, 4 and 6 channels using Sataid (Satellite Animation and Interactive Diagnosis) software will visualize forest fire in the study site. Monitoring which used Himawari-8 data on August, September and October 2015 can detect the distribution of smoke and the extents of forest fire in Sumatera and Kalimantan. The result showed the extent of forest fire can be identified for anticipation in the next step.

About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm

Directory of Open Access Journals (Sweden)

François Peyret

2013-01-01

Full Text Available Reliable GPS positioning in city environment is a key issue: actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results.

About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm

Science.gov (United States)

Peyraud, Sébastien; Bétaille, David; Renault, Stéphane; Ortiz, Miguel; Mougel, Florian; Meizel, Dominique; Peyret, François

2013-01-01

Reliable GPS positioning in city environment is a key issue actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results. PMID:23344379

Factors challenging our ability to detect long-term trends in ocean chlorophyll

Directory of Open Access Journals (Sweden)

C. Beaulieu

2013-04-01

Full Text Available Global climate change is expected to affect the ocean's biological productivity. The most comprehensive information available about the global distribution of contemporary ocean primary productivity is derived from satellite data. Large spatial patchiness and interannual to multidecadal variability in chlorophyll a concentration challenges efforts to distinguish a global, secular trend given satellite records which are limited in duration and continuity. The longest ocean color satellite record comes from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, which failed in December 2010. The Moderate Resolution Imaging Spectroradiometer (MODIS ocean color sensors are beyond their originally planned operational lifetime. Successful retrieval of a quality signal from the current Visible Infrared Imager Radiometer Suite (VIIRS instrument, or successful launch of the Ocean and Land Colour Instrument (OLCI expected in 2014 will hopefully extend the ocean color time series and increase the potential for detecting trends in ocean productivity in the future. Alternatively, a potential discontinuity in the time series of ocean chlorophyll a, introduced by a change of instrument without overlap and opportunity for cross-calibration, would make trend detection even more challenging. In this paper, we demonstrate that there are a few regions with statistically significant trends over the ten years of SeaWiFS data, but at a global scale the trend is not large enough to be distinguished from noise. We quantify the degree to which red noise (autocorrelation especially challenges trend detection in these observational time series. We further demonstrate how discontinuities in the time series at various points would affect our ability to detect trends in ocean chlorophyll a. We highlight the importance of maintaining continuous, climate-quality satellite data records for climate-change detection and attribution studies.

Reliability of recordings of subgingival calculus detected using an ultrasonic device.

Science.gov (United States)

Corraini, Priscila; López, Rodrigo

2015-04-01

To assess the intra-examiner reliability of recordings of subgingival calculus detected using an ultrasonic device, and to investigate the influence of subject-, tooth- and site-level factors on the reliability of these subgingival calculus recordings. On two occasions, within a 1-week interval, 147 adult periodontitis patients received a full-mouth clinical periodontal examination by a single trained examiner. Duplicate subgingival calculus recordings, in six sites per tooth, were obtained using an ultrasonic device for calculus detection and removal. Agreement was observed in 65 % of the 22,584 duplicate subgingival calculus recordings, ranging 45 % to 83 % according to subject. Using hierarchical modeling, disagreements in the subgingival calculus duplicate recordings were more likely in all other sites than the mid-buccal, and in sites harboring supragingival calculus. Disagreements were less likely in sites with PD ≥  4 mm and with furcation involvement  ≥  degree 2. Bleeding on probing or suppuration did not influence the reliability of subgingival calculus. At the subject-level, disagreements were less likely in patients presenting with the highest and lowest extent categories of the covariate subgingival calculus. The reliability of subgingival calculus recordings using the ultrasound technology is reasonable. The results of the present study suggest that the reliability of subgingival calculus recordings is not influenced by the presence of inflammation. Moreover, subgingival calculus can be more reliably detected using the ultrasound device at sites with higher need for periodontal therapy, i.e., sites presenting with deep pockets and premolars and molars with furcation involvement.

Arctic Sea Ice Thickness Estimation from CryoSat-2 Satellite Data Using Machine Learning-Based Lead Detection

Directory of Open Access Journals (Sweden)

Sanggyun Lee

2016-08-01

Full Text Available Satellite altimeters have been used to monitor Arctic sea ice thickness since the early 2000s. In order to estimate sea ice thickness from satellite altimeter data, leads (i.e., cracks between ice floes should first be identified for the calculation of sea ice freeboard. In this study, we proposed novel approaches for lead detection using two machine learning algorithms: decision trees and random forest. CryoSat-2 satellite data collected in March and April of 2011–2014 over the Arctic region were used to extract waveform parameters that show the characteristics of leads, ice floes and ocean, including stack standard deviation, stack skewness, stack kurtosis, pulse peakiness and backscatter sigma-0. The parameters were used to identify leads in the machine learning models. Results show that the proposed approaches, with overall accuracy >90%, produced much better performance than existing lead detection methods based on simple thresholding approaches. Sea ice thickness estimated based on the machine learning-detected leads was compared to the averaged Airborne Electromagnetic (AEM-bird data collected over two days during the CryoSat Validation experiment (CryoVex field campaign in April 2011. This comparison showed that the proposed machine learning methods had better performance (up to r = 0.83 and Root Mean Square Error (RMSE = 0.29 m compared to thickness estimation based on existing lead detection methods (RMSE = 0.86–0.93 m. Sea ice thickness based on the machine learning approaches showed a consistent decline from 2011–2013 and rebounded in 2014.

Extended seizure detection algorithm for intracranial EEG recordings

DEFF Research Database (Denmark)

Kjaer, T. W.; Remvig, L. S.; Henriksen, J.

2010-01-01

Objective: We implemented and tested an existing seizure detection algorithm for scalp EEG (sEEG) with the purpose of improving it to intracranial EEG (iEEG) recordings. Method: iEEG was obtained from 16 patients with focal epilepsy undergoing work up for resective epilepsy surgery. Each patient...... had 4 or 5 recorded seizures and 24 hours of non-ictal data were used for evaluation. Data from three electrodes placed at the ictal focus were used for the analysis. A wavelet based feature extraction algorithm delivered input to a support vector machine (SVM) classifier for distinction between ictal...... and non-ictal iEEG. We compare our results to a method published by Shoeb in 2004. While the original method on sEEG was optimal with the use of only four subbands in the wavelet analysis, we found that better seizure detection could be made if all subbands were used for iEEG. Results: When using...

Lower hybrid wave cavities detected by the FREJA satellite

International Nuclear Information System (INIS)

Pecseli, H.L.; Iranpour, K.; Holter, Oe.; Lybekk, B.; Holtet J.; Truelsen, J.; Holback, B.

1994-12-01

Localized electrostatic wave packets in the frequency region of lower-hybrid waves have been detected by the instruments on the FREJA satellite. These waves are usually associated with local density depletions indicating that the structures can be interpreted as wave filled cavities. The basic features of the observations are discussed. Based on simple statistical arguments it is attempted to present some characteristics which have to be accommodated within an ultimate theory describing the observed wave phenomena. An explanation in terms of collapse of nonlinear lower-hybrid waves is discussed in particular. It is argued that such a model seems inapplicable, at least in its simplest form, by providing time and length scales which are not in agreement with observations. Alternatives to this model are presented. 24 refs., 8 figs

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-07-01

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

Developing a Validated Long-Term Satellite-Based Albedo Record in the Central Alaska Range to Improve Regional Hydroclimate Reconstructions

Science.gov (United States)

Kreutz, K. J.; Godaire, T. P.; Burakowski, E. A.; Winski, D.; Campbell, S. W.; Wang, Z.; Sun, Q.; Hamilton, G. S.; Birkel, S. D.; Wake, C. P.; Osterberg, E. C.; Schaaf, C.

2015-12-01

Mountain glaciers around the world, particularly in Alaska, are experiencing significant surface mass loss from rapid climatic shifts and constitute a large proportion of the cryosphere's contribution to sea level rise. Surface albedo acts as a primary control on a glacier's mass balance, yet it is difficult to measure and quantify spatially and temporally in steep, mountainous settings. During our 2013 field campaign in Denali National Park to recover two surface to bedrock ice cores, we used an Analytical Spectral Devices (ASD) FieldSpec4 Standard Resolution spectroradiometer to measure incoming solar radiation, outgoing surface reflectance and optical grain size on the Kahiltna Glacier and at the Kahiltna Base Camp. A Campbell Scientific automatic weather station was installed on Mount Hunter (3900m) in June 2013, complementing a longer-term (2008-present) station installed at Kahiltna Base Camp (2100m). Use of our in situ data aids in the validation of surface albedo values derived from Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite imagery. Comparisons are made between ASD FieldSpec4 ground measurements and 500m MODIS imagery to assess the ability of MODIS to capture the variability of surface albedo across the glacier surface. The MODIS MCD43A3 BRDF/Albedo Product performs well at Kahiltna Base Camp (albedo (10-28% relative to ASD data) appear to occur along the Kahiltna Glacier due to the snow-free valley walls being captured in the 500m MODIS footprint. Incorporating Landsat imagery will strengthen our interpretations and has the potential to produce a long-term (1982-present) validated satellite albedo record for steep and mountainous terrain. Once validation is complete, we will compare the satellite-derived albedo record to the Denali ice core accumulation rate, aerosol records (i.e. volcanics and biomass burning), and glacier mass balance data. This research will ultimately contribute to an improved understanding of the

Equalization and detection for digital communication over nonlinear bandlimited satellite communication channels. Ph.D. Thesis

Science.gov (United States)

Gutierrez, Alberto, Jr.

1995-01-01

This dissertation evaluates receiver-based methods for mitigating the effects due to nonlinear bandlimited signal distortion present in high data rate satellite channels. The effects of the nonlinear bandlimited distortion is illustrated for digitally modulated signals. A lucid development of the low-pass Volterra discrete time model for a nonlinear communication channel is presented. In addition, finite-state machine models are explicitly developed for a nonlinear bandlimited satellite channel. A nonlinear fixed equalizer based on Volterra series has previously been studied for compensation of noiseless signal distortion due to a nonlinear satellite channel. This dissertation studies adaptive Volterra equalizers on a downlink-limited nonlinear bandlimited satellite channel. We employ as figure of merits performance in the mean-square error and probability of error senses. In addition, a receiver consisting of a fractionally-spaced equalizer (FSE) followed by a Volterra equalizer (FSE-Volterra) is found to give improvement beyond that gained by the Volterra equalizer. Significant probability of error performance improvement is found for multilevel modulation schemes. Also, it is found that probability of error improvement is more significant for modulation schemes, constant amplitude and multilevel, which require higher signal to noise ratios (i.e., higher modulation orders) for reliable operation. The maximum likelihood sequence detection (MLSD) receiver for a nonlinear satellite channel, a bank of matched filters followed by a Viterbi detector, serves as a probability of error lower bound for the Volterra and FSE-Volterra equalizers. However, this receiver has not been evaluated for a specific satellite channel. In this work, an MLSD receiver is evaluated for a specific downlink-limited satellite channel. Because of the bank of matched filters, the MLSD receiver may be high in complexity. Consequently, the probability of error performance of a more practical

Challenges of coordinating global climate observations - Role of satellites in climate monitoring

Science.gov (United States)

Richter, C.

2017-12-01

Global observation of the Earth's atmosphere, ocean and land is essential for identifying climate variability and change, and for understanding their causes. Observation also provides data that are fundamental for evaluating, refining and initializing the models that predict how the climate system will vary over the months and seasons ahead, and that project how climate will change in the longer term under different assumptions concerning greenhouse gas emissions and other human influences. Long-term observational records have enabled the Intergovernmental Panel on Climate Change to deliver the message that warming of the global climate system is unequivocal. As the Earth's climate enters a new era, in which it is forced by human activities, as well as natural processes, it is critically important to sustain an observing system capable of detecting and documenting global climate variability and change over long periods of time. High-quality climate observations are required to assess the present state of the ocean, cryosphere, atmosphere and land and place them in context with the past. The global observing system for climate is not a single, centrally managed observing system. Rather, it is a composite "system of systems" comprising a set of climate-relevant observing, data-management, product-generation and data-distribution systems. Data from satellites underpin many of the Essential Climate Variables(ECVs), and their historic and contemporary archives are a key part of the global climate observing system. In general, the ECVs will be provided in the form of climate data records that are created by processing and archiving time series of satellite and in situ measurements. Early satellite data records are very valuable because they provide unique observations in many regions which were not otherwise observed during the 1970s and which can be assimilated in atmospheric reanalyses and so extend the satellite climate data records back in time.

Analysis of raw AIS spectrum recordings from a LEO satellite

DEFF Research Database (Denmark)

Larsen, Jesper Abildgaard; Mortensen, Hans Peter

2014-01-01

The AAUSAT3 satellite is a 1U cubesat, which has been developed by students at Aalborg University, Denmark in collaboration with the Danish Maritime Authority. The satellite was launched in February 2013 on a mission to monitor ships from space using their AIS broadcast signals as an indication...... of position. The SDR receiver developed to listen for these AIS signals also allows for sampling and storing of the raw intermediate frequency spectrum, which has been used in order to map channel utilization over the areas of interest for the mission, which is mainly the arctic regions. The SDR based...... receiver used onboard the satellite is using a single chip front-end solution, which down converts the AIS signal located around 162 MHz into an intermediate frequency, with a up to 200 kHz bandwidth. This I/F signal is sampled with a 750 kSPS A/D converter and further processed by an Analog Devices DSP...

Early Flood Detection for Rapid Humanitarian Response: Harnessing Near Real-Time Satellite and Twitter Signals

Directory of Open Access Journals (Sweden)

Brenden Jongman

2015-10-01

Full Text Available Humanitarian organizations have a crucial role in response and relief efforts after floods. The effectiveness of disaster response is contingent on accurate and timely information regarding the location, timing and impacts of the event. Here we show how two near-real-time data sources, satellite observations of water coverage and flood-related social media activity from Twitter, can be used to support rapid disaster response, using case-studies in the Philippines and Pakistan. For these countries we analyze information from disaster response organizations, the Global Flood Detection System (GFDS satellite flood signal, and flood-related Twitter activity analysis. The results demonstrate that these sources of near-real-time information can be used to gain a quicker understanding of the location, the timing, as well as the causes and impacts of floods. In terms of location, we produce daily impact maps based on both satellite information and social media, which can dynamically and rapidly outline the affected area during a disaster. In terms of timing, the results show that GFDS and/or Twitter signals flagging ongoing or upcoming flooding are regularly available one to several days before the event was reported to humanitarian organizations. In terms of event understanding, we show that both GFDS and social media can be used to detect and understand unexpected or controversial flood events, for example due to the sudden opening of hydropower dams or the breaching of flood protection. The performance of the GFDS and Twitter data for early detection and location mapping is mixed, depending on specific hydrological circumstances (GFDS and social media penetration (Twitter. Further research is needed to improve the interpretation of the GFDS signal in different situations, and to improve the pre-processing of social media data for operational use.

The Satellite Passive-Microwave Record of Sea Ice in the Ross Sea Since Late 1978

Science.gov (United States)

Parkinson, Claire L.

2009-01-01

Satellites have provided us with a remarkable ability to monitor many aspects of the globe day-in and day-out and sea ice is one of numerous variables that by now have quite substantial satellite records. Passive-microwave data have been particularly valuable in sea ice monitoring, with a record that extends back to August 1987 on daily basis (for most of the period), to November 1970 on a less complete basis (again for most of the period), and to December 1972 on a less complete basis. For the period since November 1970, Ross Sea sea ice imagery is available at spatial resolution of approximately 25 km. This allows good depictions of the seasonal advance and retreat of the ice cover each year, along with its marked interannual variability. The Ross Sea ice extent typically reaches a minimum of approximately 0.7 x 10(exp 6) square kilometers in February, rising to a maximum of approximately 4.0 x 10(exp 6) square kilometers in September, with much variability among years for both those numbers. The Ross Sea images show clearly the day-by-day activity greatly from year to year. Animations of the data help to highlight the dynamic nature of the Ross Sea ice cover. The satellite data also allow calculation of trends in the ice cover over the period of the satellite record. Using linear least-squares fits, the Ross Sea ice extent increased at an average rate of 12,600 plus or minus 1,800 square kilometers per year between November 1978 and December 2007, with every month exhibiting increased ice extent and the rates of increase ranging from a low of 7,500 plus or minus 5,000 square kilometers per year for the February ice extents to a high of 20,300 plus or minus 6,100 kilometers per year for the October ice extents. On a yearly average basis, for 1979-2007 the Ross Sea ice extent increased at a rate of 4.8 plus or minus 1.6 % per decade. Placing the Ross Sea in the context of the Southern Ocean as a whole, over the November 1978-December 2007 period the Ross Sea had

Detection of the Velocity Shear Effect on the Spatial Distributions of the Galactic Satellites in Isolated Systems

Science.gov (United States)

Lee, Jounghun; Choi, Yun-Young

2015-02-01

We report a detection of the effect of the large-scale velocity shear on the spatial distributions of the galactic satellites around the isolated hosts. Identifying the isolated galactic systems, each of which consists of a single host galaxy and its satellites, from the Seventh Data Release of the Sloan Digital Sky Survey and reconstructing linearly the velocity shear field in the local universe, we measure the alignments between the relative positions of the satellites from their isolated hosts and the principal axes of the local velocity shear tensors projected onto the plane of sky. We find a clear signal that the galactic satellites in isolated systems are located preferentially along the directions of the minor principal axes of the large-scale velocity shear field. Those galactic satellites that are spirals, are brighter, are located at distances larger than the projected virial radii of the hosts, and belong to the spiral hosts yield stronger alignment signals, which implies that the alignment strength depends on the formation and accretion epochs of the galactic satellites. It is also shown that the alignment strength is quite insensitive to the cosmic web environment, as well as the size and luminosity of the isolated hosts. Although this result is consistent with the numerical finding of Libeskind et al. based on an N-body experiment, owing to the very low significance of the observed signals, it remains inconclusive whether or not the velocity shear effect on the satellite distribution is truly universal.

DETECTION OF THE VELOCITY SHEAR EFFECT ON THE SPATIAL DISTRIBUTIONS OF THE GALACTIC SATELLITES IN ISOLATED SYSTEMS

International Nuclear Information System (INIS)

Lee, Jounghun; Choi, Yun-Young

2015-01-01

We report a detection of the effect of the large-scale velocity shear on the spatial distributions of the galactic satellites around the isolated hosts. Identifying the isolated galactic systems, each of which consists of a single host galaxy and its satellites, from the Seventh Data Release of the Sloan Digital Sky Survey and reconstructing linearly the velocity shear field in the local universe, we measure the alignments between the relative positions of the satellites from their isolated hosts and the principal axes of the local velocity shear tensors projected onto the plane of sky. We find a clear signal that the galactic satellites in isolated systems are located preferentially along the directions of the minor principal axes of the large-scale velocity shear field. Those galactic satellites that are spirals, are brighter, are located at distances larger than the projected virial radii of the hosts, and belong to the spiral hosts yield stronger alignment signals, which implies that the alignment strength depends on the formation and accretion epochs of the galactic satellites. It is also shown that the alignment strength is quite insensitive to the cosmic web environment, as well as the size and luminosity of the isolated hosts. Although this result is consistent with the numerical finding of Libeskind et al. based on an N-body experiment, owing to the very low significance of the observed signals, it remains inconclusive whether or not the velocity shear effect on the satellite distribution is truly universal

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

Science.gov (United States)

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

2018-04-01

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

The Skeletal Muscle Satellite Cell

Science.gov (United States)

2011-01-01

The skeletal muscle satellite cell was first described and named based on its anatomic location between the myofiber plasma and basement membranes. In 1961, two independent studies by Alexander Mauro and Bernard Katz provided the first electron microscopic descriptions of satellite cells in frog and rat muscles. These cells were soon detected in other vertebrates and acquired candidacy as the source of myogenic cells needed for myofiber growth and repair throughout life. Cultures of isolated myofibers and, subsequently, transplantation of single myofibers demonstrated that satellite cells were myogenic progenitors. More recently, satellite cells were redefined as myogenic stem cells given their ability to self-renew in addition to producing differentiated progeny. Identification of distinctively expressed molecular markers, in particular Pax7, has facilitated detection of satellite cells using light microscopy. Notwithstanding the remarkable progress made since the discovery of satellite cells, researchers have looked for alternative cells with myogenic capacity that can potentially be used for whole body cell-based therapy of skeletal muscle. Yet, new studies show that inducible ablation of satellite cells in adult muscle impairs myofiber regeneration. Thus, on the 50th anniversary since its discovery, the satellite cell’s indispensable role in muscle repair has been reaffirmed. PMID:22147605

Spatial and energy distributions of satellite-speed helium atoms reflected from satellite-type surfaces

International Nuclear Information System (INIS)

Liu, S.M.; Rodgers, W.E.; Knuth, E.L.

1977-01-01

Interactions of satellite-speed helium atoms (accelerated in an expansion from an arc-heated supersonic-molecular-beam source) with practical satellite surfaces have been investigated experimentally. The density and energy distributions of the scattered atoms were measured using a detection system developed for this study. This detection system includes (a) a target positioning mechanism, (b) a detector rotating mechanism, and (c) a mass spectrometer and/or a retarding-field energy analyzer. (Auth.)

The effect of subionospheric propagation on whistlers recorded by the DEMETER satellite – observation and modelling

Directory of Open Access Journals (Sweden)

O. E. Ferencz

2007-06-01

Full Text Available During a routine analysis of whistlers on the wide-band VLF recording of the DEMETER satellite, a specific signal structure of numerous fractional-hop whistlers, termed the "Spiky Whistler" (SpW was identified. These signals appear to be composed of a conventional whistler combined by the compound mode-patterns of guided wave propagation, suggesting a whistler excited by a lightning "tweek" spheric. Rigorous, full-wave modelling of tweeks, formed by the long subionospheric guided spheric propagation and of the impulse propagation across an arbitrarily inhomogeneous ionosphere, gave an accurate description of the SpW signals. The electromagnetic impulses excited by vertical, preferably CG lightning discharge, exhibited the effects of guided behaviour and of the dispersive ionospheric plasma along their paths. This modelling and interpretation provides a consistent way to determine the generation and propagation characteristics of the recorded SpW signals, as well as to describe the traversed medium.

Detection of a weak meddy-like anomaly from high-resolution satellite SST maps

Directory of Open Access Journals (Sweden)

Mikhail Emelianov

2012-09-01

Full Text Available Despite the considerable impact of meddies on climate through the long-distance transport of properties, a consistent observation of meddy generation and propagation in the ocean is rather elusive. Meddies propagate at about 1000 m below the ocean surface, so satellite sensors are not able to detect them directly and finding them in the open ocean is more fortuitous than intentional. However, a consistent census of meddies and their paths is required in order to gain knowledge about their role in transporting properties such as heat and salt. In this paper we propose a new methodology for processing high-resolution sea surface temperature maps in order to detect meddy-like anomalies in the open ocean on a near-real-time basis. We present an example of detection, involving an atypical meddy-like anomaly that was confirmed as such by in situ measurements.

Use of the high-resolution satellite images for detection of fractures related to the ore deposits

Science.gov (United States)

Cruz-Mondaca, M.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.

2012-12-01

The Aster and GeoEye satellite high-resolution images were used to detect the structures related to the fracturing of the upper crust in the North of Chile. In particular, lineament analysis has been applied to detect the presence of epithermal fluids of low sulfurization associated with the Paleozoic ore deposits. These results have been compared with the location of the minerals altered by the presence of geothermal fluids detected using the spectral libraries. Later, the presence of fractures has been corroborated during recognition of fractures in situ and the geochemical analysis of samples of minerals altered by the presence of fluids. It was shown that the results obtained are relevant for the gold vein detection.

DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

Science.gov (United States)

Kalia, S.; Li, S.; Ganguly, S.; Nemani, R. R.

2017-12-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remotesensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud/shadow mask from geostationary satellite data iscritical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds, which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classifycloud/shadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoder-decoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multi-spectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

Multitemporal satellite data analyses for archaeological mark detection: preliminary results in Italy and Argentina

Science.gov (United States)

Lasaponara, Rosa; Masini, Nicola

2014-05-01

The current availability of very high resolution satellite data provides an excellent tool to detect and monitor archaeological marks, namely spectral and spatial anomalies linked to the presence of buried archaeological remains from a landscape view down to local scale (single site) investigations. Since the end of the nineteenth century, aerial photography has been the remote sensing tool most widely used in archaeology for surveying both surface and sub-surface archaeological remains. Aerial photography was a real "revolution" in archaeology being an excellent tool for investigations addressed at detecting underground archaeological structures through the reconnaissance of the so-called "archaeological marks" generally grouped and named as "soil","crop marks" "snow marks", and also recently "weed marks" (Lasaponara and Masini). Such marks are generally visible only from an aerial view (see detail in Lasaponara and Masini 2009, Ciminale et al. 2009, Masini and Lasaponara 2006 Lasaponara et al 2011) . In particular, soil marks are changes in soil colour or texture due to the presence of surface and shallow remains. Crop marks are changes in crop texture linked to as differences in height or colour of crops which are under stress due to lack of water or deficiencies in other nutrients caused by the presence of masonry structures in the subsoil. Crop marks can also be formed above damp and nutritious soil of buried pits and ditches. Such marks are generally visible only from an aerial view, especially during the spring season. In the context of the Project "Remote sensing technologies applied to the management of natural and cultural heritage in sites located in Italy and Argentina: from risk monitoring to mitigatin startegies P@an_sat", funded by the Italian Ministry of Foreign Affair, we tested the capability of multitemporal data, from active and passive satellite sensors, in the detection of "archaeological marks". The areas of interested were selected from

Non-Stationary Internal Tides Observed with Satellite Altimetry

Science.gov (United States)

Ray, Richard D.; Zaron, E. D.

2011-01-01

Temporal variability of the internal tide is inferred from a 17-year combined record of Topex/Poseidon and Jason satellite altimeters. A global sampling of along-track sea-surface height wavenumber spectra finds that non-stationary variance is generally 25% or less of the average variance at wavenumbers characteristic of mode-l tidal internal waves. With some exceptions the non-stationary variance does not exceed 0.25 sq cm. The mode-2 signal, where detectable, contains a larger fraction of non-stationary variance, typically 50% or more. Temporal subsetting of the data reveals interannual variability barely significant compared with tidal estimation error from 3-year records. Comparison of summer vs. winter conditions shows only one region of noteworthy seasonal changes, the northern South China Sea. Implications for the anticipated SWOT altimeter mission are briefly discussed.

Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll-a data.

Science.gov (United States)

Mélin, F; Vantrepotte, V; Chuprin, A; Grant, M; Jackson, T; Sathyendranath, S

2017-12-15

In this work, trend estimates are used as indicators to compare the multi-annual variability of different satellite chlorophyll- a (Chl a ) data and to assess the fitness-for-purpose of multi-mission Chl a products as climate data records (CDR). Under the assumption that single-mission products are free from spurious temporal artifacts and can be used as benchmark time series, multi-mission CDRs should reproduce the main trend patterns observed by single-mission series when computed over their respective periods. This study introduces and applies quantitative metrics to compare trend distributions from different data records. First, contingency matrices compare the trend diagnostics associated with two satellite products when expressed in binary categories such as existence, significance and signs of trends. Contingency matrices can be further summarized by metrics such as Cohen's κ index that rates the overall agreement between the two distributions of diagnostics. A more quantitative measure of the discrepancies between trends is provided by the distributions of differences between trend slopes. Thirdly, maps of the level of significance P of a t -test quantifying the degree to which two trend estimates differ provide a statistical, spatially-resolved, evaluation. The proposed methodology is applied to the multi-mission Ocean Colour-Climate Change Initiative (OC-CCI) Chl a data. The agreement between trend distributions associated with OC-CCI data and single-mission products usually appears as good as when single-mission products are compared. As the period of analysis is extended beyond 2012 to 2015, the level of agreement tends to be degraded, which might be at least partly due to the aging of the MODIS sensor on-board Aqua. On the other hand, the trends displayed by the OC-CCI series over the short period 2012-2015 are very consistent with those observed with VIIRS. These results overall suggest that the OC-CCI Chl a data can be used for multi-annual time

Detection of land cover change using an Artificial Neural Network on a time-series of MODIS satellite data

CSIR Research Space (South Africa)

Olivier, JC

2007-11-01

Full Text Available An Artificial Neural Network (ANN) is proposed to detect human-induced land cover change using a sliding window through a time-series of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite surface reflectance pixel values. Training...

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

Science.gov (United States)

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

2017-12-01

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

Development of Next Generation Memory Test Experiment for Deployment on a Small Satellite

Science.gov (United States)

MacLeod, Todd; Ho, Fat D.

2012-01-01

The original Memory Test Experiment successfully flew on the FASTSAT satellite launched in November 2010. It contained a single Ramtron 512K ferroelectric memory. The memory device went through many thousands of read/write cycles and recorded any errors that were encountered. The original mission length was schedule to last 6 months but was extended to 18 months. New opportunities exist to launch a similar satellite and considerations for a new memory test experiment should be examined. The original experiment had to be designed and integrated in less than two months, so the experiment was a simple design using readily available parts. The follow-on experiment needs to be more sophisticated and encompass more technologies. This paper lays out the considerations for the design and development of this follow-on flight memory experiment. It also details the results from the original Memory Test Experiment that flew on board FASTSAT. Some of the design considerations for the new experiment include the number and type of memory devices to be used, the kinds of tests that will be performed, other data needed to analyze the results, and best use of limited resources on a small satellite. The memory technologies that are considered are FRAM, FLASH, SONOS, Resistive Memory, Phase Change Memory, Nano-wire Memory, Magneto-resistive Memory, Standard DRAM, and Standard SRAM. The kinds of tests that could be performed are read/write operations, non-volatile memory retention, write cycle endurance, power measurements, and testing Error Detection and Correction schemes. Other data that may help analyze the results are GPS location of recorded errors, time stamp of all data recorded, radiation measurements, temperature, and other activities being perform by the satellite. The resources of power, volume, mass, temperature, processing power, and telemetry bandwidth are extremely limited on a small satellite. Design considerations must be made to allow the experiment to not interfere

Wildfire Detection and Tracking over Greece Using MSG‑SEVIRI Satellite Data

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Nicolaos I. Sifakis

2011-03-01

Full Text Available Greece is a high risk Mediterranean country with respect to wildfires. This risk has been increasing under the impact of climate change, and in summer 2007 approximately 200,000 ha of vegetated land were burnt. The SEVIRI sensor, on board the Meteosat Second Generation (MSG geostationary satellite, is the only spaceborne sensor providing five and 15-minute observations of Europe in 12 spectral channels, including a short-wave infrared band sensitive to fire radiative temperature. In August 2007, when the bulk of the destructive wildfires started in Greece, the receiving station, operated by the Institute for Space Applications and Remote Sensing, provided us with a time series of MSG-SEVIRI images. These images were processed in order to test the reliability of a real‑time detection and tracking system and its complementarity to conventional means provided by the Fire Brigade. EUMETSAT’s Active Fire Monitoring (FIR image processing algorithm for fire detection and monitoring was applied to SEVIRI data, then fine-tuned according to Greek conditions, and evaluated. Alarm announcements from the Fire Brigade’s archives were used as ground truthing data in order to assess detection reliability and system performance. During the examined period, MSG-SEVIRI data successfully detected 82% of the fire events in Greek territory with less than 1% false alarms.

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

Science.gov (United States)

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

2009-12-01

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

Satellite failures revisited

Science.gov (United States)

Balcerak, Ernie

2012-12-01

In January 1994, the two geostationary satellites known as Anik-E1 and Anik-E2, operated by Telesat Canada, failed one after the other within 9 hours, leaving many northern Canadian communities without television and data services. The outage, which shut down much of the country's broadcast television for hours and cost Telesat Canada more than $15 million, generated significant media attention. Lam et al. used publicly available records to revisit the event; they looked at failure details, media coverage, recovery effort, and cost. They also used satellite and ground data to determine the precise causes of those satellite failures. The researchers traced the entire space weather event from conditions on the Sun through the interplanetary medium to the particle environment in geostationary orbit.

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

Science.gov (United States)

Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

2018-06-01

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

On the reliable use of satellite-derived surface water products for global flood monitoring

Science.gov (United States)

Hirpa, F. A.; Revilla-Romero, B.; Thielen, J.; Salamon, P.; Brakenridge, R.; Pappenberger, F.; de Groeve, T.

2015-12-01

Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response management. To this end, real-time flood forecasting and satellite-based detection systems have been developed at global scale. However, due to the limited availability of up-to-date ground observations, the reliability of these systems for real-time applications have not been assessed in large parts of the globe. In this study, we performed comparative evaluations of the commonly used satellite-based global flood detections and operational flood forecasting system using 10 major flood cases reported over three years (2012-2014). Specially, we assessed the flood detection capabilities of the near real-time global flood maps from the Global Flood Detection System (GFDS), and from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the operational forecasts from the Global Flood Awareness System (GloFAS) for the major flood events recorded in global flood databases. We present the evaluation results of the global flood detection and forecasting systems in terms of correctly indicating the reported flood events and highlight the exiting limitations of each system. Finally, we propose possible ways forward to improve the reliability of large scale flood monitoring tools.

Detecting inpatient falls by using natural language processing of electronic medical records

Directory of Open Access Journals (Sweden)

Toyabe Shin-ichi

2012-12-01

Full Text Available Abstract Background Incident reporting is the most common method for detecting adverse events in a hospital. However, under-reporting or non-reporting and delay in submission of reports are problems that prevent early detection of serious adverse events. The aim of this study was to determine whether it is possible to promptly detect serious injuries after inpatient falls by using a natural language processing method and to determine which data source is the most suitable for this purpose. Methods We tried to detect adverse events from narrative text data of electronic medical records by using a natural language processing method. We made syntactic category decision rules to detect inpatient falls from text data in electronic medical records. We compared how often the true fall events were recorded in various sources of data including progress notes, discharge summaries, image order entries and incident reports. We applied the rules to these data sources and compared F-measures to detect falls between these data sources with reference to the results of a manual chart review. The lag time between event occurrence and data submission and the degree of injury were compared. Results We made 170 syntactic rules to detect inpatient falls by using a natural language processing method. Information on true fall events was most frequently recorded in progress notes (100%, incident reports (65.0% and image order entries (12.5%. However, F-measure to detect falls using the rules was poor when using progress notes (0.12 and discharge summaries (0.24 compared with that when using incident reports (1.00 and image order entries (0.91. Since the results suggested that incident reports and image order entries were possible data sources for prompt detection of serious falls, we focused on a comparison of falls found by incident reports and image order entries. Injury caused by falls found by image order entries was significantly more severe than falls detected by

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

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N. Champion

2012-08-01

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

Detection of pear thrips damage using satellite imagery data

Science.gov (United States)

James E. Vogelmann; Barrett N. Rock

1991-01-01

This study evaluates the potential of measuring, mapping and monitoring sugar maple damage caused by pear thrips in southern Vermont and northwestern Massachusetts using satellite imagery data. Landsat Thematic Mapper (TM) data were obtained during a major thrips infestation in June 1988, and were compared with satellite data acquired during June 1984 (before pear...

Atrial fibrillation detected by external loop recording for seven days or two-day simultaneous Holter recording: A comparison in patients with ischemic stroke or transient ischemic attack.

Science.gov (United States)

Sejr, Michala Herskind; Nielsen, Jens Cosedis; Damgaard, Dorte; Sandal, Birgitte Forsom; May, Ole

Atrial fibrillation (AF) is the most common cardiac cause of ischemic stroke and transient ischemic attack (IS/TIA). To compare the diagnostic value of seven-day external loop recording (ELR) and two-day Holter recording for detecting AF after IS/TIA. 191 IS/TIA patients without AF history. Endpoint was AF >30s. We started two-day Holter recording and seven-day ELR simultaneously. Seven-day ELR and two-day Holter recording detected the same three AF patients. ELR detected another six patients with AF adjudicated by cardiologists, four detections after Holter (3 vs. 7, p=0.125) and two false-positive detections during Holter. Seven-day ELR automatically classified 50/191 patients (26%) with AF, but only 7/50 (14%) were confirmed as AF by cardiologists. Seven-day ELR did not detect significantly more patients with AF than two-day Holter recording. 86% of patients with ELR-classified AF were false positives, indicating a poor performance of the automatic AF detection algorithm used. Copyright © 2017 Elsevier Inc. All rights reserved.

Insertable cardiac event recorder in detection of atrial fibrillation after cryptogenic stroke: an audit report.

Science.gov (United States)

Etgen, Thorleif; Hochreiter, Manfred; Mundel, Markus; Freudenberger, Thomas

2013-07-01

Atrial fibrillation (AF) is the most frequent risk factor in ischemic stroke but often remains undetected. We analyzed the value of insertable cardiac event recorder in detection of AF in a 1-year cohort of patients with cryptogenic ischemic stroke. All patients with cryptogenic stroke and eligibility for oral anticoagulation were offered the insertion of a cardiac event recorder. Regular follow-up for 1 year recorded the incidence of AF. Of the 393 patients with ischemic stroke, 65 (16.5%) had a cryptogenic stroke, and in 22 eligible patients, an event recorder was inserted. After 1 year, in 6 of 22 patients (27.3%), AF was detected. These preliminary data show that insertion of cardiac event recorder was eligible in approximately one third of patients with cryptogenic stroke and detected in approximately one quarter of these patients new AF.

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

Science.gov (United States)

Kit, Oleksandr; Lüdeke, Matthias

2013-09-01

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

Tadarida: A Toolbox for Animal Detection on Acoustic Recordings

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Yves Bas

2017-02-01

Full Text Available Passive Acoustic Monitoring (PAM recently extended to a very wide range of animals, but no available open software has been sufficiently generic to automatically treat several taxonomic groups. Here we present Tadarida, a software toolbox allowing for the detection and labelling of recorded sound events, and to classify any new acoustic data into known classes. It is made up of three modules handling Detection, Labelling and Classification and running on either Linux or Windows. This development resulted in the first open software (1 allowing generic sound event detection (multi-taxa, (2 providing graphical sound labelling at a single-instance level and (3 covering the whole process from sound detection to classification. This generic and modular design opens numerous reuse opportunities among (bioacoustics researchers, especially for those managing and/or developing PAM schemes. The whole toolbox is openly developed in C++ (Detection and Labelling and R (Classification and stored at https://github.com/YvesBas.

MASSIVE SATELLITES OF CLOSE-IN GAS GIANT EXOPLANETS

International Nuclear Information System (INIS)

Cassidy, Timothy A.; Johnson, Robert E.; Mendez, Rolando; Arras, Phil; Skrutskie, Michael F.

2009-01-01

We study the orbits, tidal heating and mass loss from satellites around close-in gas giant exoplanets. The focus is on large satellites which are potentially observable by their transit signature. We argue that even Earth-size satellites around hot Jupiters can be immune to destruction by orbital decay; detection of such a massive satellite would strongly constrain theories of tidal dissipation in gas giants, in a manner complementary to orbital circularization. The star's gravity induces significant periodic eccentricity in the satellite's orbit. The resulting tidal heating rates, per unit mass, are far in excess of Io's and dominate radioactive heating out to planet orbital periods of months for reasonable satellite tidal Q. Inside planet orbital periods of about a week, tidal heating can completely melt the satellite. Lastly, we compute an upper limit to the satellite mass loss rate due to thermal evaporation from the surface, valid if the satellite's atmosphere is thin and vapor pressure is negligible. Using this upper limit, we find that although rocky satellites around hot Jupiters with orbital periods less than a few days can be significantly evaporated in their lifetimes, detectable satellites suffer negligible mass loss at longer orbital periods.

Comparison of four machine learning methods for object-oriented change detection in high-resolution satellite imagery

Science.gov (United States)

Bai, Ting; Sun, Kaimin; Deng, Shiquan; Chen, Yan

2018-03-01

High resolution image change detection is one of the key technologies of remote sensing application, which is of great significance for resource survey, environmental monitoring, fine agriculture, military mapping and battlefield environment detection. In this paper, for high-resolution satellite imagery, Random Forest (RF), Support Vector Machine (SVM), Deep belief network (DBN), and Adaboost models were established to verify the possibility of different machine learning applications in change detection. In order to compare detection accuracy of four machine learning Method, we applied these four machine learning methods for two high-resolution images. The results shows that SVM has higher overall accuracy at small samples compared to RF, Adaboost, and DBN for binary and from-to change detection. With the increase in the number of samples, RF has higher overall accuracy compared to Adaboost, SVM and DBN.

5-bp Classical Satellite DNA Loci from Chromosome-1 Instability in Cervical Neoplasia Detected by DNA Breakage Detection/Fluorescence in Situ Hybridization (DBD-FISH

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Jaime Gosálvez

2013-02-01

Full Text Available We aimed to evaluate the association between the progressive stages of cervical neoplasia and DNA damage in 5-bp classical satellite DNA sequences from chromosome-1 in cervical epithelium and in peripheral blood lymphocytes using DNA breakage detection/fluorescence in situ hybridization (DBD-FISH. A hospital-based unmatched case-control study was conducted in 2011 with a sample of 30 women grouped according to disease stage and selected according to histological diagnosis; 10 with low-grade squamous intraepithelial lesions (LG-SIL, 10 with high-grade SIL (HG-SIL, and 10 with no cervical lesions, from the Unidad Medica de Alta Especialidad of The Mexican Social Security Institute, IMSS, Mexico. Specific chromosome damage levels in 5-bp classical satellite DNA sequences from chromosome-1 were evaluated in cervical epithelium and peripheral blood lymphocytes using the DBD-FISH technique. Whole-genome DNA hybridization was used as a reference for the level of damage. Results of Kruskal-Wallis test showed a significant increase according to neoplastic development in both tissues. The instability of 5-bp classical satellite DNA sequences from chromosome-1 was evidenced using chromosome-orientation FISH. In conclusion, we suggest that the progression to malignant transformation involves an increase in the instability of 5-bp classical satellite DNA sequences from chromosome-1.

5-bp Classical Satellite DNA Loci from Chromosome-1 Instability in Cervical Neoplasia Detected by DNA Breakage Detection/Fluorescence in Situ Hybridization (DBD-FISH).

Science.gov (United States)

Cortés-Gutiérrez, Elva I; Ortíz-Hernández, Brenda L; Dávila-Rodríguez, Martha I; Cerda-Flores, Ricardo M; Fernández, José Luis; López-Fernández, Carmen; Gosálvez, Jaime

2013-02-19

We aimed to evaluate the association between the progressive stages of cervical neoplasia and DNA damage in 5-bp classical satellite DNA sequences from chromosome-1 in cervical epithelium and in peripheral blood lymphocytes using DNA breakage detection/fluorescence in situ hybridization (DBD-FISH). A hospital-based unmatched case-control study was conducted in 2011 with a sample of 30 women grouped according to disease stage and selected according to histological diagnosis; 10 with low-grade squamous intraepithelial lesions (LG-SIL), 10 with high-grade SIL (HG-SIL), and 10 with no cervical lesions, from the Unidad Medica de Alta Especialidad of The Mexican Social Security Institute, IMSS, Mexico. Specific chromosome damage levels in 5-bp classical satellite DNA sequences from chromosome-1 were evaluated in cervical epithelium and peripheral blood lymphocytes using the DBD-FISH technique. Whole-genome DNA hybridization was used as a reference for the level of damage. Results of Kruskal-Wallis test showed a significant increase according to neoplastic development in both tissues. The instability of 5-bp classical satellite DNA sequences from chromosome-1 was evidenced using chromosome-orientation FISH. In conclusion, we suggest that the progression to malignant transformation involves an increase in the instability of 5-bp classical satellite DNA sequences from chromosome-1.

Modified automatic R-peak detection algorithm for patients with epilepsy using a portable electrocardiogram recorder.

Science.gov (United States)

Jeppesen, J; Beniczky, S; Fuglsang Frederiksen, A; Sidenius, P; Johansen, P

2017-07-01

Earlier studies have shown that short term heart rate variability (HRV) analysis of ECG seems promising for detection of epileptic seizures. A precise and accurate automatic R-peak detection algorithm is a necessity in a real-time, continuous measurement of HRV, in a portable ECG device. We used the portable CE marked ePatch® heart monitor to record the ECG of 14 patients, who were enrolled in the videoEEG long term monitoring unit for clinical workup of epilepsy. Recordings of the first 7 patients were used as training set of data for the R-peak detection algorithm and the recordings of the last 7 patients (467.6 recording hours) were used to test the performance of the algorithm. We aimed to modify an existing QRS-detection algorithm to a more precise R-peak detection algorithm to avoid the possible jitter Qand S-peaks can create in the tachogram, which causes error in short-term HRVanalysis. The proposed R-peak detection algorithm showed a high sensitivity (Se = 99.979%) and positive predictive value (P+ = 99.976%), which was comparable with a previously published QRS-detection algorithm for the ePatch® ECG device, when testing the same dataset. The novel R-peak detection algorithm designed to avoid jitter has very high sensitivity and specificity and thus is a suitable tool for a robust, fast, real-time HRV-analysis in patients with epilepsy, creating the possibility for real-time seizure detection for these patients.

Considerations and methods for the changes detection using satellite images in the Municipality of Paipa

International Nuclear Information System (INIS)

Riano M, Orlando

2002-01-01

In this article the considerations and methods are presented for the changes detection in the earth covering, using two images Landsat TM of different dates for an area of the municipality of Paipa, Boyaca. The changes detection has become an important application of the multi-spectral data and multi-temporal of the satellites programs for studies of natural resources Landsat, TM and Spot, in such a way that is possible to determine the types and extension of the changes that are given in the environment. To carry out this process some digital techniques they have been used for changes detection, such as: images superposition, differences between images and analysis of main components. These techniques allowed to observe and to analyze changes in the use and covering of the earth in this municipality

Detection of Convective Initiation Using Meteorological Imager Onboard Communication, Ocean, and Meteorological Satellite Based on Machine Learning Approaches

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Hyangsun Han

2015-07-01

Full Text Available As convective clouds in Northeast Asia are accompanied by various hazards related with heavy rainfall and thunderstorms, it is very important to detect convective initiation (CI in the region in order to mitigate damage by such hazards. In this study, a novel approach for CI detection using images from Meteorological Imager (MI, a payload of the Communication, Ocean, and Meteorological Satellite (COMS, was developed by improving the criteria of the interest fields of Rapidly Developing Cumulus Areas (RDCA derivation algorithm, an official CI detection algorithm for Multi-functional Transport SATellite-2 (MTSAT-2, based on three machine learning approaches—decision trees (DT, random forest (RF, and support vector machines (SVM. CI was defined as clouds within a 16 × 16 km window with the first detection of lightning occurrence at the center. A total of nine interest fields derived from visible, water vapor, and two thermal infrared images of MI obtained 15–75 min before the lightning occurrence were used as input variables for CI detection. RF produced slightly higher performance (probability of detection (POD of 75.5% and false alarm rate (FAR of 46.2% than DT (POD of 70.7% and FAR of 46.6% for detection of CI caused by migrating frontal cyclones and unstable atmosphere. SVM resulted in relatively poor performance with very high FAR ~83.3%. The averaged lead times of CI detection based on the DT and RF models were 36.8 and 37.7 min, respectively. This implies that CI over Northeast Asia can be forecasted ~30–45 min in advance using COMS MI data.

Validation of Hotspots Detected by Satellites in Sentinel Asia

Science.gov (United States)

Kaku, K.; Kushida, K.; Fukuda, M.

2008-12-01

The Sentinel Asia (SA) initiative is a collaboration between space agencies and disaster management agencies, applying remote sensing and Web-GIS technologies to assist disaster management in the Asia- Pacific region. It aims to: "EImprove safety in society by ICT and space technology "EImprove speed and accuracy of disaster preparedness and early warning "EMinimize the number of victims and social/economic losses. SA is a voluntary initiative led by the Asia-Pacific Regional Space Agency Forum (APRSAF) to share disaster information in near-real-time across the Asia-Pacific region. Wildfire is a major and recurring phenomenon that has a serious impact on property and human health, affecting many countries in the Asia region. Compared to other disasters in the area, it does not necessarily cause many immediate fatalities. However, it causes serious impact on property and human health due to smoke. Furthermore, its effects are of great relevance both at a regional and global level, and accordingly bear substantial influence on global warming. Responding to requirements from Asian countries, under Sentinel Asia a dedicated Wildfire Working Group (WG) has been established to apply remote sensing technology to the management of wildfire. Having accurate information on the location and intensity of the fires, and subsequent control of wildfire, are therefore very important and urgent tasks across the region. SA primarily addresses the issue of near-real-time information distribution on wildfires in the region. Concerning hotspot data obtained by satellites, it is essential to validate and improve its accuracy. In the framework of Sentinel Asia Wildfire WG, various approaches to hotspot detection, including MOD14 algorithm for MODIS hotspots, were studied, and their validations were carried out, comparing them with active fires extracted from satellite imagery and ground truth data in Chiengmai, Thailand and in Kalimantan, Indonesia.

On Variability in Satellite Terrestrial Chlorophyll Fluorescence Measurements: Relationships with Phenology and Ecosystem-Atmosphere Carbon Exchange, Vegetation Structure, Clouds, and Sun-Satellite Geometry

Science.gov (United States)

Joiner, J.; Yoshida, Y.; Guanter, L.; Zhang, Y.; Vasilkov, A. P.; Schaefer, K. M.; Huemmrich, K. F.; Middleton, E.; Koehler, P.; Jung, M.; Tucker, C. J.; Lyapustin, A.; Wang, Y.; Frankenberg, C.; Berry, J. A.; Koster, R. D.; Reichle, R. H.; Lee, J. E.; Kawa, S. R.; Collatz, G. J.; Walker, G. K.; Van der Tol, C.

2014-12-01

Over the past several years, there have been several breakthroughs in our ability to detect the very small fluorescence emitted by chlorophyll in vegetation globally from space. There are now multiple instruments in space capable of measuring this signal at varying temporal and spatial resolutions. We will review the state-of-the-art with respect to these relatively new satellite measurements and ongoing studies that examine the relationships with photosynthesis. Now that we have a data record spanning more than seven years, we can examine variations due to seasonal carbon uptake, interannual variability, land-use changes, and water and temperature stress. In addition, we examine how clouds and satellite viewing geometry impact the signal. We compare and contrast these variations with those from popular vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), related to the potential photosynthesis as well as with measurements from flux tower gas exchange measurements and other model-based estimates of Global Primary Productivity (GPP). Vegetation fluorescence can be simulated in global vegetation models as well as with 1D canopy radiative transport models. We will describe how the satellite fluorescence data are being used to evaluate and potentially improve these models.

Automatic lameness detection based on consecutive 3D-video recordings

NARCIS (Netherlands)

Hertem, van T.; Viazzi, S.; Steensels, M.; Maltz, E.; Antler, A.; Alchanatis, V.; Schlageter-Tello, A.; Lokhorst, C.; Romanini, C.E.B.; Bahr, C.; Berckmans, D.; Halachmi, I.

2014-01-01

Manual locomotion scoring for lameness detection is a time-consuming and subjective procedure. Therefore, the objective of this study is to optimise the classification output of a computer vision based algorithm for automated lameness scoring. Cow gait recordings were made during four consecutive

Satellite Remote Sensing Detection of Coastal Pollution in Southern California: Stormwater Runoff and Wastewater Plumes

Science.gov (United States)

Trinh, R. C.; Holt, B.; Gierach, M.

2016-02-01

Coastal pollution poses a major health and environmental hazard, not only for beach goers and coastal communities but for marine organisms as well. Stormwater runoff is the largest source of environmental pollution in coastal waters of the Southern California Bight (SCB) and is of great concern in increasingly urbanized areas. Buoyant wastewater plumes also pose a marine environmental risk. In this study we provide a comprehensive overview of satellite remote sensing capabilities in detecting buoyant coastal pollutants in the form of stormwater runoff and wastewater effluent. The SCB is the final destination of four major urban rivers that act as channels for runoff and pollution during and after rainstorms. We analyzed and compared sea surface roughness data from various Synthetic Aperture Radar (SAR) instruments to ocean color data from the Moderate Imaging System (MODIS) sensor on board the Aqua satellite and correlated the results with existing environmental data in order to create a climatology of naturally occurring stormwater plumes in coastal waters after rain events, from 1992 to 2014 from four major rivers in the area. Heat maps of the primary extent of stormwater plumes were constructed to specify areas that may be subject to the greatest risk of coastal contamination. In conjunction with our efforts to monitor coastal pollution and validate the abilities of satellite remote sensing, a recent Fall 2015 wastewater diversion from the City of Los Angeles Hyperion Treatment Plant (HTP) provided the opportunity to apply these remote sensing methodologies of plume detection to wastewater. During maintenance of their 5-mile long outfall pipe, wastewater is diverted to a shorter outfall pipe that terminates 1-mile offshore and in shallower waters. Sea surface temperature (SST), chlorophyll-a (chl-a) fluorescence, remote sensing reflectance and particulate backscatter signatures were analyzed from MODIS. Terra-ASTER and Landsat-8 thermal infrared data were also

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

Directory of Open Access Journals (Sweden)

Oscar Rojas

2013-04-01

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

Analysis of satellite-derived solar irradiance over the Netherlands

Science.gov (United States)

Dirksen, Marieke; Fokke Meirink, Jan; Sluiter, Raymond

2017-04-01

Measurements from geostationary satellites allow the retrieval of surface solar irradiance homogeneously over large areas, thereby providing essential information for the solar energy sector. In this paper, the SICCS solar irradiance data record derived from 12 years of Meteosat Second Generation satellite measurements is analysed with a focus on the Netherlands, where the spatial resolution is about 6 by 3 km2. Extensive validation of the SICCS data with pyranometer observations is performed, indicating a bias of approximately 3 W/m2 and RMSE of 11 W/m2 for daily data. Long term averages and seasonal variations of solar irradiance show regional patterns related to the surface type (e.g., coastal waters, forests, cities). The inter-annual variability over the time frame of the data record is quantified. Methods to merge satellite and surface observations into an optimized data record are explored.

An Enhanced Satellite-Based Algorithm for Detecting and Tracking Dust Outbreaks by Means of SEVIRI Data

Directory of Open Access Journals (Sweden)

Francesco Marchese

2017-05-01

Full Text Available Dust outbreaks are meteorological phenomena of great interest for scientists and authorities (because of their impact on the climate, environment, and human activities, which may be detected, monitored, and characterized from space using different methods and procedures. Among the recent dust detection algorithms, the RSTDUST multi-temporal technique has provided good results in different geographic areas (e.g., Mediterranean basin; Arabian Peninsula, exhibiting a better performance than traditional split window methods, in spite of some limitations. In this study, we present an optimized configuration of this technique, which better exploits data provided by Spinning Enhanced Visible and Infrared Imager (SEVIRI aboard Meteosat Second Generation (MSG satellites to address those issues (e.g., sensitivity reduction over arid and semi-arid regions; dependence on some meteorological clouds. Three massive dust events affecting Europe and the Mediterranean basin in May 2008/2010 are analysed in this work, using information provided by some independent and well-established aerosol products to assess the achieved results. The study shows that the proposed algorithm, christened eRSTDUST (i.e., enhanced RSTDUST, which provides qualitative information about dust outbreaks, is capable of increasing the trade-off between reliability and sensitivity. The results encourage further experimentations of this method in other periods of the year, also exploiting data provided by different satellite sensors, for better evaluating the advantages arising from the use of this dust detection technique in operational scenarios.

Optomagnetic Detection of MicroRNA Based on Duplex-Specific Nuclease-Assisted Target Recycling and Multilayer Core-Satellite Magnetic Superstructures

DEFF Research Database (Denmark)

Tian, Bo; Ma, Jing; Qiu, Zhen

2017-01-01

-efficiency, and potential for bioresponsive multiplexing. Herein, we demonstrate a sensitive and rapid miRNA detection method based on optomagnetic read-out, duplex-specific nuclease (DSN)-assisted target recycling, and the use of multilayer core-satellite magnetic superstructures. Triggered by the presence of target mi...

Advanced Oil Spill Detection Algorithms For Satellite Based Maritime Environment Monitoring

Science.gov (United States)

Radius, Andrea; Azevedo, Rui; Sapage, Tania; Carmo, Paulo

2013-12-01

During the last years, the increasing pollution occurrence and the alarming deterioration of the environmental health conditions of the sea, lead to the need of global monitoring capabilities, namely for marine environment management in terms of oil spill detection and indication of the suspected polluter. The sensitivity of Synthetic Aperture Radar (SAR) to the different phenomena on the sea, especially for oil spill and vessel detection, makes it a key instrument for global pollution monitoring. The SAR performances in maritime pollution monitoring are being operationally explored by a set of service providers on behalf of the European Maritime Safety Agency (EMSA), which has launched in 2007 the CleanSeaNet (CSN) project - a pan-European satellite based oil monitoring service. EDISOFT, which is from the beginning a service provider for CSN, is continuously investing in R&D activities that will ultimately lead to better algorithms and better performance on oil spill detection from SAR imagery. This strategy is being pursued through EDISOFT participation in the FP7 EC Sea-U project and in the Automatic Oil Spill Detection (AOSD) ESA project. The Sea-U project has the aim to improve the current state of oil spill detection algorithms, through the informative content maximization obtained with data fusion, the exploitation of different type of data/ sensors and the development of advanced image processing, segmentation and classification techniques. The AOSD project is closely related to the operational segment, because it is focused on the automation of the oil spill detection processing chain, integrating auxiliary data, like wind information, together with image and geometry analysis techniques. The synergy between these different objectives (R&D versus operational) allowed EDISOFT to develop oil spill detection software, that combines the operational automatic aspect, obtained through dedicated integration of the processing chain in the existing open source NEST

Change detection and change monitoring of natural and man-made features in multispectral and hyperspectral satellite imagery

Science.gov (United States)

Moody, Daniela Irina

2018-04-17

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Satellite line mapping in Eu3+–Ce3+ and Pr3+–Ce3+ codoped Y2SiO5

International Nuclear Information System (INIS)

Serrano, D.; Karlsson, J.; Zheng, L.; Dong, Y.; Ferrier, A.; Goldner, P.; Walther, A.; Rippe, L.; Kröll, S.

2016-01-01

In this work we perform a high-resolution spectroscopic investigation of Eu 3+ –Ce 3+ and Pr 3+ –Ce 3+ codoped Y 2 SiO 5 crystals. Satellite line spectra were recorded at low temperatures around the Eu 3+ : 7 F 0 → 5 D 0 and the Pr 3+ : 3 H 4 → 1 D 2 transitions. It is observed that the incorporation of Ce 3+ as a codopant notably changes the Eu 3+ and Pr 3+ satellite line patterns. Satellite lines measured in singly doped Eu 3+ :Y 2 SiO 5 were found at the same spectral positions in Eu 3+ –Ce 3+ codoped crystals. These coincident lines were concluded to be due to pairs of Eu 3+ ions. Extra satellite lines appeared in the codoped crystals, which were assigned to Ce 3+ related structures such as Ce 3+ –Eu 3+ pairs. The analysis of the Pr 3+ satellite line spectra presents further challenges. Satellite lines associated to Pr 3+ pairs show weaker intensity, presumably due to the efficient quenching of the Pr 3+1 D 2 emission through cross-relaxation paths ( 1 D 2 → 1 G 4 ; 3 H 4 → 3 F 4 ). The investigation of the Eu 3+ and Pr 3+ satellite line patterns in Y 2 SiO 5 is particularly interesting for their exploitation in rare-earth based quantum computation schemes. - Highlights: • We recorded Eu and Pr satellite lines in Y 2 SiO 5 with and without Ce as a codopant. • The presence of Ce leads to the appearance of extra satellite lines in the spectra. • The satellite lines are associated to minor crystal sites such as ion pairs. • Less than 100 ion pairs were detected per satellite line. • The exploitation of the satellite line structure is proposed for quantum computing.

EEG recordings as a source for the detection of IRBD

DEFF Research Database (Denmark)

Bisgaard, Sissel; Duun-Christensen, Bolette; Kempfner, Lykke

2015-01-01

The purpose of this pilot study was to develop a supportive algorithm for the detection of idiopathic Rapid Eye-Movement (REM) sleep Behaviour Disorder (iRBD) from EEG recordings. iRBD is defined as REM sleep without atonia with no current sign of neurodegenerative disease, and is one...... of the earliest known biomarkers of Parkinson's Disease (PD). It is currently diagnosed by polysomnography (PSG), primarily based on EMG recordings during REM sleep. The algorithm was developed using data collected from 42 control subjects and 34 iRBD subjects. A feature was developed to represent high amplitude...

Combining airborne and satellite remote sensing programs to repress illegal oil discharges in restricted sea areas

International Nuclear Information System (INIS)

Price, M.

2005-01-01

An airborne surveillance program has been conducted over the Belgian part of the North Sea since 1991. The role of the program is to detect infringements on the Marpol Convention via remote sensing, and to take legal action against polluters through the use of recorded observations. Although Belgium has a restricted sea area of about 3,500 km with no fixed offshore oil installations, a pollution risk is constantly present due to 2 dense traffic separation schemes close to the shoreline. The Belgian marine areas and adjacent waters are regularly scanned with a Side Looking Airborne Radar (SLAR) on board a remote sensing aircraft. This paper describes an evaluation trial that the Belgian Management Unit of the North Sea Mathematical Models (MUMM) joined in 2004, together with various agencies from the United Kingdom, Germany and the Netherlands. The trial consists of a cost-sharing satellite service for oil detection with ENVISAT ASAR data. The trial was co-funded by the European Space Agency (ESA) and run by Kongsberg Satellite Services. MUMM's objective was to evaluate the effectiveness and operational character of satellite services for detecting oil spills at sea. The results of the 3 month trial have indicated that aerial remote sensing for the detection of illegal oil discharges at sea increases the chances of catching polluters more efficiently, with improved chances of evidence collecting. It was concluded that when various services are integrated and strict operational conditions are met, satellite services may prove to be valuable in restricted, very densely navigated national waters that are easily reached by airborne means. 12 refs., 8 tabs., 3 figs

Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

Science.gov (United States)

Shiffman, Smadar

2004-01-01

Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

Global Trends in Chlorophyll Concentration Observed with the Satellite Ocean Colour Data Record

Science.gov (United States)

Melin, F.; Vantrepotte, V.; Chuprin, A.; Grant, M.; Jackson, T.; Sathyendranath, S.

2016-08-01

To detect climate change signals in the data records derived from remote sensing of ocean colour, combining data from multiple missions is required, which implies that the existence of inter-mission differences be adequately addressed prior to undertaking trend studies. Trend distributions associated with merged products are compared with those obtained from single-mission data sets in order to evaluate their suitability for climate studies. Merged products originally developed for operational applications such as near-real time distribution (GlobColour) do not appear to be proper climate data records, showing large parts of the ocean with trends significantly different from trends obtained with SeaWiFS, MODIS or MERIS. On the other hand, results obtained from the Climate Change Initiative (CCI) data are encouraging, showing a good consistency with single-mission products.

First Satellite-detected Perturbations of Outgoing Longwave Radiation Associated with Blowing Snow Events over Antarctica

Science.gov (United States)

Yang, Yuekui; Palm, Stephen P.; Marshak, Alexander; Wu, Dong L.; Yu, Hongbin; Fu, Qiang

2014-01-01

We present the first satellite-detected perturbations of the outgoing longwave radiation (OLR) associated with blowing snow events over the Antarctic ice sheet using data from Cloud-Aerosol Lidar with Orthogonal Polarization and Clouds and the Earth's Radiant Energy System. Significant cloud-free OLR differences are observed between the clear and blowing snow sky, with the sign andmagnitude depending on season and time of the day. During nighttime, OLRs are usually larger when blowing snow is present; the average difference in OLRs between without and with blowing snow over the East Antarctic Ice Sheet is about 5.2 W/m2 for the winter months of 2009. During daytime, in contrast, the OLR perturbation is usually smaller or even has the opposite sign. The observed seasonal variations and day-night differences in the OLR perturbation are consistent with theoretical calculations of the influence of blowing snow on OLR. Detailed atmospheric profiles are needed to quantify the radiative effect of blowing snow from the satellite observations.

Satellite-based detection of volcanic sulphur dioxide from recent eruptions in Central and South America

Directory of Open Access Journals (Sweden)

D. Loyola

2008-01-01

Full Text Available Volcanic eruptions can emit large amounts of rock fragments and fine particles (ash into the atmosphere, as well as several gases, including sulphur dioxide (SO₂. These ejecta and emissions are a major natural hazard, not only to the local population, but also to the infrastructure in the vicinity of volcanoes and to aviation. Here, we describe a methodology to retrieve quantitative information about volcanic SO₂ plumes from satellite-borne measurements in the UV/Visible spectral range. The combination of a satellite-based SO₂ detection scheme and a state-of-the-art 3D trajectory model enables us to confirm the volcanic origin of trace gas signals and to estimate the plume height and the effective emission height. This is demonstrated by case-studies for four selected volcanic eruptions in South and Central America, using the GOME, SCIAMACHY and GOME-2 instruments.

Analytic studies on satellite detection of severe, two-cell tornadoes

Science.gov (United States)

Carrier, G. F.; Dergarabedian, P.; Fendell, F. E.

1979-01-01

From funnel-cloud-length interpretation, the severe tornado is characterized by peak swirl speed relative to the axis of rotation of about 90 m/s. Thermohydrodynamic achievement of the pressure deficit from ambient necessary to sustain such swirls requires that a dry, compressionally heated, non-rotating downdraft of initially tropopause-level air lie within an annulus of rapidly swirling, originally low-level air ascending on a near-moist-adiabatic locus of thermodynamic states. The two-cell structure furnishes an observable parameter possibly accessible to a passively instrumented, geosynchronous meteorological satellite with mesoscale resolution, for early detection of a severe tornado. Accordingly, the low-level turnaround region, in which the surface inflow layer separates to become a free ascending layer and for which inviscid modeling suffices, is examined quantitatively. Preliminary results indicate that swirl overshoot, i.e., swirl speeds in the turnaround region in excess of the maximum achieved in the potential vortex, is modest.

Landsat—Earth observation satellites

Science.gov (United States)

,

2015-11-25

Since 1972, Landsat satellites have continuously acquired space-based images of the Earth’s land surface, providing data that serve as valuable resources for land use/land change research. The data are useful to a number of applications including forestry, agriculture, geology, regional planning, and education. Landsat is a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). NASA develops remote sensing instruments and the spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and data distribution. The result of this program is an unprecedented continuing record of natural and human-induced changes on the global landscape.

Detection, emission estimation and risk prediction of forest fires in China using satellite sensors and simulation models in the past three decades--an overview.

Science.gov (United States)

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K

2011-08-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.

DS-CDMA satellite diversity reception for personal satellite communication: Downlink performance analysis

Science.gov (United States)

DeGaudenzi, Riccardo; Giannetti, Filippo

1995-01-01

The downlink of a satellite-mobile personal communication system employing power-controlled Direct Sequence Code Division Multiple Access (DS-CDMA) and exploiting satellite-diversity is analyzed and its performance compared with a more traditional communication system utilizing single satellite reception. The analytical model developed has been thoroughly validated by means of extensive Monte Carlo computer simulations. It is shown how the capacity gain provided by diversity reception shrinks considerably in the presence of increasing traffic or in the case of light shadowing conditions. Moreover, the quantitative results tend to indicate that to combat system capacity reduction due to intra-system interference, no more than two satellites shall be active over the same region. To achieve higher system capacity, differently from terrestrial cellular systems, Multi-User Detection (MUD) techniques are likely to be required in the mobile user terminal, thus considerably increasing its complexity.

Automated detection of follow-up appointments using text mining of discharge records.

Science.gov (United States)

Ruud, Kari L; Johnson, Matthew G; Liesinger, Juliette T; Grafft, Carrie A; Naessens, James M

2010-06-01

To determine whether text mining can accurately detect specific follow-up appointment criteria in free-text hospital discharge records. Cross-sectional study. Mayo Clinic Rochester hospitals. Inpatients discharged from general medicine services in 2006 (n = 6481). Textual hospital dismissal summaries were manually reviewed to determine whether the records contained specific follow-up appointment arrangement elements: date, time and either physician or location for an appointment. The data set was evaluated for the same criteria using SAS Text Miner software. The two assessments were compared to determine the accuracy of text mining for detecting records containing follow-up appointment arrangements. Agreement of text-mined appointment findings with gold standard (manual abstraction) including sensitivity, specificity, positive predictive and negative predictive values (PPV and NPV). About 55.2% (3576) of discharge records contained all criteria for follow-up appointment arrangements according to the manual review, 3.2% (113) of which were missed through text mining. Text mining incorrectly identified 3.7% (107) follow-up appointments that were not considered valid through manual review. Therefore, the text mining analysis concurred with the manual review in 96.6% of the appointment findings. Overall sensitivity and specificity were 96.8 and 96.3%, respectively; and PPV and NPV were 97.0 and 96.1%, respectively. of individual appointment criteria resulted in accuracy rates of 93.5% for date, 97.4% for time, 97.5% for physician and 82.9% for location. Text mining of unstructured hospital dismissal summaries can accurately detect documentation of follow-up appointment arrangement elements, thus saving considerable resources for performance assessment and quality-related research.

Detection and Prediction of Hail Storms in Satellite Imagery using Deep Learning

Science.gov (United States)

Pullman, M.; Gurung, I.; Ramachandran, R.; Maskey, M.

2017-12-01

Natural hazards, such as damaging hail storms, dramatically disrupt both industry and agriculture, having significant socio-economic impacts in the United States. In 2016, hail was responsible for 3.5 billion and 23 million dollars in damage to property and crops, respectively, making it the second costliest 2016 weather phenomenon in the United States. The destructive nature and high cost of hail storms has driven research into the development of more accurate hail-prediction algorithms in an effort to mitigate societal impacts. Recently, weather forecasting efforts have turned to deep learning neural networks because neural networks can more effectively model complex, nonlinear, dynamical phenomenon that exist in large datasets through multiple stages of transformation and representation. In an effort to improve hail-prediction techniques, we propose a deep learning technique that leverages satellite imagery to detect and predict the occurrence of hail storms. The technique is applied to satellite imagery from 2006 to 2016 for the contiguous United States and incorporates hail reports obtained from the National Center for Environmental Information Storm Events Database for training and validation purposes. In this presentation, we describe a novel approach to predicting hail via a neural network model that creates a large labeled dataset of hail storms, the accuracy and results of the model, and its applications for improving hail forecasting.

PATMOS-x Cloud Climate Record Trend Sensitivity to Reanalysis Products

Directory of Open Access Journals (Sweden)

Michael J. Foster

2016-05-01

Full Text Available Continuous satellite-derived cloud records now extend over three decades, and are increasingly used for climate applications. Certain applications, such as trend detection, require a clear understanding of uncertainty as it relates to establishing statistical significance. The use of reanalysis products as sources of ancillary data could be construed as one such source of uncertainty, as there has been discussion regarding the suitability of reanalysis products for trend detection. Here we use three reanalysis products: Climate Forecast System Reanalysis (CFSR, Modern Era Retrospective Analysis for Research and Applications (MERRA and European Center for Medium range Weather Forecasting (ECMWF ERA-Interim (ERA-I as sources of ancillary data for the Pathfinder Atmospheres Extended/Advanced Very High Resolution Radiometer (PATMOS-x/AVHRR Satellite Cloud Climate Data Record (CDR, and perform inter-comparisons to determine how sensitive the climatology is to choice of ancillary data source. We find differences among reanalysis fields required for PATMOS-x processing, which translate to small but not insignificant differences in retrievals of cloud fraction, cloud top height and cloud optical depth. The retrieval variability due to choice of reanalysis product is on the order of one third the size of the retrieval uncertainty, making it a potentially significant factor in trend detection. Cloud fraction trends were impacted the most by choice of reanalysis while cloud optical depth trends were impacted the least. Metrics used to determine the skill of the reanalysis products for use as ancillary data found no clear best choice for use in PATMOS-x. We conclude use of reanalysis products as ancillary data in the PATMOS-x/AVHRR Cloud CDR do not preclude its use for trend detection, but for that application uncertainty in reanalysis fields should be better represented in the PATMOS-x retrieval uncertainty.

A Dynamic Enhancement With Background Reduction Algorithm: Overview and Application to Satellite-Based Dust Storm Detection

Science.gov (United States)

Miller, Steven D.; Bankert, Richard L.; Solbrig, Jeremy E.; Forsythe, John M.; Noh, Yoo-Jeong; Grasso, Lewis D.

2017-12-01

This paper describes a Dynamic Enhancement Background Reduction Algorithm (DEBRA) applicable to multispectral satellite imaging radiometers. DEBRA uses ancillary information about the clear-sky background to reduce false detections of atmospheric parameters in complex scenes. Applied here to the detection of lofted dust, DEBRA enlists a surface emissivity database coupled with a climatological database of surface temperature to approximate the clear-sky equivalent signal for selected infrared-based multispectral dust detection tests. This background allows for suppression of false alarms caused by land surface features while retaining some ability to detect dust above those problematic surfaces. The algorithm is applicable to both day and nighttime observations and enables weighted combinations of dust detection tests. The results are provided quantitatively, as a detection confidence factor [0, 1], but are also readily visualized as enhanced imagery. Utilizing the DEBRA confidence factor as a scaling factor in false color red/green/blue imagery enables depiction of the targeted parameter in the context of the local meteorology and topography. In this way, the method holds utility to both automated clients and human analysts alike. Examples of DEBRA performance from notable dust storms and comparisons against other detection methods and independent observations are presented.

Conflict Detection Performance Analysis for Function Allocation Using Time-Shifted Recorded Traffic Data

Science.gov (United States)

Guerreiro, Nelson M.; Butler, Ricky W.; Maddalon, Jeffrey M.; Hagen, George E.; Lewis, Timothy A.

2015-01-01

The performance of the conflict detection function in a separation assurance system is dependent on the content and quality of the data available to perform that function. Specifically, data quality and data content available to the conflict detection function have a direct impact on the accuracy of the prediction of an aircraft's future state or trajectory, which, in turn, impacts the ability to successfully anticipate potential losses of separation (detect future conflicts). Consequently, other separation assurance functions that rely on the conflict detection function - namely, conflict resolution - are prone to negative performance impacts. The many possible allocations and implementations of the conflict detection function between centralized and distributed systems drive the need to understand the key relationships that impact conflict detection performance, with respect to differences in data available. This paper presents the preliminary results of an analysis technique developed to investigate the impacts of data quality and data content on conflict detection performance. Flight track data recorded from a day of the National Airspace System is time-shifted to create conflicts not present in the un-shifted data. A methodology is used to smooth and filter the recorded data to eliminate sensor fusion noise, data drop-outs and other anomalies in the data. The metrics used to characterize conflict detection performance are presented and a set of preliminary results is discussed.

International Satellite Cloud Climatology Project (ISCCP) Climate Data Record, H-Series

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The International Satellite Cloud Climatology Project (ISCCP) focuses on the distribution and variation of cloud radiative properties to improve the understanding of...

Remote sensing for greenhouse detection from stereo pairs of WorldView-2 satellite

Directory of Open Access Journals (Sweden)

M.A. Aguilar

2014-05-01

Full Text Available The successful launch of the first very high resolution (VHR satellites capable of capturing panchromatic imagery of the land surface with ground sample distance even lower than 1 m (e.g. IKONOS in 1999 or QuickBird in 2001 marked the beginning of a wholly new age in remote sensing. On January 4, 2010, images of WorldView-2 were placed on the market. Possibly it is the most sophisticated commercial VHR satellite currently orbiting the Earth and the exploitation of its data poses a challenge to researchers worldwide. Moreover, the practice of under plastic agriculture had a great development in the Mediterranean area during the past 60 years, especially in Almeria, acting as a key economic driver in the area. The goal of this work is the automatic greenhouse mapping by using Object Based Image Analysis (OBIA. The required input data will be a pan-sharpened orthoimage and a normalized digital surface model (nDSM for objects, both products generated from a WorldView-2 stereo pair. The attained results show that the very high resolution 8-band multispectral and the nDSM data improve the greenhouses automatic detection. In this way, overall accuracies higher than 90% can be achieved.

Detection of induced seismicity effects on ground surface using data from Sentinel 1A/1B satellites

Science.gov (United States)

Milczarek, W.

2017-12-01

Induced seismicity is the result of human activity and manifests itself in the form of shock and vibration of the ground surface. One of the most common factors causing the occurrence of induced shocks is underground mining activity. Sufficiently strong high-energy shocks may cause displacements of the ground surface. This type of shocks can have a significant impact on buildings and infrastructure. Assessment of the size and influence of induced seismicity on the ground surface is one of the major problems associated with mining activity. In Poland (Central Eastern Europe) induced seismicity occurs in the area of hard coal mining in the Upper Silesian Coal Basin and in the area of the Legnica - Głogów Copper Basin.The study presents an assessment of the use of satellite radar data (SAR) for the detection influence of induced seismicity in mining regions. Selected induced shocks from the period 2015- 2017 which occurred in the Upper Silesian Coal Basin and the Legnica - Głogów Copper Basin areas have been analyzed. In the calculations SAR data from the Sentinel 1A and Sentinel 1B satellites have been used. The results indicate the possibility of quickly and accurate detection of ground surface displacements after an induced shock. The results of SAR data processing were compared with the results from geodetic measurements. It has been shown that SAR data can be used to detect ground surface displacements on the relative small regions.

CLOUD DETECTION OF OPTICAL SATELLITE IMAGES USING SUPPORT VECTOR MACHINE

Directory of Open Access Journals (Sweden)

K.-Y. Lee

2016-06-01

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

Cloud Detection of Optical Satellite Images Using Support Vector Machine

Science.gov (United States)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

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

Protected transitional solution to transformational satellite communications

Science.gov (United States)

Brand, Jerry C.

2005-06-01

As the Warfighter progresses into the next generation battlefield, transformational communications become evident as an enabling technology. Satellite communications become even more vital as the battles range over greater non-contiguous spaces. While current satellite communications provide suitable beyond line-of-sight communications and the Transformational Communications Architecture (TCA) sets the stage for sound information exchange, a realizable transition must occur to ensure successful succession to this higher level. This paper addresses the need for a planned escalation to the next generation satellite communications architecture and offers near-term alternatives. Commercial satellite systems continue to enable the Warfighter to reach back to needed information resources, providing a large majority of available bandwidth. Four areas of concentration for transition include encrypted Telemetry, Tracking and Control (or Command) (TT&C), encrypted and covered data, satellite attack detection and protection, and operational mobility. Solution methodologies include directly embedding COMSEC devices in the satellites and terminals, and supplementing existing terminals with suitable equipment and software. Future satellites planned for near-term launches can be adapted to include commercial grade and higher-level secure equipment. Alternately, the expected use of programmable modems (Software Defined Radios (SDR)) enables incorporation of powerful cipher methods approaching military standards as well as waveforms suitable for on-the-move operation. Minimal equipment and software additions on the satellites can provide reasonable attack detection and protection methods in concert with the planned satellite usage. Network management suite modifications enable cohesive incorporation of these protection schemes. Such transitional ideas offer a smooth and planned transition as the TCA takes life.

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

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Cheng Liu

2011-07-01

Full Text Available Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction，have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR and near infrared (NIR channels of satellite sensors have been employed for detecting live fuel moisture content (FMC, and the Normalized Difference Water Index (NDWI was used for evaluating the forest vegetation condition and its moisture status.

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

Science.gov (United States)

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K.

2011-01-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status. PMID:21909297

SatelliteDL: a Toolkit for Analysis of Heterogeneous Satellite Datasets

Science.gov (United States)

Galloy, M. D.; Fillmore, D.

2014-12-01

Climate Data Records as they become available. To obtain SatelliteDL, please visit the project website at http://www.txcorp.com/SatelliteDL

Vessel and oil spill early detection using COSMO satellite imagery

Science.gov (United States)

Revollo, Natalia V.; Delrieux, Claudio A.

2017-10-01

Oil spillage is one of the most common sources of environmental damage in places where coastal wild life is found in natural reservoirs. This is especially the case in the Patagonian coast, with a littoral more than 5000 km long and a surface above a million and half square km. In addition, furtive fishery activities in Argentine waters are depleting the food supplies of several species, altering the ecological equilibrium. For this reason, early oil spills and vessel detection is an imperative surveillance task for environmental and governmental authorities. However, given the huge geographical extension, human assisted monitoring is unfeasible, and therefore real time remote sensing technologies are the only operative and economically feasible solution. In this work we describe the theoretical foundations and implementation details of a system specifically designed to take advantage of the SAR imagery delivered by two satellite constellations (the SAOCOM mission, developed by the Argentine Space Agency, and the COSMO mission, developed by the Italian Space Agency), to provide real-time detection of vessels and oil spills. The core of the system is based on pattern recognition over a statistical characterization of the texture patterns arising in the positive and negative conditions (i.e., vessel, oil, or plain sea surfaces). Training patterns were collected from a large number of previously reported contacts tagged by experts in the National Commission on Space Activities (CONAE). The resulting system performs well above the sensitivity and specificity of other avalilable systems.

Detecting long-term changes to vegetation in northern Canada using the Landsat satellite image archive

International Nuclear Information System (INIS)

Fraser, R H; Olthof, I; Carrière, M; Deschamps, A; Pouliot, D

2011-01-01

Analysis of coarse resolution (∼1 km) satellite imagery has provided evidence of vegetation changes in arctic regions since the mid-1980s that may be attributable to climate warming. Here we investigate finer-scale changes to northern vegetation over the same period using stacks of 30 m resolution Landsat TM and ETM + satellite images. Linear trends in the normalized difference vegetation index (NDVI) and tasseled cap indices are derived for four widely spaced national parks in northern Canada. The trends are related to predicted changes in fractional shrub and other vegetation covers using regression tree classifiers trained with plot measurements and high resolution imagery. We find a consistent pattern of greening (6.1–25.5% of areas increasing) and predicted increases in vascular vegetation in all four parks that is associated with positive temperature trends. Coarse resolution (3 km) NDVI trends were not detected in two of the parks that had less intense greening. A range of independent studies and observations corroborate many of the major changes observed.

Statistical methods for change-point detection in surface temperature records

Science.gov (United States)

Pintar, A. L.; Possolo, A.; Zhang, N. F.

2013-09-01

We describe several statistical methods to detect possible change-points in a time series of values of surface temperature measured at a meteorological station, and to assess the statistical significance of such changes, taking into account the natural variability of the measured values, and the autocorrelations between them. These methods serve to determine whether the record may suffer from biases unrelated to the climate signal, hence whether there may be a need for adjustments as considered by M. J. Menne and C. N. Williams (2009) "Homogenization of Temperature Series via Pairwise Comparisons", Journal of Climate 22 (7), 1700-1717. We also review methods to characterize patterns of seasonality (seasonal decomposition using monthly medians or robust local regression), and explain the role they play in the imputation of missing values, and in enabling robust decompositions of the measured values into a seasonal component, a possible climate signal, and a station-specific remainder. The methods for change-point detection that we describe include statistical process control, wavelet multi-resolution analysis, adaptive weights smoothing, and a Bayesian procedure, all of which are applicable to single station records.

On the Use of Global Flood Forecasts and Satellite-Derived Inundation Maps for Flood Monitoring in Data-Sparse Regions

Directory of Open Access Journals (Sweden)

Beatriz Revilla-Romero

2015-11-01

Full Text Available Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response decisions. Global-scale flood forecasting and satellite-based flood detection systems are currently operating, however their reliability for decision-making applications needs to be assessed. In this study, we performed comparative evaluations of several operational global flood forecasting and flood detection systems, using 10 major flood events recorded over 2012–2014. Specifically, we evaluated the spatial extent and temporal characteristics of flood detections from the Global Flood Detection System (GFDS and the Global Flood Awareness System (GloFAS. Furthermore, we compared the GFDS flood maps with those from NASA’s two Moderate Resolution Imaging Spectroradiometer (MODIS sensors. Results reveal that: (1 general agreement was found between the GFDS and MODIS flood detection systems, (2 large differences exist in the spatio-temporal characteristics of the GFDS detections and GloFAS forecasts, and (3 the quantitative validation of global flood disasters in data-sparse regions is highly challenging. Overall, satellite remote sensing provides useful near real-time flood information that can be useful for risk management. We highlight the known limitations of global flood detection and forecasting systems, and propose ways forward to improve the reliability of large-scale flood monitoring tools.

Automated tracking for advanced satellite laser ranging systems

Science.gov (United States)

McGarry, Jan F.; Degnan, John J.; Titterton, Paul J., Sr.; Sweeney, Harold E.; Conklin, Brion P.; Dunn, Peter J.

1996-06-01

NASA's Satellite Laser Ranging Network was originally developed during the 1970's to track satellites carrying corner cube reflectors. Today eight NASA systems, achieving millimeter ranging precision, are part of a global network of more than 40 stations that track 17 international satellites. To meet the tracking demands of a steadily growing satellite constellation within existing resources, NASA is embarking on a major automation program. While manpower on the current systems will be reduced to a single operator, the fully automated SLR2000 system is being designed to operate for months without human intervention. Because SLR2000 must be eyesafe and operate in daylight, tracking is often performed in a low probability of detection and high noise environment. The goal is to automatically select the satellite, setup the tracking and ranging hardware, verify acquisition, and close the tracking loop to optimize data yield. TO accomplish the autotracking tasks, we are investigating (1) improved satellite force models, (2) more frequent updates of orbital ephemerides, (3) lunar laser ranging data processing techniques to distinguish satellite returns from noise, and (4) angular detection and search techniques to acquire the satellite. A Monte Carlo simulator has been developed to allow optimization of the autotracking algorithms by modeling the relevant system errors and then checking performance against system truth. A combination of simulator and preliminary field results will be presented.

Developing NOAA's Climate Data Records From AVHRR and Other Data

Science.gov (United States)

Privette, J. L.; Bates, J. J.; Kearns, E. J.

2010-12-01

As part of the provisional NOAA Climate Service, NOAA is providing leadership in the development of authoritative, measurement-based information on climate change and variability. NOAA’s National Climatic Data Center (NCDC) recently initiated a satellite Climate Data Record Program (CDRP) to provide sustained and objective climate information derived from meteorological satellite data that NOAA has collected over the past 30+ years - particularly from its Polar Orbiting Environmental Satellites (POES) program. These are the longest sustained global measurement records in the world and represent billions of dollars of investment. NOAA is now applying advanced analysis methods -- which have improved remarkably over the last decade -- to the POES AVHRR and other instrument data. Data from other satellite programs, including NASA and international research programs and the Defense Meteorological Satellite Program (DMSP), are also being used. This process will unravel the underlying climate trend and variability information and return new value from the records. In parallel, NCDC will extend these records by applying the same methods to present-day and future satellite measurements, including the Joint Polar Satellite System (JPSS) and Jason-3. In this presentation, we will describe the AVHRR-related algorithm development activities that CDRP recently selected and funded through open competitions. We will particularly discuss some of the technical challenges related to adapting and using AVHRR algorithms with the VIIRS data that should become available with the launch of the NPOESS Preparatory Project (NPP) satellite in early 2012. We will also describe IT system development activities that will provide data processing and reprocessing, storage and management. We will also outline the maturing Program framework, including the strategies for coding and development standards, community reviews, independent program oversight, and research-to-operations algorithm

Detection of High Frequency Oscillations by Hybrid Depth Electrodes in Standard Clinical Intracranial EEG Recordings

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Efstathios D Kondylis

2014-08-01

Full Text Available High frequency oscillations (HFOs have been proposed as a novel marker for epileptogenic tissue, spurring tremendous research interest into the characterization of these transient events. A wealth of continuously recorded intracranial electroencephalographic (iEEG data is currently available from patients undergoing invasive monitoring for the surgical treatment of epilepsy. In contrast to data recorded on research-customized recording systems, data from clinical acquisition systems remain an underutilized resource for HFO detection in most centers. The effective and reliable use of this clinically obtained data would be an important advance in the ongoing study of HFOs and their relationship to ictogenesis. The diagnostic utility of HFOs ultimately will be limited by the ability of clinicians to detect these brief, sporadic, and low amplitude events in an electrically noisy clinical environment. Indeed, one of the most significant factors limiting the use of such clinical recordings for research purposes is their low signal to noise ratio, especially in the higher frequency bands. In order to investigate the presence of HFOs in clinical data, we first obtained continuous intracranial recordings in a typical clinical environment using a commercially available, commonly utilized data acquisition system and off the shelf hybrid macro/micro depth electrodes. This data was then inspected for the presence of HFOs using semi-automated methods and expert manual review. With targeted removal of noise frequency content, HFOs were detected on both macro- and micro-contacts, and preferentially localized to seizure onset zones. HFOs detected by the offline, semi-automated method were also validated in the clinical viewer, demonstrating that 1 this clinical system allows for the visualization of HFOs, and 2 with effective signal processing, clinical recordings can yield valuable information for offline analysis.

Forensic applications of infrared imaging for the detection and recording of latent evidence.

Science.gov (United States)

Lin, Apollo Chun-Yen; Hsieh, Hsing-Mei; Tsai, Li-Chin; Linacre, Adrian; Lee, James Chun-I

2007-09-01

We report on a simple method to record infrared (IR) reflected images in a forensic science context. Light sources using ultraviolet light have been used previously in the detection of latent prints, but the use of infrared light has been subjected to less investigation. IR light sources were used to search for latent evidence and the images were captured by either video or using a digital camera with a CCD array sensitive to IR wavelength. Bloodstains invisible to the eye, inks, tire prints, gunshot residue, and charred document on dark background are selected as typical matters that may be identified during a forensic investigation. All the evidence types could be detected and identified using a range of photographic techniques. In this study, a one in eight times dilution of blood could be detected on 10 different samples of black cloth. When using 81 black writing inks, the observation rates were 95%, 88% and 42% for permanent markers, fountain pens and ball-point pens, respectively, on the three kinds of dark cloth. The black particles of gunshot residue scattering around the entrance hole under IR light were still observed at a distance of 60 cm from three different shooting ranges. A requirement of IR reflectivity is that there is a contrast between the latent evidence and the background. In the absence of this contrast no latent image will be detected, which is similar to all light sources. The use of a video camera allows the recording of images either at a scene or in the laboratory. This report highlights and demonstrates the robustness of IR to detect and record the presence of latent evidence.

Satellite Remote Sensing in Seismology. A Review

Directory of Open Access Journals (Sweden)

Andrew A. Tronin

2009-12-01

Full Text Available A wide range of satellite methods is applied now in seismology. The first applications of satellite data for earthquake exploration were initiated in the ‘70s, when active faults were mapped on satellite images. It was a pure and simple extrapolation of airphoto geological interpretation methods into space. The modern embodiment of this method is alignment analysis. Time series of alignments on the Earth's surface are investigated before and after the earthquake. A further application of satellite data in seismology is related with geophysical methods. Electromagnetic methods have about the same long history of application for seismology. Stable statistical estimations of ionosphere-lithosphere relation were obtained based on satellite ionozonds. The most successful current project "DEMETER" shows impressive results. Satellite thermal infra-red data were applied for earthquake research in the next step. Numerous results have confirmed previous observations of thermal anomalies on the Earth's surface prior to earthquakes. A modern trend is the application of the outgoing long-wave radiation for earthquake research. In ‘80s a new technology—satellite radar interferometry—opened a new page. Spectacular pictures of co-seismic deformations were presented. Current researches are moving in the direction of pre-earthquake deformation detection. GPS technology is also widely used in seismology both for ionosphere sounding and for ground movement detection. Satellite gravimetry has demonstrated its first very impressive results on the example of the catastrophic Indonesian earthquake in 2004. Relatively new applications of remote sensing for seismology as atmospheric sounding, gas observations, and cloud analysis are considered as possible candidates for applications.

Real time deforestation detection using ann and satellite images the Amazon rainforest study case

CERN Document Server

Nunes Kehl, Thiago; Roberto Veronez, Maurício; Cesar Cazella, Silvio

2015-01-01

The foremost aim of the present study was the development of a tool to detect daily deforestation in the Amazon rainforest, using satellite images from the MODIS/TERRA sensor and Artificial Neural Networks. The developed tool provides parameterization of the configuration for the neural network training to enable us to select the best neural architecture to address the problem. The tool makes use of confusion matrices to determine the degree of success of the network. A spectrum-temporal analysis of the study area was done on 57 images from May 20 to July 15, 2003 using the trained neural network. The analysis enabled verification of quality of the implemented neural network classification and also aided in understanding the dynamics of deforestation in the Amazon rainforest, thereby highlighting the vast potential of neural networks for image classification. However, the complex task of detection of predatory actions at the beginning, i.e., generation of consistent alarms, instead of false alarms has not bee...

Passivity Based Nonlinear Attitude Control of the Rømer Satellite

DEFF Research Database (Denmark)

Quottrup, Michael Melholt; Krogh-Sørensen, J.; Wisniewski, Rafal

2001-01-01

This paper suggests nonlinear attitude control of the Danish satellite Rømer. This satellite will be designed to fulfil two scientific objectives: The observation of stellar oscillations and the detection and localisation of gamma-ray bursts. The satellite will be equipped with a tetrahedron...

The application of an optical Fourier spectrum analyzer on detecting defects in mass-produced satellite photographs

Science.gov (United States)

Athale, R.; Lee, S. H.

1976-01-01

Various defects in mass-produced pictures transmitted to earth from a satellite are investigated. It is found that the following defects are readily detectable via Fourier spectrum analysis: (1) bit slip, (2) breakup causing loss of image, and (3) disabled track at the top of the imagery. The scratches made on the film during mass production, which are difficult to detect by visual observation, also show themselves readily in Fourier spectrum analysis. A relation is established between the number of scratches, their width and depth and the intensity of their Fourier spectra. Other defects that are found to be equally suitable for Fourier spectrum analysis or visual (image analysis) detection are synchronous loss without blurring of image, and density variation in gray scale. However, the Fourier spectrum analysis is found to be unsuitable for detection of such defects as pin holes, annotation error, synchronous loss with blurring of images, and missing image in the beginning of the work order. The design of an automated, real time system, which will reject defective films, is treated.

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

Science.gov (United States)

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

2017-08-01

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

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

DEFF Research Database (Denmark)

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

2006-01-01

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

Assessment of satellite-based precipitation estimates over Paraguay

Science.gov (United States)

Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

2018-04-01

Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

Predictive modeling of structured electronic health records for adverse drug event detection.

Science.gov (United States)

Zhao, Jing; Henriksson, Aron; Asker, Lars; Boström, Henrik

2015-01-01

The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. This can be exploited to support public health activities such as pharmacovigilance, wherein the safety of drugs is monitored to inform regulatory decisions about sustained use. To that end, electronic health records have emerged as a potentially valuable data source, providing access to longitudinal observations of patient treatment and drug use. A nascent line of research concerns predictive modeling of healthcare data for the automatic detection of adverse drug events, which presents its own set of challenges: it is not yet clear how to represent the heterogeneous data types in a manner conducive to learning high-performing machine learning models. Datasets from an electronic health record database are used for learning predictive models with the purpose of detecting adverse drug events. The use and representation of two data types, as well as their combination, are studied: clinical codes, describing prescribed drugs and assigned diagnoses, and measurements. Feature selection is conducted on the various types of data to reduce dimensionality and sparsity, while allowing for an in-depth feature analysis of the usefulness of each data type and representation. Within each data type, combining multiple representations yields better predictive performance compared to using any single representation. The use of clinical codes for adverse drug event detection significantly outperforms the use of measurements; however, there is no significant difference over datasets between using only clinical codes and their combination with measurements. For certain adverse drug events, the combination does, however, outperform using only clinical codes. Feature selection leads to increased predictive performance for both data types, in isolation and

H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

Science.gov (United States)

Kalia, Subodh; Ganguly, Sangram; Li, Shuang; Nemani, Ramakrishna R.

2017-01-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remote sensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud shadow mask from geostationary satellite data is critical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds,which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classify cloudshadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoderdecoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multispectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

A simple system for detection of EEG artifacts in polysomnographic recordings.

Science.gov (United States)

Durka, P J; Klekowicz, H; Blinowska, K J; Szelenberger, W; Niemcewicz, Sz

2003-04-01

We present an efficient parametric system for automatic detection of electroencephalogram (EEG) artifacts in polysomnographic recordings. For each of the selected types of artifacts, a relevant parameter was calculated for a given epoch. If any of these parameters exceeded a threshold, the epoch was marked as an artifact. Performance of the system, evaluated on 18 overnight polysomnographic recordings, revealed concordance with decisions of human experts close to the interexpert agreement and the repeatability of expert's decisions, assessed via a double-blind test. Complete software (Matlab source code) for the presented system is freely available from the Internet at http://brain.fuw.edu.pl/artifacts.

LiteBIRD: a small satellite for the study of B-mode polarization and inflation from cosmic background radiation detection

Science.gov (United States)

Hazumi, M.; Borrill, J.; Chinone, Y.; Dobbs, M. A.; Fuke, H.; Ghribi, A.; Hasegawa, M.; Hattori, K.; Hattori, M.; Holzapfel, W. L.; Inoue, Y.; Ishidoshiro, K.; Ishino, H.; Karatsu, K.; Katayama, N.; Kawano, I.; Kibayashi, A.; Kibe, Y.; Kimura, N.; Koga, K.; Komatsu, E.; Lee, A. T.; Matsuhara, H.; Matsumura, T.; Mima, S.; Mitsuda, K.; Morii, H.; Murayama, S.; Nagai, M.; Nagata, R.; Nakamura, S.; Natsume, K.; Nishino, H.; Noda, A.; Noguchi, T.; Ohta, I.; Otani, C.; Richards, P. L.; Sakai, S.; Sato, N.; Sato, Y.; Sekimoto, Y.; Shimizu, A.; Shinozaki, K.; Sugita, H.; Suzuki, A.; Suzuki, T.; Tajima, O.; Takada, S.; Takagi, Y.; Takei, Y.; Tomaru, T.; Uzawa, Y.; Watanabe, H.; Yamasaki, N.; Yoshida, M.; Yoshida, T.; Yotsumoto, K.

2012-09-01

LiteBIRD [Lite (Light) satellite for the studies of B-mode polarization and Inflation from cosmic background Radiation Detection] is a small satellite to map the polarization of the cosmic microwave background (CMB) radiation over the full sky at large angular scales with unprecedented precision. Cosmological inflation, which is the leading hypothesis to resolve the problems in the Big Bang theory, predicts that primordial gravitational waves were created during the inflationary era. Measurements of polarization of the CMB radiation are known as the best probe to detect the primordial gravitational waves. The LiteBIRD working group is authorized by the Japanese Steering Committee for Space Science (SCSS) and is supported by JAXA. It has more than 50 members from Japan, USA and Canada. The scientific objective of LiteBIRD is to test all the representative inflation models that satisfy single-field slow-roll conditions and lie in the large-field regime. To this end, the requirement on the precision of the tensor-to-scalar ratio, r, at LiteBIRD is equal to or less than 0.001. Our baseline design adopts an array of multi-chroic superconducting polarimeters that are read out with high multiplexing factors in the frequency domain for a compact focal plane. The required sensitivity of 1.8μKarcmin is achieved with 2000 TES bolometers at 100mK. The cryogenic system is based on the Stirling/JT technology developed for SPICA, and the continuous ADR system shares the design with future X-ray satellites.

A neural network detection system for lower-hybrid cavities in electron plasma density measured by the FREJA satellite

International Nuclear Information System (INIS)

Waldemark, J.; Karlsson, Jan

1995-03-01

This paper presents a lower-hybrid cavity detection system, CDS, for measurements of electron plasma density on the FREJA satellite wave experiment. The system can reduce the amount of data to be analysed by as much as 96% and still retain more than 85% of the desired information. The CDS is a combination of a hybrid neural network, HNN and expert rules. The HNN is a Self Organizing Map, SOM, combined with a feed forward back propagation neural net, BP. The CDS can be controlled by the user to operate with various degrees of sensitivity. Maximum detection capability is as high as 95% with data reduction lowered to 85%. 10 refs

Observation of GEO Satellite Above Thailand’s Sky

Science.gov (United States)

Kasonsuwan, K.; Wannawichian, S.; Kirdkao, T.

2017-09-01

The direct observations of Geostationary Orbit (GEO) satellites above Thailand’s sky by 0.7-meters telescope were proceeded at Inthanon Mt., Chiang Mai, Thailand. The observation took place at night with Sidereal Stare Mode (SSM). With this observing mode, the moving object will appear as a streak. The star identification for image calibration is based on (1) a star catalogue, (2) the streak detection of the satellite using the software and (3) the extraction of the celestial coordinate of the satellite as a predicted position. Finally, the orbital elements for GEO satellites were calculated.

Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis)

Science.gov (United States)

Carvalho, Gustavo A.; Minnett, Peter J.; Fleming, Lora E.; Banzon, Viva F.; Baringer, Warner

2010-01-01

In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods – July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×104 cells l−1 defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs. PMID:21037979

Fine-tuning satellite-based rainfall estimates

Science.gov (United States)

Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

2018-05-01

Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

Monitoring volcanic thermal activity by Robust Satellite Techniques: achievements and perspectives

Science.gov (United States)

Tramutoli, V.; Marchese, F.; Mazzeo, G.; Pergola, N.

2009-12-01

Satellite data have been increasingly used in last decades to study active volcanoes and to monitor thermal activity variation in space-time domain. Several satellite techniques and original methods have been developed and tested, devoted to hotspot detection and thermal monitoring. Among them, a multi-temporal approach, named RST (Robust Satellite Techniques), has shown high performances in detecting hotspots, with a low false positive rate under different observational and atmospheric conditions, providing also a potential toward low-level thermal anomalies which may announce incoming eruptions. As the RST scheme is intrinsically exportable on different geographic areas and satellite sensors, it has been applied and tested on a number of volcanoes and in different environmental conditions. This work presents major results and outcomes of studies carried out on Etna and Stromboli (Italy), Merapi (Java Indonesia), Asamayama (Japan), Jebel Al Tair (Yemen) by using different satellite systems and sensors (e.g. NOAA-AVHRR, EOS-MODIS, MSG-SEVIRI). Performances on hotspot detection, early warning and real-time monitoring, together with capabilities in possible thermal precursor identification, will be presented and discussed.

Towards an integrated strategy for monitoring wetland inundation with virtual constellations of optical and radar satellites

Science.gov (United States)

DeVries, B.; Huang, W.; Huang, C.; Jones, J. W.; Lang, M. W.; Creed, I. F.; Carroll, M.

2017-12-01

The function of wetlandscapes in hydrological and biogeochemical cycles is largely governed by surface inundation, with small wetlands that experience periodic inundation playing a disproportionately large role in these processes. However, the spatial distribution and temporal dynamics of inundation in these wetland systems are still poorly understood, resulting in large uncertainties in global water, carbon and greenhouse gas budgets. Satellite imagery provides synoptic and repeat views of the Earth's surface and presents opportunities to fill this knowledge gap. Despite the proliferation of Earth Observation satellite missions in the past decade, no single satellite sensor can simultaneously provide the spatial and temporal detail needed to adequately characterize inundation in small, dynamic wetland systems. Surface water data products must therefore integrate observations from multiple satellite sensors in order to address this objective, requiring the development of improved and coordinated algorithms to generate consistent estimates of surface inundation. We present a suite of algorithms designed to detect surface inundation in wetlands using data from a virtual constellation of optical and radar sensors comprising the Landsat and Sentinel missions (DeVries et al., 2017). Both optical and radar algorithms were able to detect inundation in wetlands without the need for external training data, allowing for high-efficiency monitoring of wetland inundation at large spatial and temporal scales. Applying these algorithms across a gradient of wetlands in North America, preliminary findings suggest that while these fully automated algorithms can detect wetland inundation at higher spatial and temporal resolutions than currently available surface water data products, limitations specific to the satellite sensors and their acquisition strategies are responsible for uncertainties in inundation estimates. Further research is needed to investigate strategies for

Automatic Threshold Determination for a Local Approach of Change Detection in Long-Term Signal Recordings

Directory of Open Access Journals (Sweden)

David Hewson

2007-01-01

Full Text Available CUSUM (cumulative sum is a well-known method that can be used to detect changes in a signal when the parameters of this signal are known. This paper presents an adaptation of the CUSUM-based change detection algorithms to long-term signal recordings where the various hypotheses contained in the signal are unknown. The starting point of the work was the dynamic cumulative sum (DCS algorithm, previously developed for application to long-term electromyography (EMG recordings. DCS has been improved in two ways. The first was a new procedure to estimate the distribution parameters to ensure the respect of the detectability property. The second was the definition of two separate, automatically determined thresholds. One of them (lower threshold acted to stop the estimation process, the other one (upper threshold was applied to the detection function. The automatic determination of the thresholds was based on the Kullback-Leibler distance which gives information about the distance between the detected segments (events. Tests on simulated data demonstrated the efficiency of these improvements of the DCS algorithm.

Satellite sar detection of hurricane helene (2006)

DEFF Research Database (Denmark)

Ju, Lian; Cheng, Yongcun; Xu, Qing

2013-01-01

In this paper, the wind structure of hurricane Helene (2006) over the Atlantic Ocean is investigated from a C-band RADARSAT-1 synthetic aperture radar (SAR) image acquired on 20 September 2006. First, the characteristics, e.g., the center, scale and area of the hurricane eye (HE) are determined. ...... observations from the stepped frequency microwave radiometer (SFMR) on NOAA P3 aircraft. All the results show the capability of hurricane monitoring by satellite SAR. Copyright © 2013 by the International Society of Offshore and Polar Engineers (ISOPE)....

Flexible Method for the Automated Offline-Detection of Artifacts in Multi-Channel Electroencephalogram Recordings

DEFF Research Database (Denmark)

Waser, Markus; Garn, Heinrich; Benke, Thomas

2017-01-01

. However, these preprocessing steps do not allow for complete artifact correction. We propose a method for the automated offline-detection of remaining artifacts after preprocessing in multi-channel EEG recordings. In contrast to existing methods it requires neither adaptive parameters varying between...... recordings nor a topography template. It is suited for short EEG segments and is flexible with regard to target applications. The algorithm was developed and tested on 60 clinical EEG samples of 20 seconds each that were recorded both in resting state and during cognitive activation to gain a realistic...

Experimental Demonstration of an Algorithm to Detect the Presence of a Parasitic Satellite

National Research Council Canada - National Science Library

Dabrowski, Vincent

2003-01-01

Published reports of microsatellite weapons testing have led to a concern that some of these "parasitic" satellites could be deployed against US satellites to rendezvous dock and then disrupt, degrade...

Automated Detection of Sepsis Using Electronic Medical Record Data: A Systematic Review.

Science.gov (United States)

Despins, Laurel A

Severe sepsis and septic shock are global issues with high mortality rates. Early recognition and intervention are essential to optimize patient outcomes. Automated detection using electronic medical record (EMR) data can assist this process. This review describes automated sepsis detection using EMR data. PubMed retrieved publications between January 1, 2005 and January 31, 2015. Thirteen studies met study criteria: described an automated detection approach with the potential to detect sepsis or sepsis-related deterioration in real or near-real time; focused on emergency department and hospitalized neonatal, pediatric, or adult patients; and provided performance measures or results indicating the impact of automated sepsis detection. Detection algorithms incorporated systemic inflammatory response and organ dysfunction criteria. Systems in nine studies generated study or care team alerts. Care team alerts did not consistently lead to earlier interventions. Earlier interventions did not consistently translate to improved patient outcomes. Performance measures were inconsistent. Automated sepsis detection is potentially a means to enable early sepsis-related therapy but current performance variability highlights the need for further research.

Homogeneity of a Global Multisatellite Soil Moisture Climate Data Record

Science.gov (United States)

Su, Chun-Hsu; Ryu, Dongryeol; Dorigo, Wouter; Zwieback, Simon; Gruber, Alexander; Albergel, Clement; Reichle, Rolf H.; Wagner, Wolfgang

2016-01-01

Climate Data Records (CDR) that blend multiple satellite products are invaluable for climate studies, trend analysis and risk assessments. Knowledge of any inhomogeneities in the CDR is therefore critical for making correct inferences. This work proposes a methodology to identify the spatiotemporal extent of the inhomogeneities in a 36-year, global multisatellite soil moisture CDR as the result of changing observing systems. Inhomogeneities are detected at up to 24 percent of the tested pixels with spatial extent varying with satellite changeover times. Nevertheless, the contiguous periods without inhomogeneities at changeover times are generally longer than 10 years. Although the inhomogeneities have measurable impact on the derived trends, these trends are similar to those observed in ground data and land surface reanalysis, with an average error less than 0.003 cubic meters per cubic meter per year. These results strengthen the basis of using the product for long-term studies and demonstrate the necessity of homogeneity testing of multisatellite CDRs in general.

Search for shot-time growths of flares od cosmic heavy nuclei according to measurement data at ''Prognoz'' satellites

International Nuclear Information System (INIS)

Volodichev, N.N.; Savenko, I.A.; Suslov, A.A.

1983-01-01

Surch for short-time growths of fluxes of mainly cosmic heavy nuclei with the energy epsilon > or approximately 500 MeV/nucleon according to measurement data at ''Prognoz-2'' and ''Prognoz-3'' satellites is undertaken. Such growths have been recorded during the flights of the first soviet cosmic rockets, spacecraft-satellites, ''Electron'', ''Molnia-1'' satellites. At the ''Prognoz'' satellite such growth have not been observed. Moreover, the 2.1.1974 growth found at the ''Molnia-1'' satellite by the telescope of scintillation and Cherenkov counters has not been recorded by the analogous device at ''Prognoz-3'' satellite. Therefore, the problem on the nature of short-time growths of the heavy nuclei fluxes remains unsolved

The CM SAF SSM/I-based total column water vapour climate data record: methods and evaluation against re-analyses and satellite

Directory of Open Access Journals (Sweden)

M. Schröder

2013-03-01

Full Text Available The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF aims at the provision and sound validation of well documented Climate Data Records (CDRs in sustained and operational environments. In this study, a total column water vapour path (WVPA climatology from CM SAF is presented and inter-compared to water vapour data records from various data sources. Based on homogenised brightness temperatures from the Special Sensor Microwave Imager (SSM/I, a climatology of WVPA has been generated within the Hamburg Ocean–Atmosphere Fluxes and Parameters from Satellite (HOAPS framework. Within a research and operation transition activity the HOAPS data and operation capabilities have been successfully transferred to the CM SAF where the complete HOAPS data and processing schemes are hosted in an operational environment. An objective analysis for interpolation, namely kriging, has been applied to the swath-based WVPA retrievals from the HOAPS data set. The resulting climatology consists of daily and monthly mean fields of WVPA over the global ice-free ocean. The temporal coverage ranges from July 1987 to August 2006. After a comparison to the precursor product the CM SAF SSM/I-based climatology has been comprehensively compared to different types of meteorological analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF-ERA40, ERA INTERIM and operational analyses and from the Japan Meteorological Agency (JMA–JRA. This inter-comparison shows an overall good agreement between the climatology and the analyses, with daily absolute biases generally smaller than 2 kg m−2. The absolute value of the bias to JRA and ERA INTERIM is typically smaller than 0.5 kg m−2. For the period 1991–2006, the root mean square error (RMSE for both reanalyses is approximately 2 kg m−2. As SSM/I WVPA and radiances are assimilated into JMA and all ECMWF analyses and

Use of high-resolution satellite images for detection of geothermal reservoirs

Science.gov (United States)

Arellano-Baeza, A. A.

2012-12-01

Chile has an enormous potential to use the geothermal resources for electric energy generation. The main geothermal fields are located in the Central Andean Volcanic Chain in the North, between the Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT and ASTER satellites have been used to delineate the geological structures related to the Calerias geothermal field located at the northern end of the Southern Volcanic Zone of Chile and Puchuldiza geothermal field located in the Region of Tarapaca. It was done by applying the lineament extraction technique developed by author. These structures have been compared with the distribution of main geological structures obtained in the fields. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields.

Utilizing Multi-Sensor Fire Detections to Map Fires in the United States

Science.gov (United States)

Howard, S. M.; Picotte, J. J.; Coan, M. J.

2014-11-01

In 2006, the Monitoring Trends in Burn Severity (MTBS) project began a cooperative effort between the US Forest Service (USFS) and the U.S.Geological Survey (USGS) to map and assess burn severity all large fires that have occurred in the United States since 1984. Using Landsat imagery, MTBS is mandated to map wildfire and prescribed fire that meet specific size criteria: greater than 1000 acres in the west and 500 acres in the east, regardless of ownership. Relying mostly on federal and state fire occurrence records, over 15,300 individual fires have been mapped. While mapping recorded fires, an additional 2,700 "unknown" or undocumented fires were discovered and assessed. It has become apparent that there are perhaps thousands of undocumented fires in the US that are yet to be mapped. Fire occurrence records alone are inadequate if MTBS is to provide a comprehensive accounting of fire across the US. Additionally, the sheer number of fires to assess has overwhelmed current manual procedures. To address these problems, the National Aeronautics and Space Administration (NASA) Applied Sciences Program is helping to fund the efforts of the USGS and its MTBS partners (USFS, National Park Service) to develop, and implement a system to automatically identify fires using satellite data. In near real time, USGS will combine active fire satellite detections from MODIS, AVHRR and GOES satellites with Landsat acquisitions. Newly acquired Landsat imagery will be routinely scanned to identify freshly burned area pixels, derive an initial perimeter and tag the burned area with the satellite date and time of detection. Landsat imagery from the early archive will be scanned to identify undocumented fires. Additional automated fire assessment processes will be developed. The USGS will develop these processes using open source software packages in order to provide freely available tools to local land managers providing them with the capability to assess fires at the local level.

Fetal movement detection based on QRS amplitude variations in abdominal ECG recordings.

Science.gov (United States)

Rooijakkers, M J; de Lau, H; Rabotti, C; Oei, S G; Bergmans, J W M; Mischi, M

2014-01-01

Evaluation of fetal motility can give insight in fetal health, as a strong decrease can be seen as a precursor to fetal death. Typically, the assessment of fetal health by fetal movement detection relies on the maternal perception of fetal activity. The percentage of detected movements is strongly subject dependent and with undivided attention of the mother varies between 37% to 88%. Various methods to assist in fetal movement detection exist based on a wide spectrum of measurement techniques. However, these are typically unsuitable for ambulatory or long-term observation. In this paper, a novel method for fetal motion detection is presented based on amplitude and shape changes in the abdominally recorded fetal ECG. The proposed method has a sensitivity and specificity of 0.67 and 0.90, respectively, outperforming alternative fetal ECG-based methods from the literature.

Satellites

International Nuclear Information System (INIS)

Burns, J.A.; Matthews, M.S.

1986-01-01

The present work is based on a conference: Natural Satellites, Colloquium 77 of the IAU, held at Cornell University from July 5 to 9, 1983. Attention is given to the background and origins of satellites, protosatellite swarms, the tectonics of icy satellites, the physical characteristics of satellite surfaces, and the interactions of planetary magnetospheres with icy satellite surfaces. Other topics include the surface composition of natural satellites, the cratering of planetary satellites, the moon, Io, and Europa. Consideration is also given to Ganymede and Callisto, the satellites of Saturn, small satellites, satellites of Uranus and Neptune, and the Pluto-Charon system

Comparison of semiautomated bird song recognition with manual detection of recorded bird song samples

OpenAIRE

Lisa A. Venier; Marc J. Mazerolle; Anna Rodgers; Ken A. McIlwrick; Stephen Holmes; Dean Thompson

2017-01-01

Automated recording units are increasingly being used to sample wildlife populations. These devices can produce large amounts of data that are difficult to process manually. However, the information in the recordings can be summarized with semiautomated sound recognition software. Our objective was to assess the utility of the semiautomated bird song recognizers to produce data useful for conservation and sustainable forest management applications. We compared detection data generated from ex...

Pre-seismic anomalies from optical satellite observations: a review

Science.gov (United States)

Jiao, Zhong-Hu; Zhao, Jing; Shan, Xinjian

2018-04-01

Detecting various anomalies using optical satellite data prior to strong earthquakes is key to understanding and forecasting earthquake activities because of its recognition of thermal-radiation-related phenomena in seismic preparation phases. Data from satellite observations serve as a powerful tool in monitoring earthquake preparation areas at a global scale and in a nearly real-time manner. Over the past several decades, many new different data sources have been utilized in this field, and progressive anomaly detection approaches have been developed. This paper reviews the progress and development of pre-seismic anomaly detection technology in this decade. First, precursor parameters, including parameters from the top of the atmosphere, in the atmosphere, and on the Earth's surface, are stated and discussed. Second, different anomaly detection methods, which are used to extract anomalous signals that probably indicate future seismic events, are presented. Finally, certain critical problems with the current research are highlighted, and new developing trends and perspectives for future work are discussed. The development of Earth observation satellites and anomaly detection algorithms can enrich available information sources, provide advanced tools for multilevel earthquake monitoring, and improve short- and medium-term forecasting, which play a large and growing role in pre-seismic anomaly detection research.

Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

Science.gov (United States)

Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

2017-04-01

Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze

Satellite-based detection of global urban heat-island temperature influence

Science.gov (United States)

Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

2002-01-01

This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

Preliminary study on peroxidase isoenzyme detection and RAPD molecular verification for sweet pepper 87-2 carried by a recoverable satellite

International Nuclear Information System (INIS)

Liu Min; Li Jinguo; Wang Yalin; Zhang Zan; Xue Huai; Zhang Chunhua; Li Sherong

1999-01-01

The detection technology of peroxidase isoenzyme pattern and RAPD (Randomly Amplified Polymorphic DNA) analysis were used to space-flown sweet pepper variety of 87-2 carried by a recoverable satellite, and its correspondent ground control Longjiao-2. Determination of peroxidase isoenzyme revealed that the physiological activities of space-flown sweet pepper were significantly higher than those of its ground control. To detect the polymorphism of gene sequence and the difference in molecular level. 42 primers were used, among them, 38 primers amplified polymorphic products, and the amplified products from 5 primers of sweet pepper 87-2 differed from those of ground control

Plasma waves and electric discharges induced by a beam from a high-latitude satellite

International Nuclear Information System (INIS)

Kuns, G.; Koen, G.

1985-01-01

Using P78-2 satellite measurements of characteristics of space probe charging in synchronous orbit are carried out. A particle beam generation system including electron and ion guns was part of the satellite equipment. Electric charge analyser placed aboard the satellite in course of electron and ion beam generation recorded plasma waves and electric discharges

Isolation, Culture, Functional Assays, and Immunofluorescence of Myofiber-Associated Satellite Cells.

Science.gov (United States)

Vogler, Thomas O; Gadek, Katherine E; Cadwallader, Adam B; Elston, Tiffany L; Olwin, Bradley B

2016-01-01

Adult skeletal muscle stem cells, termed satellite cells, regenerate and repair the functional contractile cells in adult skeletal muscle called myofibers. Satellite cells reside in a niche between the basal lamina and sarcolemma of myofibers. Isolating single myofibers and their associated satellite cells provides a culture system that partially mimics the in vivo environment. We describe methods for isolating and culturing intact individual myofibers and their associated satellite cells from the mouse extensor digitorum longus muscle. Following dissection and isolation of individual myofibers we provide protocols for myofiber transplantation, satellite cell transfection, immune detection of satellite cell antigens, and assays to examine satellite cell self-renewal and proliferation.

Dissemination of satellite-based river discharge and flood data

Science.gov (United States)

Kettner, A. J.; Brakenridge, G. R.; van Praag, E.; de Groeve, T.; Slayback, D. A.; Cohen, S.

2014-12-01

In collaboration with NASA Goddard Spaceflight Center and the European Commission Joint Research Centre, the Dartmouth Flood Observatory (DFO) daily measures and distributes: 1) river discharges, and 2) near real-time flood extents with a global coverage. Satellite-based passive microwave sensors and hydrological modeling are utilized to establish 'remote-sensing based discharge stations', and observed time series cover 1998 to the present. The advantages over in-situ gauged discharges are: a) easy access to remote or due to political reasons isolated locations, b) relatively low maintenance costs to maintain a continuous observational record, and c) the capability to obtain measurements during floods, hazardous conditions that often impair or destroy in-situ stations. Two MODIS instruments aboard the NASA Terra and Aqua satellites provide global flood extent coverage at a spatial resolution of 250m. Cloud cover hampers flood extent detection; therefore we ingest 6 images (the Terra and Aqua images of each day, for three days), in combination with a cloud shadow filter, to provide daily global flood extent updates. The Flood Observatory has always made it a high priority to visualize and share its data and products through its website. Recent collaborative efforts with e.g. GeoSUR have enhanced accessibility of DFO data. A web map service has been implemented to automatically disseminate geo-referenced flood extent products into client-side GIS software. For example, for Latin America and the Caribbean region, the GeoSUR portal now displays current flood extent maps, which can be integrated and visualized with other relevant geographical data. Furthermore, the flood state of satellite-observed river discharge sites are displayed through the portal as well. Additional efforts include implementing Open Geospatial Consortium (OGC) standards to incorporate Water Markup Language (WaterML) data exchange mechanisms to further facilitate the distribution of the satellite

Spatio-temporal hotspots of satellite-tracked arctic foxes reveal a large detection range in a mammalian predator.

Science.gov (United States)

Lai, Sandra; Bêty, Joël; Berteaux, Dominique

2015-01-01

The scale at which animals perceive their environment is a strong fitness determinant, yet few empirical estimates of animal detection ranges exist, especially in mammalian predators. Using daily Argos satellite tracking of 26 adult arctic foxes (Vulpes lagopus) during a single winter in the High Canadian Arctic, we investigated the detection range of arctic foxes by detecting hotspots of fox activity on the sea ice. While maintaining territories in the tundra, these solitary foragers occasionally used the sea ice where they sometimes formed spatio-temporal hotspots, likely scavenging on marine mammal carcasses. We detected 35 movements by 13 individuals forming five hotspots. Foxes often traveled more than 10 km, and up to 40 km, to reach hotspots, which lasted one-two weeks and could gather up to 12 individuals. The likelihood of a fox joining a hotspot was neither influenced by its distance from the hotspot nor by the distance of its home range to the coast. Observed traveling distances may indicate a high detection range in arctic foxes, and our results suggest their ability to detect food sources on the sea ice from their terrestrial home range. While revealing a wide knowledge gap regarding resource detection abilities in mammalian predators, our study provides estimates of detection range useful for interpreting and modeling animal movements. It also allows a better understanding of foraging behavior and navigation capacity in terrestrial predators.

Structural assurance testing for post-shipping satellite inspection

Science.gov (United States)

Reynolds, Whitney D.; Doyle, Derek; Arritt, Brandon

2012-04-01

Current satellite transportation sensors can provide a binary indication of the acceleration or shock that a satellite has experienced during the shipping process but do little to identify if significant structural change has occurred in the satellite and where it may be located. When a sensor indicates that the satellite has experienced shock during transit, an extensive testing process begins to evaluate the satellite functionality. If errors occur during the functional checkout, extensive physical inspection of the structure follows. In this work an alternate method for inspecting satellites for structural defects after shipping is presented. Electro- Mechanical Impedance measurements are used as an indication of the structural state. In partnership with the Air Force Research Laboratory University Nanosatellite Program, Cornell's CUSat mass model was instrumented with piezoelectric transducers and tested under several structural damage scenarios. A method for detecting and locating changes in the structure using EMI data is presented.

Velocity estimation of an airplane through a single satellite image

Institute of Scientific and Technical Information of China (English)

Zhuxin Zhao; Gongjian Wen; Bingwei Hui; Deren Li

2012-01-01

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

Noise detection during heart sound recording using periodicity signatures

International Nuclear Information System (INIS)

Kumar, D; Carvalho, P; Paiva, R P; Henriques, J; Antunes, M

2011-01-01

Heart sound is a valuable biosignal for diagnosis of a large set of cardiac diseases. Ambient and physiological noise interference is one of the most usual and highly probable incidents during heart sound acquisition. It tends to change the morphological characteristics of heart sound that may carry important information for heart disease diagnosis. In this paper, we propose a new method applicable in real time to detect ambient and internal body noises manifested in heart sound during acquisition. The algorithm is developed on the basis of the periodic nature of heart sounds and physiologically inspired criteria. A small segment of uncontaminated heart sound exhibiting periodicity in time as well as in the time-frequency domain is first detected and applied as a reference signal in discriminating noise from the sound. The proposed technique has been tested with a database of heart sounds collected from 71 subjects with several types of heart disease inducing several noises during recording. The achieved average sensitivity and specificity are 95.88% and 97.56%, respectively

a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

Science.gov (United States)

Haigang, Sui; Zhina, Song

2016-06-01

Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.

Test-day records as a tool for subclinical ketosis detection

OpenAIRE

Gantner Vesna; Potočnik K.; Jovanovac Sonja

2009-01-01

The prevalence, as well as the effect of subclinical ketosis on daily milk yield, was observed using 1.299,630 test-day records collected from January 2000 to December 2005 on 73,255 Slovenian Holstein cows. Subclinical ketosis was indicated by the fat to protein ratio (F/P ratio) higher than 1.5 in cows that yielded between 33 to 50 kg of milk per day (Eicher, 2004). The ketosis index was defined in relation to the timing of subclinical ketosis detection to the subsequent measures of test-da...

Data-driven drug safety signal detection methods in pharmacovigilance using electronic primary care records: A population based study

Directory of Open Access Journals (Sweden)

Shang-Ming Zhou

2017-04-01

Data-driven analytic methods are a valuable aid to signal detection of ADEs from large electronic health records for drug safety monitoring. This study finds the methods can detect known ADE and so could potentially be used to detect unknown ADE.

Long Short-Term Memory Neural Networks for Online Disturbance Detection in Satellite Image Time Series

Directory of Open Access Journals (Sweden)

Yun-Long Kong

2018-03-01

Full Text Available A satellite image time series (SITS contains a significant amount of temporal information. By analysing this type of data, the pattern of the changes in the object of concern can be explored. The natural change in the Earth’s surface is relatively slow and exhibits a pronounced pattern. Some natural events (for example, fires, floods, plant diseases, and insect pests and human activities (for example, deforestation and urbanisation will disturb this pattern and cause a relatively profound change on the Earth’s surface. These events are usually referred to as disturbances. However, disturbances in ecosystems are not easy to detect from SITS data, because SITS contain combined information on disturbances, phenological variations and noise in remote sensing data. In this paper, a novel framework is proposed for online disturbance detection from SITS. The framework is based on long short-term memory (LSTM networks. First, LSTM networks are trained by historical SITS. The trained LSTM networks are then used to predict new time series data. Last, the predicted data are compared with real data, and the noticeable deviations reveal disturbances. Experimental results using 16-day compositions of the moderate resolution imaging spectroradiometer (MOD13Q1 illustrate the effectiveness and stability of the proposed approach for online disturbance detection.

CLUMPY STREAMS FROM CLUMPY HALOS: DETECTING MISSING SATELLITES WITH COLD STELLAR STRUCTURES

International Nuclear Information System (INIS)

Yoon, Joo Heon; Johnston, Kathryn V.; Hogg, David W.

2011-01-01

Dynamically cold stellar streams are ideal probes of the gravitational field of the Milky Way. This paper re-examines the question of how such streams might be used to test for the presence of m issing satellites - the many thousands of dark-matter subhalos with masses 10 5 -10 7 M sun which are seen to orbit within Galactic-scale dark-matter halos in simulations of structure formation in ΛCDM cosmologies. Analytical estimates of the frequency and energy scales of stream encounters indicate that these missing satellites should have a negligible effect on hot debris structures, such as the tails from the Sagittarius dwarf galaxy. However, long cold streams, such as the structure known as GD1 or those from the globular cluster Palomar 5 (Pal 5), are expected to suffer many tens of direct impacts from missing satellites during their lifetimes. Numerical experiments confirm that these impacts create gaps in the debris' orbital energy distribution, which will evolve into degree- and sub-degree-scale fluctuations in surface density over the age of the debris. Maps of Pal 5's own stream contain surface density fluctuations on these scales. The presence and frequency of these inhomogeneities suggests the existence of a population of missing satellites in numbers predicted in the standard ΛCDM cosmologies.

A national accounts satellite for human capital and education

OpenAIRE

Bos, Frits

2011-01-01

The official national accounts statistics do not show the role of human capital in the national economy. A set of satellite tables supplementing the standard national accounts statistics could serve this data need. In this satellite account, expenditure on education and training are recorded as human capital formation. This includes not only the expenditure on primary, secondary and tertiary education, but also expenditure on training and courses by employers and the earnings foregone by stud...

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions with Climate Data Record Applications

Science.gov (United States)

Kim, Edward

2011-01-01

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201 I. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record-provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica-parameters such as surface temperature.

Satellite Observations from SEVIRI of Saharan dust over West Africa, within the context of the Fennec project

Science.gov (United States)

Banks, J.; Brindley, H.

2012-04-01

During the summer months, the atmosphere over the western half of the Sahara carries some of the highest dust loadings on the planet. This situation develops when intense solar heating over the dry desert creates a deep and hot low pressure system (the Saharan Heat Low, SHL), which allows a strong vertical mixing of dust. The Fennec* consortium project aims to address the deficiency in observations from the sparsely populated western Sahara through the use of field campaign measurements made in June 2011, incorporating observations from ground instruments, aircraft, and from satellite instruments such as SEVIRI, in combination with climate modelling. Fennec aims to study the poorly understood behaviour of the SHL, and the processes which take place within it. Due to their high temporal resolution, observations from SEVIRI can offer new insights into the timing of activation of specific dust sources, and the processes governing their behaviour. Here we employ a multi-year, high time-resolution record of dust detection and aerosol optical depth (AOD) derived from SEVIRI using an algorithm developed at Imperial College to both identify areas of high dust loading and diagnose diurnal patterns in their activation. We will present results from the SEVIRI record alongside results from other satellite instruments such as MODIS, and place these findings in the context of the initial ground-based and in-situ observations available from the Fennec field campaign. We will also identify surface features which can contaminate the dust detection retrieval, due to their emissivities in the 8.7 micron channel. New techniques can be used to filter out these features, based on the difference between the brightness temperatures at 10.8 and 8.7 microns. Using surface visibility measurements and AERONET data, we will evaluate the consequences of this on the dust detection and AOD record. * Fennec is a consortium project which includes groups from the universities of Oxford, Imperial

37 CFR 382.12 - Royalty fees for the public performance of sound recordings and the making of ephemeral recordings.

Science.gov (United States)

2010-07-01

... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Royalty fees for the public... Preexisting Satellite Digital Audio Radio Services § 382.12 Royalty fees for the public performance of sound recordings and the making of ephemeral recordings. (a) In general. The monthly royalty fee to be paid by a...

Development of a technique for long-term detection of precursors of strong earthquakes using high-resolution satellite images

Science.gov (United States)

Soto-Pinto, C. A.; Arellano-Baeza, A. A.; Ouzounov, D. P.

2012-12-01

Among a variety of processes involved in seismic activity, the principal process is the accumulation and relaxation of stress in the crust, which takes place at the depth of tens of kilometers. While the Earth's surface bears at most the indirect sings of the accumulation and relaxation of the crust stress, it has long been understood that there is a strong correspondence between the structure of the underlying crust and the landscape. We assume the structure of the lineaments reflects an internal structure of the Earth's crust, and the variation of the lineament number and arrangement reflects the changes in the stress patterns related to the seismic activity. Contrary to the existing assumptions that lineament structure changes only at the geological timescale, we have found that the much faster seismic activity strongly affects the system of lineaments extracted from the high-resolution multispectral satellite images. Previous studies have shown that accumulation of the stress in the crust previous to a strong earthquake is directly related to the number increment and preferential orientation of lineament configuration present in the satellite images of epicenter zones. This effect increases with the earthquake magnitude and can be observed approximately since one month before. To study in details this effect we have developed a software based on a series of algorithms for automatic detection of lineaments. It was found that the Hough transform implemented after the application of discontinuity detection mechanisms like Canny edge detector or directional filters is the most robust technique for detection and characterization of changes in the lineament patterns related to strong earthquakes, which can be used as a robust long-term precursor of earthquakes indicating regions of strong stress accumulation.

The best printing methods to print satellite images

Directory of Open Access Journals (Sweden)

G.A. Yousif

2011-12-01

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

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

Science.gov (United States)

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

2017-07-07

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

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

Directory of Open Access Journals (Sweden)

Douglas C. Comer

2017-10-01

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

Laser color recording unit

Science.gov (United States)

Jung, E.

1984-05-01

A color recording unit was designed for output and control of digitized picture data within computer controlled reproduction and picture processing systems. In order to get a color proof picture of high quality similar to a color print, together with reduced time and material consumption, a photographic color film material was exposed pixelwise by modulated laser beams of three wavelengths for red, green and blue light. Components of different manufacturers for lasers, acousto-optic modulators and polygon mirrors were tested, also different recording methods as (continuous tone mode or screened mode and with a drum or flatbed recording principle). Besides the application for the graphic arts - the proof recorder CPR 403 with continuous tone color recording with a drum scanner - such a color hardcopy peripheral unit with large picture formats and high resolution can be used in medicine, communication, and satellite picture processing.

Detection of soil erosion within pinyon-juniper woodlands using Thematic Mapper (TM) satellite data

Science.gov (United States)

Price, Kevin P.; Ridd, Merrill K.

1991-01-01

The sensitivity of Landsat TM data for detecting soil erosion within pinyon-juniper woodlands, and the potential of the spectral data for assigning the universal soil loss equation (USLE) crop managemnent (C) factor to varying cover types within the woodlands are assessed. Results show greatly accelerated rates of soil erosion on pinyon-juniper sites. Percent cover by pinyon-juniper, total soil-loss, and total nonliving ground cover accounted for nearly 70 percent of the variability in TM channels 2, 3, 4, and 5. TM spectral data were consistently better predictors of soil erosion than the biotic and abiotic field variables. Satellite data were more sensitive to vegetation variation than the USLE C factor, and USLE was found to be a poor predictor of soil loss on pinyon-juniper sites. A new string-to-ground soil erosion prediction technique is introduced.

On the feasibility of using satellite gravity observations for detecting large-scale solid mass transfer events

Science.gov (United States)

Peidou, Athina C.; Fotopoulos, Georgia; Pagiatakis, Spiros

2017-10-01

The main focus of this paper is to assess the feasibility of utilizing dedicated satellite gravity missions in order to detect large-scale solid mass transfer events (e.g. landslides). Specifically, a sensitivity analysis of Gravity Recovery and Climate Experiment (GRACE) gravity field solutions in conjunction with simulated case studies is employed to predict gravity changes due to past subaerial and submarine mass transfer events, namely the Agulhas slump in southeastern Africa and the Heart Mountain Landslide in northwestern Wyoming. The detectability of these events is evaluated by taking into account the expected noise level in the GRACE gravity field solutions and simulating their impact on the gravity field through forward modelling of the mass transfer. The spectral content of the estimated gravity changes induced by a simulated large-scale landslide event is estimated for the known spatial resolution of the GRACE observations using wavelet multiresolution analysis. The results indicate that both the Agulhas slump and the Heart Mountain Landslide could have been detected by GRACE, resulting in {\\vert }0.4{\\vert } and {\\vert }0.18{\\vert } mGal change on GRACE solutions, respectively. The suggested methodology is further extended to the case studies of the submarine landslide in Tohoku, Japan, and the Grand Banks landslide in Newfoundland, Canada. The detectability of these events using GRACE solutions is assessed through their impact on the gravity field.

Automatic QRS complex detection algorithm designed for a novel wearable, wireless electrocardiogram recording device

DEFF Research Database (Denmark)

Saadi, Dorthe Bodholt; Egstrup, Kenneth; Branebjerg, Jens

2012-01-01

We have designed and optimized an automatic QRS complex detection algorithm for electrocardiogram (ECG) signals recorded with the DELTA ePatch platform. The algorithm is able to automatically switch between single-channel and multi-channel analysis mode. This preliminary study includes data from ...

A global satellite assisted precipitation climatology

Science.gov (United States)

Funk, Christopher C.; Verdin, Andrew P.; Michaelsen, Joel C.; Pedreros, Diego; Husak, Gregory J.; Peterson, P.

2015-01-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate

Intraesophageal pressure recording improves the detection of cough during multichannel intraluminal impedance testing in children.

Science.gov (United States)

Rosen, Rachel; Amirault, Janine; Giligan, Emily; Khatwa, Umakanth; Nurko, Samuel

2014-01-01

One of the primary reasons for referral for reflux testing is to correlate reflux events with symptoms such as cough. Adult studies have suggested that symptom recording is flawed and pediatricians feel this is an even more significant problem because there may be errors in both parental and patient reports. We hypothesize that intraesophageal pressure recording (IEPR) provides an objective method to identify coughs during reflux testing in children. We recruited 20 children undergoing multichannel intraluminal impedance with pH (pH-MII) testing for the evaluation of cough. We placed simultaneous intraesophageal pressure and pH-MII catheters. Tracings were blindly scored by 2 observers without knowledge of patient/parent symptom report. After the blinded scoring, patient/parent report of symptoms was recorded. Ninety-four percent of all coughs were detected by IEPR and only 48% of all coughs were reported by patients/parents. The mean time from the IEPR cough to the patient/parent cough was 11±16 seconds. Using IEPR as the criterion standard for the detection of cough, the sensitivity of patient report for the detection of cough is 46%. Using varying symptom windows because of the increased precision of IEPR, the number of patients with a positive symptom index could be reduced from 30% to 0%, preventing children from being falsely categorized as having reflux-related lung disease. Parental and patient symptom recording in children is inadequate for making the diagnosis of reflux-related lung disease. If patients undergo pH-MII testing for reflux-related cough, IEPR should become the new standard by which to correlate reflux with cough.

Modeling Earth Albedo for Satellites in Earth Orbit

DEFF Research Database (Denmark)

Bhanderi, Dan; Bak, Thomas

2005-01-01

Many satellite are influences by the Earthøs albedo, though very few model schemes exist.in order to predict this phenomenon. Earth albedo is often treated as noise, or ignored completely. When applying solar cells in the attitude hardware, Earth albedo can cause the attitude estimate to deviate...... with as much as 20 deg. Digital Sun sensors with Earth albedo correction in hardware exist, but are expensive. In addition, albedo estimates are necessary in thermal calculations and power budgets. We present a modeling scheme base4d on Eartht reflectance, measured by NASA's Total Ozone Mapping Spectrometer......, in which the Earth Probe Satellite has recorded reflectivity data daily since mid 1996. The mean of these data can be used to calculate the Earth albedo given the positions of the satellite and the Sun. Our results show that the albedo varies highly with the solar angle to the satellite's field of view...

Planning and Scheduling for Fleets of Earth Observing Satellites

Science.gov (United States)

Frank, Jeremy; Jonsson, Ari; Morris, Robert; Smith, David E.; Norvig, Peter (Technical Monitor)

2001-01-01

We address the problem of scheduling observations for a collection of earth observing satellites. This scheduling task is a difficult optimization problem, potentially involving many satellites, hundreds of requests, constraints on when and how to service each request, and resources such as instruments, recording devices, transmitters, and ground stations. High-fidelity models are required to ensure the validity of schedules; at the same time, the size and complexity of the problem makes it unlikely that systematic optimization search methods will be able to solve them in a reasonable time. This paper presents a constraint-based approach to solving the Earth Observing Satellites (EOS) scheduling problem, and proposes a stochastic heuristic search method for solving it.

Satellite Sounder Observations of Contrasting Tropospheric Moisture Transport Regimes: Saharan Air Layers, Hadley Cells, and Atmospheric Rivers

Energy Technology Data Exchange (ETDEWEB)

Nalli, Nicholas R.; Barnet, Christopher D.; Reale, Tony; Liu, Quanhua; Morris, Vernon R.; Spackman, J. Ryan; Joseph, Everette; Tan, Changyi; Sun, Bomin; Tilley, Frank; Leung, L. Ruby; Wolfe, Daniel

2016-12-01

This paper examines the performance of satellite sounder atmospheric vertical moisture proles (AVMP) under tropospheric conditions encompassing moisture contrasts driven by convection and advection transport mechanisms, specifically Atlantic Ocean Saharan air layers (SALs) and Pacific Ocean moisture conveyer belts (MCBs) commonly referred to as atmospheric rivers (ARs), both of these being mesoscale to synoptic meteorological phenomena within the vicinity of subtropical Hadley subsidence zones. Operational AVMP environmental data records retrieved from the Suomi National Polar-orbiting Partnership (SNPP) NOAA-Unique Combined Atmospheric Processing System (NUCAPS) are collocated with dedicated radiosonde observations (RAOBs) obtained from ocean-based intensive field campaigns; these RAOBs provide uniquely independent correlative truth data not assimilated into numerical weather prediction models for satellite sounder validation over open ocean. Using these marine-based data, we empirically assess the performance of the operational NUCAPS AVMP product for detecting and resolving these tropospheric moisture features over otherwise RAOB-sparse regions.

Eyes in the sky: a comparative spatial analysis of aerial and satellite surveillance of east coast Canadian oil pollution

Energy Technology Data Exchange (ETDEWEB)

Lieske, David J. [Mount Allison University (Canada)], email: dlieske@mta.ca; Mahoney, Matthew [Environment Canada (Canada); Wilhelm, Sabina I. [Canadian Wildlife Service, Environment Canada (Canada); Weir, Laurie [Marine and Ice Services, Meteorological Service of Canada, Environment Canada (Canada); O' Hara, Patrick [Canadian Wildlife Service, Institute of Ocean Science (canada)

2011-07-01

This study offers an insight into three different oil spill detection schemes used in Canadian waters: visually unaided aerial surveillance, SLAR-assisted aerial surveillance, and RADARSAT-based image processing. The main purpose of this study is to compare the effectiveness of these schemes with respect to spill surveillance methodology, and to make recommendations for future planning techniques. In order to quantify the surveillance capacity of each method, flight paths had to be generated, followed by calculating oil loading. Flight paths were generated manually from images and records for the first approach, while this information was extracted from digitalized records for the second and third approaches. Results showed that SLAR technology increased the efficiency of NASP aircraft in spill detection by increasing the area surveyed and by its not having to rely on naked-eye spotting of the spills. Moreover, ISTOP widened the aircraft coverage range due to its satellite-based imagery, which can operate at night as well as in daylight.

Homogeneity testing of the global ESA CCI multi-satellite soil moisture climate data record

Science.gov (United States)

Preimesberger, Wolfgang; Su, Chun-Hsu; Gruber, Alexander; Dorigo, Wouter

2017-04-01

ESA's Climate Change Initiative (CCI) creates a global, long-term data record by merging multiple available earth observation products with the goal to provide a product for climate studies, trend analysis, and risk assessments. The blending of soil moisture (SM) time series derived from different active and passive remote sensing instruments with varying sensor characteristics, such as microwave frequency, signal polarization or radiometric accuracy, could potentially lead to inhomogeneities in the merged long-term data series, undercutting the usefulness of the product. To detect the spatio-temporal extent of contiguous periods without inhomogeneities as well as subsequently minimizing their negative impact on the data records, different relative homogeneity tests (namely Fligner-Killeen test of homogeneity of variances and Wilcoxon rank-sums test) are implemented and tested on the combined active-passive ESA CCI SM data set. Inhomogeneities are detected by comparing the data against reference data from in-situ data from ISMN, and model-based estimates from GLDAS-Noah and MERRA-Land. Inhomogeneity testing is performed over the ESA CCI SM data time frame of 38 years (from 1978 to 2015), on a global quarter-degree grid and with regard to six alterations in the combination of observation systems used in the data blending process. This study describes and explains observed variations in the spatial and temporal patterns of inhomogeneities in the combined products. Besides we proposes methodologies for measuring and reducing the impact of inhomogeneities on trends derived from the ESA CCI SM data set, and suggest the use of inhomogeneity-corrected data for future trend studies. This study is supported by the European Union's FP7 EartH2Observe "Global Earth Observation for Integrated Water Resource Assessment" project (grant agreement number 331 603608).

Significance of satellite sign and spot sign in predicting hematoma expansion in spontaneous intracerebral hemorrhage.

Science.gov (United States)

Yu, Zhiyuan; Zheng, Jun; Ali, Hasan; Guo, Rui; Li, Mou; Wang, Xiaoze; Ma, Lu; Li, Hao; You, Chao

2017-11-01

Hematoma expansion is related to poor outcome in spontaneous intracerebral hemorrhage (ICH). Recently, a non-enhanced computed tomography (CT) based finding, termed the 'satellite sign', was reported to be a novel predictor for poor outcome in spontaneous ICH. However, it is still unclear whether the presence of the satellite sign is related to hematoma expansion. Initial computed tomography angiography (CTA) was conducted within 6h after ictus. Satellite sign on non-enhanced CT and spot sign on CTA were detected by two independent reviewers. The sensitivity and specificity of both satellite sign and spot sign were calculated. Receiver-operator analysis was conducted to evaluate their predictive accuracy for hematoma expansion. This study included 153 patients. Satellite sign was detected in 58 (37.91%) patients and spot sign was detected in 38 (24.84%) patients. Among 37 patients with hematoma expansion, 22 (59.46%) had satellite sign and 23 (62.16%) had spot sign. The sensitivity and specificity of satellite sign for prediction of hematoma expansion were 59.46% and 68.97%, respectively. The sensitivity and specificity of spot sign were 62.16% and 87.07%, respectively. The area under the curve (AUC) of satellite sign was 0.642 and the AUC of spot sign was 0.746. (P=0.157) CONCLUSION: Our results suggest that the satellite sign is an independent predictor for hematoma expansion in spontaneous ICH. Although spot sign has the higher predictive accuracy, satellite sign is still an acceptable predictor for hematoma expansion when CTA is unavailable. Copyright © 2017 Elsevier B.V. All rights reserved.

Water Quality Monitoring by Satellite

Science.gov (United States)

Journal of Chemical Education, 2004

2004-01-01

The availability of abundant water resources in the Upper Midwest of the United States is nullified by their contamination through heavy commercial and industrial activities. Scientists have taken the responsibility of detecting the water quality of these resources through remote-sensing satellites to develop a wide-ranging water purification plan…

Advancing the capabilities of reservoir remote sensing by leveraging multi-source satellite data

Science.gov (United States)

Gao, H.; Zhang, S.; Zhao, G.; Li, Y.

2017-12-01

With a total global capacity of more than 6000 km3, reservoirs play a key role in the hydrological cycle and in water resources management. However, essential reservoir data (e.g., elevation, storage, and evaporation loss) are usually not shared at a large scale. While satellite remote sensing offers a unique opportunity for monitoring large reservoirs from space, the commonly used radar altimeters can only detect storage variations of about 15% of global lakes at a repeat period of 10 days or longer. To advance the capabilities of reservoir sensing, we developed a series of algorithms geared towards generating long term reservoir records at improved spatial coverage, and at improved temporal resolution. To this goal, observations are leveraged from multiple satellite sensors, which include radar/laser altimeters, imagers, and passive microwave radiometers. In South Asia, we demonstrate that reservoir storage can be estimated under all-weather conditions at a 4 day time step, with the total capacity of monitored reservoirs increased to 45%. Within the Continuous United States, a first Landsat based evaporation loss dataset was developed (containing 204 reservoirs) from 1984 to 2011. The evaporation trends of these reservoirs are identified and the causes are analyzed. All of these algorithms and products were validated with gauge observations. Future satellite missions, which will make significant contributions to monitoring global reservoirs, are also discussed.

A hierarchical model for estimating the spatial distribution and abundance of animals detected by continuous-time recorders.

Directory of Open Access Journals (Sweden)

Robert M Dorazio

Full Text Available Several spatial capture-recapture (SCR models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data.We developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data.Our approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species distribution model, even in

A Comprehensive Training Data Set for the Development of Satellite-Based Volcanic Ash Detection Algorithms

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Schmidl, Marius

2017-04-01

We present a comprehensive training data set covering a large range of atmospheric conditions, including disperse volcanic ash and desert dust layers. These data sets contain all information required for the development of volcanic ash detection algorithms based on artificial neural networks, urgently needed since volcanic ash in the airspace is a major concern of aviation safety authorities. Selected parts of the data are used to train the volcanic ash detection algorithm VADUGS. They contain atmospheric and surface-related quantities as well as the corresponding simulated satellite data for the channels in the infrared spectral range of the SEVIRI instrument on board MSG-2. To get realistic results, ECMWF, IASI-based, and GEOS-Chem data are used to calculate all parameters describing the environment, whereas the software package libRadtran is used to perform radiative transfer simulations returning the brightness temperatures for each atmospheric state. As optical properties are a prerequisite for radiative simulations accounting for aerosol layers, the development also included the computation of optical properties for a set of different aerosol types from different sources. A description of the developed software and the used methods is given, besides an overview of the resulting data sets.

a Fuzzy Automatic CAR Detection Method Based on High Resolution Satellite Imagery and Geodesic Morphology

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Zarrinpanjeh, N.; Dadrassjavan, F.

2017-09-01

Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

Future development of IR thermovision weather satellite equipment

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Listratov, A. V.

1974-01-01

The self radiation of the surface being viewed is used for image synthesis in IR thermovision equipment. The installation of such equipment aboard weather satellites makes it possible to obtain cloud cover pictures of the earth's surface in a complete orbit, regardless of the illumination conditions, and also provides quantitative information on the underlying surface temperature and cloud top height. Such equipment is used successfully aboard the Soviet satellites of the Meteor system, and experimentally on the American satellites of the Nimbus series. With regard to surface resolution, the present-day IR weather satellite equipment is inferior to the television equipment. This is due primarily to the comparatively low detectivity of the IR detectors used. While IR equipment has several fundamental advantages in comparison with the conventional television equipment, the problem arises of determining the possibility for future development of weather satellite IR thermovision equipment. Criteria are examined for evaluating the quality of IR.

Do asteroids have satellites

International Nuclear Information System (INIS)

Weidenschilling, S.J.; Paolicchi, P.; Zappala, V.

1989-01-01

A substantial body of indirect evidence suggests that some asteroids have satelities, although none has been detected unambiguously. Collisions between asteroids provide physically plausible mechanisms for the production of binaries, but these operate with low probability; only a small minority of asteroids are likely to have satellites. The abundance of binary asteroids can constrain the collisional history of the entire belt population. The allowed angular momentum of binaries and their rate of tidal evolution limit separations to no more than a few tens of the primary's radii. Their expected properties are consistent with failure to detect them by current imaging techniques

Features of High-Latitude Ionospheric Irregularities Development as Revealed by Ground-Based GPS Observations, Satellite-Borne GPS Observations and Satellite In Situ Measurements over the Territory of Russia during the Geomagnetic Storm on March 17-18, 2015

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Zakharenkova, I. E.; Cherniak, Iu. V.; Shagimuratov, I. I.; Klimenko, M. V.

2018-01-01

The dynamic picture of the response of the high- and mid-latitude ionosphere to the strong geomagnetic disturbances on March 17-18, 2015, has been studied with ground-based and satellite observations, mainly, by transionospheric measurements of delays of GPS (Global Positioning System) signals. The advantages of the joint use of ground-based GPS measurements and GPS measurements on board of the Swarm Low-Earth-Orbit satellite mission for monitoring of the appearance of ionospheric irregularities over the territory of Russia are shown for the first time. The results of analysis of ground-based and space-borne GPS observations, as well as satellite, in situ measurements, revealed large-scale ionospheric plasma irregularities observed over the territory of Russia in the latitude range of 50°-85° N during the main phase of the geomagnetic storm. The most intense ionospheric irregularities were detected in the auroral zone and in the region of the main ionospheric trough (MIT). It has been found that sharp changes in the phase of the carrier frequency of the navigation signal from all tracked satellites were recorded at all GPS stations located to the North from 55° MLAT. The development of a deep MIT was related to dynamic processes in the subauroral ionosphere, in particular, with electric fields of the intense subauroral polarization stream. Analysis of the electron and ion density values obtained by instruments on board of the Swarm and DMSP satellites showed that the zone of highly structured auroral ionosphere extended at least to heights of 850-900 km.

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

Science.gov (United States)

Khodaverdi zahraee, N.; Rastiveis, H.

2017-09-01

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

Evaluating Surface Radiation Fluxes Observed From Satellites in the Southeastern Pacific Ocean

Science.gov (United States)

Pinker, R. T.; Zhang, B.; Weller, R. A.; Chen, W.

2018-03-01

This study is focused on evaluation of current satellite and reanalysis estimates of surface radiative fluxes in a climatically important region. It uses unique observations from the STRATUS Ocean Reference Station buoy in a region of persistent marine stratus clouds 1,500 km off northern Chile during 2000-2012. The study shows that current satellite estimates are in better agreement with buoy observations than model outputs at a daily time scale and that satellite data depict well the observed annual cycle in both shortwave and longwave surface radiative fluxes. Also, buoy and satellite estimates do not show any significant trend over the period of overlap or any interannual variability. This verifies the stability and reliability of the satellite data and should make them useful to examine El Niño-Southern Oscillation variability influences on surface radiative fluxes at the STRATUS site for longer periods for which satellite record is available.

Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning.

Directory of Open Access Journals (Sweden)

Erico N de Souza

Full Text Available A key challenge in contemporary ecology and conservation is the accurate tracking of the spatial distribution of various human impacts, such as fishing. While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas. Better understanding of the behavior of the global fishing fleets is required in order to prioritize and enforce fisheries management and conservation measures worldwide. Satellite-based Automatic Information Systems (S-AIS are now commonly installed on most ocean-going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. Here we present approaches to identify fishing activity from S-AIS data for three dominant fishing gear types: trawl, longline and purse seine. Using a large dataset containing worldwide fishing vessel tracks from 2011-2015, we developed three methods to detect and map fishing activities: for trawlers we produced a Hidden Markov Model (HMM using vessel speed as observation variable. For longliners we have designed a Data Mining (DM approach using an algorithm inspired from studies on animal movement. For purse seiners a multi-layered filtering strategy based on vessel speed and operation time was implemented. Validation against expert-labeled datasets showed average detection accuracies of 83% for trawler and longliner, and 97% for purse seiner. Our study represents the first comprehensive approach to detect and identify potential fishing behavior for three major gear types operating on a global scale. We hope that this work will enable new efforts to assess the spatial and temporal distribution of global fishing effort and make global fisheries activities transparent to ocean scientists, managers and the public.

Upwelling Dynamic Based on Satellite and INDESO Data in the Flores Sea

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Kurniawan, Reski; Suriamihardja, D. A.; Hamzah Assegaf, Alimuddin

2018-03-01

Upwelling phenomenon is crucial to be forecasted, mainly concerning the information of potential fishery areas. Utilization of calibrated model for recorded upwelling such as INDESO gives benefit for historical result up to the present time. The aim of this study is to estimate areas and seasons of upwelling occurrences in the Flores Sea using data assimilation of satellite and modeling result. This study uses sea surface temperature, chlorophyll-a data from level 3 of MODIS image and sea surface height from satellite Jason-2 monthly for three years (2014-2016) and INDESO model data for sea surface temperature, sea surface height, and chlorophyll-a daily for three years (2014-2016). The upwelling is indicated by declining of sea surface temperature, sea surface height and increasing of chlorophyll-a. Verification is conducted by comparing the model result with recorded MODIS satellite image. The result shows that the area of southern Makassar Strait having occurrences of upwelling phenomenon every year starting in June, extended to July and August. The strongest upwelling occurred in 2015 covering more or less the area of 23,000 km2. The relation of monthly data of satellite has significantly correlated with daily data of INDESO model

First satellite measurements of chemical changes in coincidence with sprite activity

Science.gov (United States)

Arnone, Enrico; São Sabbas, Fernanda; Kero, Antti; Soula, Serge; Carlotti, Massimo; Chanrion, Olivier; Dinelli, Bianca Maria; Papandrea, Enzo; Castelli, Elisa; Neubert, Torsten

2010-05-01

The last twenty years have seen the discovery of electric discharges in the Earth's atmosphere above thunderstorms, the so-called sprites and jets. It has been suggested that they impact the atmospheric chemistry and possibly affect the ozone layer through their repeated occurrence. Whereas theoretical studies and laboratory experiments suggest enhancement of such gasses as nitrogen oxides by up to hundreds of percent within sprites, a definitive detection of their chemical effects have to date been unsuccessful. In this paper, we report on the first measurements of atmospheric chemical perturbations recorded in coincidence with sprite activity. A striking event occurred on 25 August 2003 when the MIPAS spectrometer onboard the Envisat satellite recorded spectroscopic measurements soon after a sequence of 11 sprites observed above Corsica (France) by Eurosprite ground facilities (details of the convective system are discussed in a companion paper by São Sabbas et al.). The measurements show an enhancement of ambient nitrous oxide by 80% at 52 km altitude in the region above the parent thunderstorm. The recorded chemical changes imply sprites can exert significant modification of the atmospheric chemistry at a regional scale, confirming model and laboratory predictions of sprite-chemistry, and requiring a new estimate of their global impact. The results of the analysis and their implications are discussed.

Improving the automated detection of refugee/IDP dwellings using the multispectral bands of the WorldView-2 satellite

Science.gov (United States)

Kemper, Thomas; Gueguen, Lionel; Soille, Pierre

2012-06-01

The enumeration of the population remains a critical task in the management of refugee/IDP camps. Analysis of very high spatial resolution satellite data proofed to be an efficient and secure approach for the estimation of dwellings and the monitoring of the camp over time. In this paper we propose a new methodology for the automated extraction of features based on differential morphological decomposition segmentation for feature extraction and interactive training sample selection from the max-tree and min-tree structures. This feature extraction methodology is tested on a WorldView-2 scene of an IDP camp in Darfur Sudan. Special emphasis is given to the additional available bands of the WorldView-2 sensor. The results obtained show that the interactive image information tool is performing very well by tuning the feature extraction to the local conditions. The analysis of different spectral subsets shows that it is possible to obtain good results already with an RGB combination, but by increasing the number of spectral bands the detection of dwellings becomes more accurate. Best results were obtained using all eight bands of WorldView-2 satellite.

Online Visualization and Analysis of Global Half-Hourly Infrared Satellite Data

Science.gov (United States)

Liu, Zhong; Ostrenga, Dana; Leptoukh, Gregory

2011-01-01

nfrared (IR) images (approximately 11-micron channel) recorded by satellite sensors have been widely used in weather forecasting, research, and classroom education since the Nimbus program. Unlike visible images, IR imagery can reveal cloud features without sunlight illumination; therefore, they can be used to monitor weather phenomena day and night. With geostationary satellites deployed around the globe, it is possible to monitor weather events 24/7 at a temporal resolution that polar-orbiting satellites cannot achieve at the present time. When IR data from multiple geostationary satellites are merged to form a single product--also known as a merged product--it allows for observing weather on a global scale. Its high temporal resolution (e.g., every half hour) also makes it an ideal ancillary dataset for supporting other satellite missions, such as the Tropical Rainfall Measuring Mission (TRMM), etc., by providing additional background information about weather system evolution.

Satellite altimetry in sea ice regions - detecting open water for estimating sea surface heights

Science.gov (United States)

Müller, Felix L.; Dettmering, Denise; Bosch, Wolfgang

2017-04-01

The Greenland Sea and the Farm Strait are transporting sea ice from the central Arctic ocean southwards. They are covered by a dynamic changing sea ice layer with significant influences on the Earth climate system. Between the sea ice there exist various sized open water areas known as leads, straight lined open water areas, and polynyas exhibiting a circular shape. Identifying these leads by satellite altimetry enables the extraction of sea surface height information. Analyzing the radar echoes, also called waveforms, provides information on the surface backscatter characteristics. For example waveforms reflected by calm water have a very narrow and single-peaked shape. Waveforms reflected by sea ice show more variability due to diffuse scattering. Here we analyze altimeter waveforms from different conventional pulse-limited satellite altimeters to separate open water and sea ice waveforms. An unsupervised classification approach employing partitional clustering algorithms such as K-medoids and memory-based classification methods such as K-nearest neighbor is used. The classification is based on six parameters derived from the waveform's shape, for example the maximum power or the peak's width. The open-water detection is quantitatively compared to SAR images processed while accounting for sea ice motion. The classification results are used to derive information about the temporal evolution of sea ice extent and sea surface heights. They allow to provide evidence on climate change relevant influences as for example Arctic sea level rise due to enhanced melting rates of Greenland's glaciers and an increasing fresh water influx into the Arctic ocean. Additionally, the sea ice cover extent analyzed over a long-time period provides an important indicator for a globally changing climate system.

Noise detection in heart sound recordings.

Science.gov (United States)

Zia, Mohammad K; Griffel, Benjamin; Fridman, Vladimir; Saponieri, Cesare; Semmlow, John L

2011-01-01

Coronary artery disease (CAD) is the leading cause of death in the United States. Although progression of CAD can be controlled using drugs and diet, it is usually detected in advanced stages when invasive treatment is required. Current methods to detect CAD are invasive and/or costly, hence not suitable as a regular screening tool to detect CAD in early stages. Currently, we are developing a noninvasive and cost-effective system to detect CAD using the acoustic approach. This method identifies sounds generated by turbulent flow through partially narrowed coronary arteries to detect CAD. The limiting factor of this method is sensitivity to noises commonly encountered in the clinical setting. Because the CAD sounds are faint, these noises can easily obscure the CAD sounds and make detection impossible. In this paper, we propose a method to detect and eliminate noise encountered in the clinical setting using a reference channel. We show that our method is effective in detecting noise, which is essential to the success of the acoustic approach.

Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Stratospheric Water and Ozone Satellite Homogenized (SWOOSH) data set is a merged record of stratospheric ozone and water vapor measurements taken by a number of...

The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors

Science.gov (United States)

Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.

2016-12-01

Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection

Automatic bad channel detection in intracranial electroencephalographic recordings using ensemble machine learning.

Science.gov (United States)

Tuyisenge, Viateur; Trebaul, Lena; Bhattacharjee, Manik; Chanteloup-Forêt, Blandine; Saubat-Guigui, Carole; Mîndruţă, Ioana; Rheims, Sylvain; Maillard, Louis; Kahane, Philippe; Taussig, Delphine; David, Olivier

2018-03-01

Intracranial electroencephalographic (iEEG) recordings contain "bad channels", which show non-neuronal signals. Here, we developed a new method that automatically detects iEEG bad channels using machine learning of seven signal features. The features quantified signals' variance, spatial-temporal correlation and nonlinear properties. Because the number of bad channels is usually much lower than the number of good channels, we implemented an ensemble bagging classifier known to be optimal in terms of stability and predictive accuracy for datasets with imbalanced class distributions. This method was applied on stereo-electroencephalographic (SEEG) signals recording during low frequency stimulations performed in 206 patients from 5 clinical centers. We found that the classification accuracy was extremely good: It increased with the number of subjects used to train the classifier and reached a plateau at 99.77% for 110 subjects. The classification performance was thus not impacted by the multicentric nature of data. The proposed method to automatically detect bad channels demonstrated convincing results and can be envisaged to be used on larger datasets for automatic quality control of iEEG data. This is the first method proposed to classify bad channels in iEEG and should allow to improve the data selection when reviewing iEEG signals. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Influence of satellite alerts on the efficiency of aircraft monitoring of maritime oil pollution in German waters

Science.gov (United States)

Helmke, Peer; Baschek, Björn; Hunsänger, Thomas; Kranz, Susanne

2014-10-01

For detecting accidental and illegal pollution by mineral oil, the German exclusive economic zone and surrounding waters have been monitored by aircraft operationally for more than 25 years. Aircraft surveillance uses predominantly Side-Looking-Airborne-Radar for visualization of the effect of oil to smoothen capillary waves. A set of near range sensors complements the remote sensing data available for the human operator to classify the detected features as "mineral oil", "natural phenomenon", "other substance" or "unknown" pollution. Today, as an add-on to aerial surveillance, the German Central Command of Maritime Emergencies uses the operational satellite service "CleanSeaNet" provided by the European Maritime Safety Agency: Radar satellite data is analyzed in near real time and alerts of potential pollution are sent out. Shortly after receiving the results, aircraft surveillance flights are started by the 3rd Naval Air Wing and the locations of the satellite alerts are checked. Thus, a combined system of satellite and aerial surveillance is in place. The German Federal Institute of Hydrology, BfG, has access to the data of the pollution events detected during these flights and the corresponding meta-data of flights and satellite images. In this work, a period of two years of this data is analyzed. The probability to detect pollutions is evaluated for (A) flight missions associated with satellite scenes, and (B) additional flights performed independently from satellite scenes. Thus, the influence of satellite alerts on the efficiency of aircraft monitoring is investigated. Coverage and coordination of the monitoring by aircraft and satellite are assessed and implications for the operational monitoring are discussed.

Robust detection of heart beats in multimodal records using slope- and peak-sensitive band-pass filters.

Science.gov (United States)

Pangerc, Urška; Jager, Franc

2015-08-01

In this work, we present the development, architecture and evaluation of a new and robust heart beat detector in multimodal records. The detector uses electrocardiogram (ECG) signals, and/or pulsatile (P) signals, such as: blood pressure, artery blood pressure and pulmonary artery pressure, if present. The base approach behind the architecture of the detector is collecting signal energy (differentiating and low-pass filtering, squaring, integrating). To calculate the detection and noise functions, simple and fast slope- and peak-sensitive band-pass digital filters were designed. By using morphological smoothing, the detection functions were further improved and noise intervals were estimated. The detector looks for possible pacemaker heart rate patterns and repairs the ECG signals and detection functions. Heart beats are detected in each of the ECG and P signals in two steps: a repetitive learning phase and a follow-up detecting phase. The detected heart beat positions from the ECG signals are merged into a single stream of detected ECG heart beat positions. The merged ECG heart beat positions and detected heart beat positions from the P signals are verified for their regularity regarding the expected heart rate. The detected heart beat positions of a P signal with the best match to the merged ECG heart beat positions are selected for mapping into the noise and no-signal intervals of the record. The overall evaluation scores in terms of average sensitivity and positive predictive values obtained on databases that are freely available on the Physionet website were as follows: the MIT-BIH Arrhythmia database (99.91%), the MGH/MF Waveform database (95.14%), the augmented training set of the follow-up phase of the PhysioNet/Computing in Cardiology Challenge 2014 (97.67%), and the Challenge test set (93.64%).

A new 25 years Arctic Sea level record from ESA satellites

DEFF Research Database (Denmark)

Andersen, Ole Baltazar; Cheng, Yongcun; Knudsen, Per

The Arctic is an extremely challenging region for the use of remote sensing for ocean studies. One is the fact that despite 25 years of altimetry only very limited sea level observations exists in the interior of the Arctic Ocean. However, with Cryosat-2 SAR altimetry the situation is changing...... the ESA GOCE mission we are now able to derive a mean dynamic topography of the Arctic Ocean with unprecedented accuracy to constrain the ocean circulation. We present both a new estimation of the mean ocean circulation and new estimates of large scale sea level changes based on satellite data and perform...

Satellite Image Classification of Building Damages Using Airborne and Satellite Image Samples in a Deep Learning Approach

Science.gov (United States)

Duarte, D.; Nex, F.; Kerle, N.; Vosselman, G.

2018-05-01

The localization and detailed assessment of damaged buildings after a disastrous event is of utmost importance to guide response operations, recovery tasks or for insurance purposes. Several remote sensing platforms and sensors are currently used for the manual detection of building damages. However, there is an overall interest in the use of automated methods to perform this task, regardless of the used platform. Owing to its synoptic coverage and predictable availability, satellite imagery is currently used as input for the identification of building damages by the International Charter, as well as the Copernicus Emergency Management Service for the production of damage grading and reference maps. Recently proposed methods to perform image classification of building damages rely on convolutional neural networks (CNN). These are usually trained with only satellite image samples in a binary classification problem, however the number of samples derived from these images is often limited, affecting the quality of the classification results. The use of up/down-sampling image samples during the training of a CNN, has demonstrated to improve several image recognition tasks in remote sensing. However, it is currently unclear if this multi resolution information can also be captured from images with different spatial resolutions like satellite and airborne imagery (from both manned and unmanned platforms). In this paper, a CNN framework using residual connections and dilated convolutions is used considering both manned and unmanned aerial image samples to perform the satellite image classification of building damages. Three network configurations, trained with multi-resolution image samples are compared against two benchmark networks where only satellite image samples are used. Combining feature maps generated from airborne and satellite image samples, and refining these using only the satellite image samples, improved nearly 4 % the overall satellite image

A Geometry-Based Cycle Slip Detection and Repair Method with Time-Differenced Carrier Phase (TDCP for a Single Frequency Global Position System (GPS + BeiDou Navigation Satellite System (BDS Receiver

Directory of Open Access Journals (Sweden)

Chuang Qian

2016-12-01

Full Text Available As the field of high-precision applications based on carriers continues to expand, the development of low-cost, small, modular receivers and their application in diverse scenarios and situations with complex data quality has increased the requirements of carrier-phase data preprocessing. A new geometry-based cycle slip detection and repair method based on Global Position System (GPS + BeiDou Navigation Satellite System (BDS is proposed. The method uses a Time-differenced Carrier Phase (TDCP model, which eliminates the Inner-System Bias (ISB between GPS and BDS, and it is conducive to the effective combination of GPS and BDS. It avoids the interference of the noise of the pseudo-range with cycle slip detection, while the cycle slips are preserved as integers. This method does not limit the receiver frequency number, and it is applicable to single-frequency data. The process is divided into two steps to detect and repair cycle slip. The first step is cycle slip detection, using the Improved Local Analysis Method (ILAM to find satellites that have cycle slips; The second step is to repair the cycle slips, including estimating the float solution of changes in ambiguities at the satellites that have cycle slips with the least squares method and the integer solution of the cycle slips by rounding. In the process of rounding, in addition to the success probability, a decimal test is carried out to validate the result. Finally, experiments with filed test data are carried out to prove the effectiveness of this method. The results show that the detectable cycle slips number with GPS + BDS is much greater than that with GPS. The method can also detect the non-integer outliers while fixing the cycle slip. The maximum decimal bias in repair is less than that with GPS. It implies that this method takes full advantages of multi-system.

Epigenetic reprogramming of pericentromeric satellite DNA in premalignant and malignant lesions

DEFF Research Database (Denmark)

Brückmann, Nadine Heidi; Pedersen, Christina Bøg; Ditzel, Henrik Jørn

2018-01-01

on pericentromeric satellites in primary melanocytes. This suggests that polycomb bodies form in cancer cells with global DNA demethylation to control the stability of pericentromeric satellite DNA. These results reveal a novel epigenetic perturbation specific to premalignant and malignant cells thatmaybe used...... as an early diagnostic marker for detection of precancerous changes and a new therapeutic entry point. Implications: Pericentromeric satellite DNA is epigenetically reprogrammed into polycomb bodies as a premalignant event with implications for transcriptional activity and genomic stability. Mol Cancer Res...

Acoustic occurrence detection of a newly recorded Indo-Pacific humpback dolphin population in waters southwest of Hainan Island, China.

Science.gov (United States)

Dong, Lijun; Liu, Mingming; Dong, Jianchen; Li, Songhai

2017-11-01

In 2014, Indo-Pacific humpback dolphins were recorded for the first time in waters southwest of Hainan Island, China. In this paper, the temporal occurrence of Indo-Pacific humpback dolphins in this region was detected by stationary passive acoustic monitoring. During the 130-day observation period (from January to July 2016), 1969 click trains produced by Indo-Pacific humpback dolphins were identified, and 262 ten-minute recording bins contained echolocation click trains of dolphins, of which 70.9% were at night and 29.1% were during the day. A diurnal rhythm with a nighttime peak in acoustic detections was found. Passive acoustic detections indicated that the Indo-Pacific humpback dolphins frequently occurred in this area and were detected mainly at night. This information may be relevant to conservation efforts for these dolphins in the near future.

Satellite remote sensing at the Sea Empress spill - a help or potential hindrance

International Nuclear Information System (INIS)

Lunel, T.

1996-01-01

The application of satellite images in an oil spill response operation, was discussed. The oil movement and satellite imagery of the Sea Empress spill was described in detail. There were large discrepancies in the predictions by Radarsat satellite imagery and the actual oil movement, and in this instance, the satellite imagery proved to be more of a distraction than a useful tool. It was suggested that the greatest potential for satellite imagery is in detecting smaller releases of oil, such as from illegal tank washings, ballast waters from ships, or operational malfunctions at oil rigs. 4 refs., 10 figs

Detection of Interictal Epileptiform Discharges Using Signal Envelope Distribution Modelling: Application to Epileptic and Non-Epileptic Intracranial Recordings

Czech Academy of Sciences Publication Activity Database

Janča, R.; Ježdík, P.; Čmejla, R.; Tomášek, M.; Worrell, G. A.; Stead, M.; Wagenaar, J.; Jefferys, J. G. R.; Kršek, P.; Komárek, V.; Jiruška, Přemysl; Marusič, P.

2015-01-01

Roč. 28, č. 1 (2015), s. 172-183 ISSN 0896-0267 Grant - others:GA Mzd(CZ) NT11460 Institutional support: RVO:67985823 Keywords : spike detection * interictal epileptiform discharges * intracranial recording * automatic detection * Hilbert transform * principal component analysis Subject RIV: FH - Neurology Impact factor: 3.727, year: 2015

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

Science.gov (United States)

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

2014-12-01

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

A FUZZY AUTOMATIC CAR DETECTION METHOD BASED ON HIGH RESOLUTION SATELLITE IMAGERY AND GEODESIC MORPHOLOGY

Directory of Open Access Journals (Sweden)

N. Zarrinpanjeh

2017-09-01

Full Text Available Automatic car detection and recognition from aerial and satellite images is mostly practiced for the purpose of easy and fast traffic monitoring in cities and rural areas where direct approaches are proved to be costly and inefficient. Towards the goal of automatic car detection and in parallel with many other published solutions, in this paper, morphological operators and specifically Geodesic dilation are studied and applied on GeoEye-1 images to extract car items in accordance with available vector maps. The results of Geodesic dilation are then segmented and labeled to generate primitive car items to be introduced to a fuzzy decision making system, to be verified. The verification is performed inspecting major and minor axes of each region and the orientations of the cars with respect to the road direction. The proposed method is implemented and tested using GeoEye-1 pansharpen imagery. Generating the results it is observed that the proposed method is successful according to overall accuracy of 83%. It is also concluded that the results are sensitive to the quality of available vector map and to overcome the shortcomings of this method, it is recommended to consider spectral information in the process of hypothesis verification.

Quantifying the clear-sky bias of satellite-derived infrared LST

Science.gov (United States)

Ermida, S. L.; Trigo, I. F.; DaCamara, C.

2017-12-01

Land surface temperature (LST) is one of the most relevant parameters when addressing the physical processes that take place at the surface of the Earth. Satellite data are particularly appropriate for measuring LST over the globe with high temporal resolution. Remote-sensed LST estimation from space-borne sensors has been systematically performed over the Globe for nearly 3 decades and geostationary LST climate data records are now available. The retrieval of LST from satellite observations generally relies on measurements in the thermal infrared (IR) window. Although there is a large number of IR sensors on-board geostationary satellites and polar orbiters suitable for LST retrievals with different temporal and spatial resolutions, the use of IR observations limits LST estimates to clear sky conditions. As a consequence, climate studies based on IR LST are likely to be affected by the restriction of LST data to cloudless conditions. However, such "clear sky bias" has never been quantified and, therefore, the actual impact of relying only on clear sky data is still to be determined. On the other hand, an "all-weather" global LST database may be set up based on passive microwave (MW) measurements which are much less affected by clouds. An 8-year record of all-weather MW LST is here used to quantify the clear-sky bias of IR LST at global scale based on MW observations performed by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) onboard NASA's Aqua satellite. Selection of clear-sky and cloudy pixels is based on information derived from measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the same satellite.

User Validation of VIIRS Satellite Imagery

Directory of Open Access Journals (Sweden)

Don Hillger

2015-12-01

Full Text Available Visible/Infrared Imaging Radiometer Suite (VIIRS Imagery from the Suomi National Polar-orbiting Partnership (S-NPP satellite is the finest spatial resolution (375 m multi-spectral imagery of any operational meteorological satellite to date. The Imagery environmental data record (EDR has been designated as a Key Performance Parameter (KPP for VIIRS, meaning that its performance is vital to the success of a series of Joint Polar Satellite System (JPSS satellites that will carry this instrument. Because VIIRS covers the high-latitude and Polar Regions especially well via overlapping swaths from adjacent orbits, the Alaska theatre in particular benefits from VIIRS more than lower-latitude regions. While there are no requirements that specifically address the quality of the EDR Imagery aside from the VIIRS SDR performance requirements, the value of VIIRS Imagery to operational users is an important consideration in the Cal/Val process. As such, engaging a wide diversity of users constitutes a vital part of the Imagery validation strategy. The best possible image quality is of utmost importance. This paper summarizes the Imagery Cal/Val Team’s quality assessment in this context. Since users are a vital component to the validation of VIIRS Imagery, specific examples of VIIRS imagery applied to operational needs are presented as an integral part of the post-checkout Imagery validation.

Remote sensing for oil spill detection and response

International Nuclear Information System (INIS)

Engelhardt, F.R.

1999-01-01

This paper focuses on the use of remote sensing for marine oil spill detection and response. The surveillance and monitoring of discharges, and the main elements of effective surveillance are discussed. Tactical emergency response and the requirements for selecting a suitable remote sensing approach, airborne remote sensing systems, and the integration of satellite and airborne imaging are examined. Specifications of satellite surveillance systems potentially usable for oil spill detection, and specifications of airborne remote sensing systems suitable for oil spill detection, monitoring and supplemental actions are tabulated, and a schema of integrated satellite-airborne remote sensing (ISARS) is presented. (UK)

Saturn satellites

International Nuclear Information System (INIS)

Ruskol, E.L.

1981-01-01

The characteristics of the Saturn satellites are discussed. The satellites close to Saturn - Janus, Mimas, Enceladus, Tethys, Dione and Rhea - rotate along the circular orbits. High reflectivity is attributed to them, and the density of the satellites is 1 g/cm 3 . Titan is one of the biggest Saturn satellites. Titan has atmosphere many times more powerful than that of Mars. The Titan atmosphere is a peculiar medium with a unique methane and hydrogen distribution in the whole Solar system. The external satellites - Hyperion, Japetus and Phoebe - are poorly investigated. Neither satellite substance density, nor their composition are known. The experimental data on the Saturn rings obtained on the ''Pioneer-11'' and ''Voyager-1'' satellites are presented [ru

The SUMO Ship Detector Algorithm for Satellite Radar Images

Directory of Open Access Journals (Sweden)

Harm Greidanus

2017-03-01

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

Satellite monitoring of remote volcanoes improves study efforts in Alaska

Science.gov (United States)

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

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

Using limnological and optical knowledge to detect discharges from nuclear facilities - Potential application of satellite imagery for international safeguards

International Nuclear Information System (INIS)

Borstad, G.; Truong, Q.S. Bob; Keeffe, R.; Baines, P.; Staenz, K.; Neville, R.

2001-01-01

Previous work carried out under the Canadian Safeguards Support Program, has shown that thermal imagery from the American Landsat satellites could be used to detect the cooling water discharges, and could therefore be used to verify the operational status of nuclear facilities. In some images, thermal plumes could be easily detected in single band imagery with no mathematical manipulation and little image enhancement because there was a very strong thermal contrast between the effluent and the receiving water. However, for certain situations such as discharges into well mixed conditions (cold water and violent tides) the thermal plume may be more subtle. We show here that the visible bands of Landsat and IKONOS images often contain additional information, and that the thermal signature of a discharge from a nuclear facility is not the only signal available to describe its operation. This paper introduces some important hydrological phenomena that govern the biological and physical organization of water bodies, and discusses some basic concepts of marine and aquatic optics that are relevant to the safeguards problem. Using image analysis techniques that have been used widely in ocean optics work and in applications in the mapping and monitoring of water quality, we have re-analyzed data that were obtained under a joint project between various Canadian government departments. We present a preliminary examination of imagery from both satellite multispectral and aircraft hyperspectral sensors, and discuss methods to extract information that could be useful in the detection and verification of declared or undeclared nuclear activities. In one example of an IKONOS image of the Canadian Bruce Nuclear Generating Facility, simple enhancement techniques failed to find any plume other than a small jet visible in the surface wave field. With knowledge of limnology, oceanography and aquatic optics, we have been able to separate and remove the surface reflection, and detect a

Detection of Coccolithophore Blooms in Ocean Color Satellite Imagery: a Generalized Approach for Use with Multiple Sensors

Science.gov (United States)

Moore, Timothy; Dowell, Mark; Franz, Bryan A.

2012-01-01

A generalized coccolithophore bloom classifier has been developed for use with ocean color imagery. The bloom classifier was developed using extracted satellite reflectance data from SeaWiFS images screened by the default bloom detection mask. In the current application, we extend the optical water type (OWT) classification scheme by adding a new coccolithophore bloom class formed from these extracted reflectances. Based on an in situ coccolithophore data set from the North Atlantic, the detection levels with the new scheme were between 1,500 and 1,800 coccolithophore cellsmL and 43,000 and 78,000 lithsmL. The detected bloom area using the OWT method was an average of 1.75 times greater than the default bloom detector based on a collection of SeaWiFS 1 km imagery. The versatility of the scheme is shown with SeaWiFS, MODIS Aqua, CZCS and MERIS imagery at the 1 km scale. The OWT scheme was applied to the daily global SeaWiFS imagery mission data set (years 19972010). Based on our results, average annual coccolithophore bloom area was more than two times greater in the southern hemisphere compared to the northern hemi- sphere with values of 2.00 106 km2 and 0.75 106 km2, respectively. The new algorithm detects larger bloom areas in the Southern Ocean compared to the default algorithm, and our revised global annual average of 2.75106 km2 is dominated by contributions from the Southern Ocean.

Real-time monitoring of seismic data using satellite telemetry

Directory of Open Access Journals (Sweden)

L. Merucci

1997-06-01

Full Text Available This article describes the ARGO Satellite Seismic Network (ARGO SSN as a reliable system for monitoring, collection, visualisation and analysis of seismic and geophysical low-frequency data, The satellite digital telemetry system is composed of peripheral geophysical stations, a centraI communications node (master sta- tion located in CentraI Italy, and a data collection and processing centre located at ING (Istituto Nazionale di Geofisica, Rome. The task of the peripheral stations is to digitalise and send via satellite the geophysical data collected by the various sensors to the master station. The master station receives the data and forwards them via satellite to the ING in Rome; it also performs alI the monitoring functions of satellite communications. At the data collection and processing centre of ING, the data are received and analysed in real time, the seismic events are identified and recorded, the low-frequency geophysical data are stored. In addition, the generaI sta- tus of the satellite network and of each peripheral station connected, is monitored. The procedure for analysjs of acquired seismic signals allows the automatic calculation of local magnitude and duration magnitude The communication and data exchange between the seismic networks of Greece, Spain and Italy is the fruit of a recent development in the field of technology of satellite transmission of ARGO SSN (project of European Community "Southern Europe Network for Analysis of Seismic Data"

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data.

Science.gov (United States)

Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

A new framework for analysing automated acoustic species-detection data: occupancy estimation and optimization of recordings post-processing

Science.gov (United States)

Chambert, Thierry A.; Waddle, J. Hardin; Miller, David A.W.; Walls, Susan; Nichols, James D.

2018-01-01

The development and use of automated species-detection technologies, such as acoustic recorders, for monitoring wildlife are rapidly expanding. Automated classification algorithms provide a cost- and time-effective means to process information-rich data, but often at the cost of additional detection errors. Appropriate methods are necessary to analyse such data while dealing with the different types of detection errors.We developed a hierarchical modelling framework for estimating species occupancy from automated species-detection data. We explore design and optimization of data post-processing procedures to account for detection errors and generate accurate estimates. Our proposed method accounts for both imperfect detection and false positive errors and utilizes information about both occurrence and abundance of detections to improve estimation.Using simulations, we show that our method provides much more accurate estimates than models ignoring the abundance of detections. The same findings are reached when we apply the methods to two real datasets on North American frogs surveyed with acoustic recorders.When false positives occur, estimator accuracy can be improved when a subset of detections produced by the classification algorithm is post-validated by a human observer. We use simulations to investigate the relationship between accuracy and effort spent on post-validation, and found that very accurate occupancy estimates can be obtained with as little as 1% of data being validated.Automated monitoring of wildlife provides opportunity and challenges. Our methods for analysing automated species-detection data help to meet key challenges unique to these data and will prove useful for many wildlife monitoring programs.

Strengthening IAEA safeguards using high-resolution commercial satellite imagery

International Nuclear Information System (INIS)

Zhang Hui

2001-01-01

Full text: In May 1997, the IAEA Board of Governors adopted the Additional Safeguards Protocol to improve its ability to detect the undeclared production of fissile material. This new strengthened safeguards system has opened the door for the IAEA to use of all types of information, including the potential use of commercial satellite imagery. We have therefore been investigating the feasibility of strengthening IAEA safeguards using commercial satellite imagery. Based on our analysis on a number of one-meter resolution IKONOS satellite images of military nuclear production facilities at nuclear states including Russia, China, India, Pakistan and Israel, we found that the new high-resolution commercial satellite imagery would play a new and valuable role in strengthening IAEA safeguards. Since 1999, images with a resolution of one meter have been available commercially from Space Imaging's IKONOS satellite. One-meter images from other companies are expected to enter the market soon. Although still an order of magnitude less capable than military imaging satellites, the capabilities of these new high-resolution commercial satellites are good enough to detect and identify the major visible characteristics of nuclear production facilities and sites. Unlike the classified spy satellite photos limited to few countries, the commercial satellite imagery is commercially available to anyone who wants to purchase it. Therefore, the new commercial satellite open a new chance that each state, international organizations, and non-governmental groups could use the commercial images to play a more proactive role in monitoring the nuclear activities in related countries and verifying the compliance of non-proliferation agreements. This could help galvanize support for intensified efforts to slow the pace of nuclear proliferation. To produce fissile materials (plutonium and highly enriched uranium) for weapons, a country would operate dedicated plutonium-production reactors and the

A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data

International Nuclear Information System (INIS)

Elvidge, Ch. D.; Erwin, E. H.; Ziskin, D.; Baugh, K. E.; Tuttle, B. T.; Ghosh, T.; Tuttle, B. T.; Ghosh, T.; Pack, D. W.; Zhizhin, M.

2009-01-01

We have produced annual estimates of national and global gas flaring and gas flaring efficiency from 1994 through 2008 using low light imaging data acquired by the Defense Meteorological Satellite Program (DMSP). Gas flaring is a widely used practice for the disposal of associated gas in oil production and processing facilities where there is insufficient infrastructure for utilization of the gas (primarily methane). Improved utilization of the gas is key to reducing global carbon emissions to the atmosphere. The DMSP estimates of flared gas volume are based on a calibration developed with a pooled set of reported national gas flaring volumes and data from individual flares. Flaring efficiency was calculated as the volume of flared gas per barrel of crude oil produced. Global gas flaring has remained largely stable over the past fifteen years, in the range of 140 to 170 billion cubic meters (BCM). Global flaring efficiency was in the seven to eight cubic meters per barrel from 1994 to 2005 and declined to 5.6 m 3 per barrel by 2008. The 2008 gas flaring estimate of 139 BCM represents 21% of the natural gas consumption of the USA with a potential retail market value of 68 billions USD. The 2008 flaring added more than 278 million metric tons of carbon dioxide equivalent (CO 2e ) into the atmosphere. The DMSP estimated gas flaring volumes indicate that global gas flaring has declined by 19% since 2005, led by gas flaring reductions in Russia and Nigeria, the two countries with the highest gas flaring levels. The flaring efficiency of both Russia and Nigeria improved from 2005 to 2008, suggesting that the reductions in gas flaring are likely the result of either improved utilization of the gas, reinjection, or direct venting of gas into the atmosphere, although the effect of uncertainties in the satellite data cannot be ruled out. It is anticipated that the capability to estimate gas flaring volumes based on satellite data will spur improved utilization of gas that

Global ocean tides through assimilation of oceanographic and altimeter satellite data in a hydrodynamic model

Science.gov (United States)

Leprovost, Christian; Mazzega, P.; Vincent, P.

1991-01-01

Ocean tides must be considered in many scientific disciplines: astronomy, oceanography, geodesy, geophysics, meteorology, and space technologies. Progress in each of these disciplines leads to the need for greater knowledge and more precise predictions of the ocean tide contribution. This is particularly true of satellite altimetry. On one side, the present and future satellite altimetry missions provide and will supply new data that will contribute to the improvement of the present ocean tide solutions. On the other side, tidal corrections included in the Geophysical Data Records must be determined with the maximum possible accuracy. The valuable results obtained with satellite altimeter data thus far have not been penalized by the insufficiencies of the present ocean tide predictions included in the geophysical data records (GDR's) because the oceanic processes investigated have shorter wavelengths than the error field of the tidal predictions, so that the residual errors of the tidal corrections are absorbed in the empirical tilt and bias corrections of the satellite orbit. For future applications to large-scale oceanic phenomena, however, it will no longer be possible to ignore these insufficiencies.

Landuse change detection in a surface coal mine area using multi-temporal high resolution satellite images

Energy Technology Data Exchange (ETDEWEB)

Demirel, N.; Duzgun, S.; Kemal Emil, M. [Middle East Technical Univ., Ankara (Turkey). Dept. of Mining Engineering

2010-07-01

Changes in the landcover and landuse of a mine area can be caused by surface mining activities, exploitation of ore and stripping and dumping overburden. In order to identify the long-term impacts of mining on the environment and land cover, these changes must be continuously monitored. A facility to regularly observe the progress of surface mining and reclamation is important for effective enforcement of mining and environmental regulations. Remote sensing provides a powerful tool to obtain rigorous data and reduce the need for time-consuming and expensive field measurements. The purpose of this study was to conduct post classification change detection for identifying, quantifying, and analyzing the spatial response of landscape due to surface lignite coal mining activities in Goynuk, Bolu, Turkey, from 2004 to 2008. The paper presented the research algorithm which involved acquiring multi temporal high resolution satellite data; preprocessing the data; performing image classification using maximum likelihood classification algorithm and performing accuracy assessment on the classification results; performing post classification change detection algorithm; and analyzing the results. Specifically, the paper discussed the study area, data and methodology, and image preprocessing using radiometric correction. Image classification and change detection were also discussed. It was concluded that the mine and dump area decreased by 192.5 ha from 2004 to 2008 and was caused by the diminishing reserves in the area and decline in the required production. 5 refs., 2 tabs., 4 figs.

Evaluation of Latent Heat Flux Fields from Satellites and Models during SEMAPHORE.

Science.gov (United States)

Bourras, Denis; Liu, W. Timothy; Eymard, Laurence; Tang, Wenqing

2003-02-01

Latent heat fluxes were derived from satellite observations in the region of Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale (SEMAPHORE), which was conducted near the Azores islands in the North Atlantic Ocean in autumn of 1993. The satellite fluxes were compared with output fields of two atmospheric circulation models and in situ measurements. The rms error of the instantaneous satellite fluxes is between 35 and 40 W m-2 and the bias is 60-85 W m-2. The large bias is mainly attributed to a bias in satellite-derived atmospheric humidity and is related to the particular shape of the vertical humidity profiles during SEMAPHORE. The bias in humidity implies that the range of estimated fluxes is smaller than the range of ship fluxes, by 34%-38%. The rms errors for fluxes from models are 30-35 W m-2, and the biases are smaller than the biases in satellite fluxes (14-18 W m-2). Two case studies suggest that the satellites detect horizontal gradients of wind speed and specific humidity if the magnitude of the gradients exceeds a detection threshold, which is 1.27 g kg-1 (100 km)-1 for specific humidity and between 0.35 and 0.82 m s-1 (30 km)-1 for wind speed. In contrast, the accuracy of the spatial gradients of bulk variables from models always varies as a function of the location and number of assimilated observations. A comparison between monthly fluxes from satellites and models reveals that satellite-derived flux anomaly fields are consistent with reanalyzed fields, whereas operational model products lack part of the mesoscale structures present in the satellite fields.

The Chinese FY-1 Meteorological Satellite Application in Observation on Oceanic Environment

Science.gov (United States)

Weimin, S.

meteorological satellite is stated in this paper. exploration of the ocean resources has been a very important question of global strategy in the world. The exploration of the ocean resources includes following items: Making full use of oceanic resources and space, protecting oceanic environment. to observe the ocean is by using of satellite. In 1978, US successfully launched the first ocean observation satellite in the world --- Sea Satellite. It develops ancient oceanography in to advanced space-oceanography. FY-1 B and FY- IC respectively. High quality data were acquired at home and abroad. FY-1 is Chinese meteorological satellite, but with 0.43 ~ 0.48 μm ,0.48 ~ 0.53 μm and 0.53 ~ 0.58 μm three ocean color channels, actually it is a multipurpose remote sensing satellite of meteorology and oceanography. FY-1 satellite's capability of observation on ocean partly, thus the application field is expanded and the value is increased. With the addition of oceanic channels on FY-1, the design of the satellite is changed from the original with meteorological observation as its main purpose into remote sensing satellite possessing capability of observing meteorology and ocean as well. Thus, the social and economic benefit of FY-1 is increased. the social and economic benefit of the development of the satellite is the key technique in the system design of the satellite. technically feasible but also save the funds in researching and manufacturing of the satellite, quicken the tempo of researching and manufacturing satellite. the scanning radiometer for FY-1 is conducted an aviation experiment over Chinese ocean. This experiment was of vital importance to the addition of oceanic observation channel on FY-1. FY-1 oceanic channels design to be correct. detecting ocean color. This is the unique character of Chinese FY-1 meteorological satellite. meteorological remote sensing channel on FY-1 to form detecting capability of three visible channels: red, yellow and blue

Continuity of Climate Data Records derived from Microwave Observations

Science.gov (United States)

Mears, C. A.; Wentz, F. J.; Brewer, M.; Meissner, T.; Ricciardulli, L.

2017-12-01

Remote Sensing Systems (www.remss.com) has been producing and distributing microwave climate data products from microwave imagers (SSMI, TMI, AMSR, WindSat, GMI, Aquarius, SMAP) over the global oceans since the launch of the first SSMI in 1987. Interest in these data products has been significant as researchers around the world have downloaded the approximate equivalent of 1 million satellite years of processed data. Users, including NASA, NOAA, US National Laboratories, US Navy, UK Met, ECMWF, JAXA, JMA, CMC, the Australian Bureau of Meteorology, as well as many hundreds of other agencies and universities routinely access these microwave data products. The quality of these data records has increased as more observations have become available and inter-calibration techniques have improved. The impending end of missions for WindSat, AMSR-2, and the remaining SSMIs will have significant impact on the quality and continuity of long term microwave climate data records. In addition to the problem of reduced numbers of observations, there is a real danger of losing overlapping observations. Simultaneous operation of satellites, especially when the observations are at similar local crossing times, provides a significant benefit in the effort to inter-calibrate satellites to yield accurate and stable long-term records. The end of WindSat and AMSR-2 will leave us without microwave SSTs in cold water, as there will be no microwave imagers with C-band channels. Microwave SSTs have a crucial advantage over IR SSTs, which is not able to measure SST in clouds or if aerosols are present. The gap in ocean wind vectors will be somewhat mitigated as the European ASCAT C-band scatterometer mission on MetOp is continuing. Nonetheless, the anticipated cease of several microwave satellite radiometers retrieving ocean winds in the coming years will lead to a significant gap in temporal coverage. Atmospheric water vapor, cloud liquid water, and rain rate are all important climate

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data

Science.gov (United States)

Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Objective. Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. Approach. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. Main results. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. Significance. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

Using satellite fire detection to calibrate components of the fire weather index system in Malaysia and Indonesia.

Science.gov (United States)

Dymond, Caren C; Field, Robert D; Roswintiarti, Orbita; Guswanto

2005-04-01

Vegetation fires have become an increasing problem in tropical environments as a consequence of socioeconomic pressures and subsequent land-use change. In response, fire management systems are being developed. This study set out to determine the relationships between two aspects of the fire problems in western Indonesia and Malaysia, and two components of the Canadian Forest Fire Weather Index System. The study resulted in a new method for calibrating components of fire danger rating systems based on satellite fire detection (hotspot) data. Once the climate was accounted for, a problematic number of fires were related to high levels of the Fine Fuel Moisture Code. The relationship between climate, Fine Fuel Moisture Code, and hotspot occurrence was used to calibrate Fire Occurrence Potential classes where low accounted for 3% of the fires from 1994 to 2000, moderate accounted for 25%, high 26%, and extreme 38%. Further problems arise when there are large clusters of fires burning that may consume valuable land or produce local smoke pollution. Once the climate was taken into account, the hotspot load (number and size of clusters of hotspots) was related to the Fire Weather Index. The relationship between climate, Fire Weather Index, and hotspot load was used to calibrate Fire Load Potential classes. Low Fire Load Potential conditions (75% of an average year) corresponded with 24% of the hotspot clusters, which had an average size of 30% of the largest cluster. In contrast, extreme Fire Load Potential conditions (1% of an average year) corresponded with 30% of the hotspot clusters, which had an average size of 58% of the maximum. Both Fire Occurrence Potential and Fire Load Potential calibrations were successfully validated with data from 2001. This study showed that when ground measurements are not available, fire statistics derived from satellite fire detection archives can be reliably used for calibration. More importantly, as a result of this work, Malaysia and

Crowdsourcing seizure detection: algorithm development and validation on human implanted device recordings.

Science.gov (United States)

Baldassano, Steven N; Brinkmann, Benjamin H; Ung, Hoameng; Blevins, Tyler; Conrad, Erin C; Leyde, Kent; Cook, Mark J; Khambhati, Ankit N; Wagenaar, Joost B; Worrell, Gregory A; Litt, Brian

2017-06-01

There exist significant clinical and basic research needs for accurate, automated seizure detection algorithms. These algorithms have translational potential in responsive neurostimulation devices and in automatic parsing of continuous intracranial electroencephalography data. An important barrier to developing accurate, validated algorithms for seizure detection is limited access to high-quality, expertly annotated seizure data from prolonged recordings. To overcome this, we hosted a kaggle.com competition to crowdsource the development of seizure detection algorithms using intracranial electroencephalography from canines and humans with epilepsy. The top three performing algorithms from the contest were then validated on out-of-sample patient data including standard clinical data and continuous ambulatory human data obtained over several years using the implantable NeuroVista seizure advisory system. Two hundred teams of data scientists from all over the world participated in the kaggle.com competition. The top performing teams submitted highly accurate algorithms with consistent performance in the out-of-sample validation study. The performance of these seizure detection algorithms, achieved using freely available code and data, sets a new reproducible benchmark for personalized seizure detection. We have also shared a 'plug and play' pipeline to allow other researchers to easily use these algorithms on their own datasets. The success of this competition demonstrates how sharing code and high quality data results in the creation of powerful translational tools with significant potential to impact patient care. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

Science.gov (United States)

Hester, David Barry

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

Isolation, culture and biological characteristics of multipotent porcine skeletal muscle satellite cells.

Science.gov (United States)

Yang, Jinjuan; Liu, Hao; Wang, Kunfu; Li, Lu; Yuan, Hongyi; Liu, Xueting; Liu, Yingjie; Guan, Weijun

2017-12-01

Skeletal muscle has a huge regenerative potential for postnatal muscle growth and repair, which mainly depends on a kind of muscle progenitor cell population, called satellite cell. Nowadays, the majority of satellite cells were obtained from human, mouse, rat and other animals but rarely from pig. In this article, the porcine skeletal muscle satellite cells were isolated and cultured in vitro. The expression of surface markers of satellite cells was detected by immunofluorescence and RT-PCR assays. The differentiation capacity was assessed by inducing satellite cells into adipocytes, myoblasts and osteoblasts. The results showed that satellite cells isolated from porcine tibialis anterior were subcultured up to 12 passages and were positive for Pax7, Myod, c-Met, desmin, PCNA and NANOG but were negative for Myogenin. Satellite cells were also induced to differentiate into adipocytes, osteoblasts and myoblasts, respectively. These findings indicated that porcine satellite cells possess similar biological characteristics of stem cells, which may provide theoretical basis and experimental evidence for potential therapeutic application in the treatment of dystrophic muscle and other muscle injuries.

Development of an algorithm for heartbeats detection and classification in Holter records based on temporal and morphological features

International Nuclear Information System (INIS)

García, A; Romano, H; Laciar, E; Correa, R

2011-01-01

In this work a detection and classification algorithm for heartbeats analysis in Holter records was developed. First, a QRS complexes detector was implemented and their temporal and morphological characteristics were extracted. A vector was built with these features; this vector is the input of the classification module, based on discriminant analysis. The beats were classified in three groups: Premature Ventricular Contraction beat (PVC), Atrial Premature Contraction beat (APC) and Normal Beat (NB). These beat categories represent the most important groups of commercial Holter systems. The developed algorithms were evaluated in 76 ECG records of two validated open-access databases 'arrhythmias MIT BIH database' and M IT BIH supraventricular arrhythmias database . A total of 166343 beats were detected and analyzed, where the QRS detection algorithm provides a sensitivity of 99.69 % and a positive predictive value of 99.84 %. The classification stage gives sensitivities of 97.17% for NB, 97.67% for PCV and 92.78% for APC.

Detection of Traveling Ionospheric Disturbances (TIDs) from various man-made sources using Global Navigation Satellite System (GNSS)

Science.gov (United States)

Helmboldt, J.; Park, J.; von Frese, R. R. B.; Grejner-Brzezinska, D. A.

2016-12-01

Traveling ionospheric disturbance (TID) is generated by various sources and detectable by observing the spatial and temporal change of electron contents in the ionosphere. This study focused on detecting and analyzing TIDs generated by acoustic-gravity waves from man-made events including underground nuclear explosions (UNEs), mine collapses, mine blasts, and large chemical explosions (LCEs) using Global Navigation Satellite System (GNSS). In this study we selected different types of events for case study which covers two US and three North Korean UNEs, two large US mine collapses, three large US mine blasts, and a LCE in northern China and a second LCE at the Nevada Test Site. In most cases, we successfully detected the TIDs as array signatures from the multiple nearby GNSS stations. The array-based TID signatures from these studies were found to yield event-appropriate TID propagation speeds ranging from about a few hundred m/s to roughly a km/s. In addition, the event TID waveforms, and propagation angles and directions were established. The TID waveforms and the maximum angle between each event and the IPP of its TID with the longest travel distance from the source may help differentiate UNEs and LCEs, but the uneven distributions of the observing GNSS stations complicates these results. Thus, further analysis is required of the utility of the apertures of event signatures in the ionosphere for discriminating these events. In general, the results of this study show the potential utility of GNSS observations for detecting and mapping the ionospheric signatures of large-energy anthropological explosions and subsurface collapses.

Satellite precipitation estimation over the Tibetan Plateau

Science.gov (United States)

Porcu, F.; Gjoka, U.

2012-04-01

Precipitation characteristics over the Tibetan Plateau are very little known, given the scarcity of reliable and widely distributed ground observation, thus the satellite approach is a valuable choice for large scale precipitation analysis and hydrological cycle studies. However,the satellite perspective undergoes various shortcomings at the different wavelengths used in atmospheric remote sensing. In the microwave spectrum often the high soil emissivity masks or hides the atmospheric signal upwelling from light-moderate precipitation layers, while low and relatively thin precipitating clouds are not well detected in the visible-infrared, because of their low contrast with cold and bright (if snow covered) background. In this work an IR-based, statistical rainfall estimation technique is trained and applied over the Tibetan Plateau hydrological basin to retrive precipitation intensity at different spatial and temporal scales. The technique is based on a simple artificial neural network scheme trained with two supervised training sets assembled for monsoon season and for the rest of the year. For the monsoon season (estimated from June to September), the ground radar precipitation data for few case studies are used to build the training set: four days in summer 2009 are considered. For the rest of the year, CloudSat-CPR derived snowfall rate has been used as reference precipitation data, following the Kulie and Bennartz (2009) algorithm. METEOSAT-7 infrared channels radiance (at 6.7 and 11 micometers) and derived local variability features (such as local standard deviation and local average) are used as input and the actual rainrate is obtained as output for each satellite slot, every 30 minutes on the satellite grid. The satellite rainrate maps for three years (2008-2010) are computed and compared with available global precipitation products (such as C-MORPH and TMPA products) and with other techniques applied to the Plateau area: similarities and differences are

Applications of Satellite Observations of Tropospheric Composition

Science.gov (United States)

Monks, Paul S.; Beirle, Steffen

A striking feature of the field of tropospheric composition is the sheer number of chemical species that have been detected and measured with satellite instruments. The measurements have found application both in atmospheric chemistry itself, providing evidence, for example, of unexpected cryochemistry in the Arctic regions, and also in environmental monitoring with, for example, the observed growth in NO2 emissions over eastern Asia. Chapter 8 gives an overview of the utility of satellite observations for measuring tropospheric composition, dealing with each of the many compounds seen in detail. A comprehensive compound by compound table of the many studies performed is a most useful feature.

Green leaf phenology at Landsat resolution: scaling from the plot to satellite

Science.gov (United States)

Fisher, J. I.; Mustard, J. F.; Vadeboncour, M.

2005-12-01

Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In particular, while most phenological patterns and trends derived from satellites appear realistic and coherent, they may not reflect spatial and temporal patterns at the plot level. An obvious explanation is the drastic scale difference from plot-level to most satellite observations. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r2 = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (example, our results indicate that deciduous forests in the Providence, RI metropolitan area leaf out 5-7 days earlier than comparable rural areas. In preliminary work, we validated the Landsat-derived metrics with similar analyses of MODIS and AVHRR, and demonstrate that aggregating diverse local phenologies into coarse grids may convolute interpretations. Despite these complications, the platform-independent curve-fit methodology may be extended across platforms and field data. The methodologically consistent approach, in tandem with Landsat data, allows us to effectively scale

Visual attitude propagation for small satellites

Science.gov (United States)

Rawashdeh, Samir A.

As electronics become smaller and more capable, it has become possible to conduct meaningful and sophisticated satellite missions in a small form factor. However, the capability of small satellites and the range of possible applications are limited by the capabilities of several technologies, including attitude determination and control systems. This dissertation evaluates the use of image-based visual attitude propagation as a compliment or alternative to other attitude determination technologies that are suitable for miniature satellites. The concept lies in using miniature cameras to track image features across frames and extracting the underlying rotation. The problem of visual attitude propagation as a small satellite attitude determination system is addressed from several aspects: related work, algorithm design, hardware and performance evaluation, possible applications, and on-orbit experimentation. These areas of consideration reflect the organization of this dissertation. A "stellar gyroscope" is developed, which is a visual star-based attitude propagator that uses relative motion of stars in an imager's field of view to infer the attitude changes. The device generates spacecraft relative attitude estimates in three degrees of freedom. Algorithms to perform the star detection, correspondence, and attitude propagation are presented. The Random Sample Consensus (RANSAC) approach is applied to the correspondence problem to successfully pair stars across frames while mitigating falsepositive and false-negative star detections. This approach provides tolerance to the noise levels expected in using miniature optics and no baffling, and the noise caused by radiation dose on orbit. The hardware design and algorithms are validated using test images of the night sky. The application of the stellar gyroscope as part of a CubeSat attitude determination and control system is described. The stellar gyroscope is used to augment a MEMS gyroscope attitude propagation

On the use of Satellite Remote Sensing and GIS to detect NO2 in the Troposphere

DEFF Research Database (Denmark)

Nielsen, Søren Zebitz

2012-01-01

This thesis studies the spatio-temporal patterns and trends in NO2 air pollution over Denmark using the satellite remote sensing product OMNO2e retrieved from the OMI instrument on the NASA AURA satellite. These data are related to in situ measurements of NO2 made at four rural and four urban...... measured in Denmark. Trends in the data are assessed and declining trends are seen over several European cities, whereas no significant trends are found in the Danish area. The mean distribution of NO2 from the satellite data is also used to evaluate the NOx emission inventory....

Spatial and Temporal Homogeneity of Solar Surface Irradiance across Satellite Generations

Directory of Open Access Journals (Sweden)

Rebekka Posselt

2011-05-01

Full Text Available Solar surface irradiance (SIS is an essential variable in the radiation budget of the Earth. Climate data records (CDR’s of SIS are required for climate monitoring, for climate model evaluation and for solar energy applications. A 23 year long (1983–2005 continuous and validated SIS CDR based on the visible channel (0.45–1 μm of the MVIRI instruments onboard the first generation of Meteosat satellites has recently been generated using a climate version of the well established Heliosat method. This version of the Heliosat method includes a newly developed self-calibration algorithm and an improved algorithm to determine the clear sky reflection. The climate Heliosat version is also applied to the visible narrow-band channels of SEVIRI onboard the Meteosat Second Generation Satellites (2004–present. The respective channels are observing the Earth in the wavelength region at about 0.6 μm and 0.8 μm. SIS values of the overlapping time period are used to analyse whether a homogeneous extension of the MVIRI CDR is possible with the SEVIRI narrowband channels. It is demonstrated that the spectral differences between the used visible channels leads to significant differences in the solar surface irradiance in specific regions. Especially, over vegetated areas the reflectance exhibits a high spectral dependency resulting in large differences in the retrieved SIS. The applied self-calibration method alone is not able to compensate the spectral differences of the channels. Furthermore, the extended range of the input values (satellite counts enhances the cloud detection of the SEVIRI instruments resulting in lower values for SIS, on average. Our findings have implications for the application of the Heliosat method to data from other geostationary satellites (e.g., GOES, GMS. They demonstrate the need for a careful analysis of the effect of spectral and technological differences in visible channels on the retrieved solar irradiance.

The effects of clouds on the detection of light signals from near-ground nuclear bursts at satellite

International Nuclear Information System (INIS)

Zhang Zhongshan; Zhang Enshan; Zhao Wenli; Gao Chunxia

2002-01-01

The effects of clouds on the detection of light signals from near-ground nuclear bursts are analysed quantitatively. The results indicate: the degree of the effect increasing with the growth of clouds optical thickness and satellite look angle; clouds lead really harmful effect in detectable signal intensity and precision of optical location, but degree of the effect is not great too. The enhancement of the photon optical paths by multiple scattering within the cloud will cause both a delay and a time-broadening of an impulsive light signal, and get 'lower and fat'; upward optical transmission of light through clouds is essentially the same as if there were no cloud present at all, when a point source is above the geometrical mid-plane of the cloud. And if the point source is below the mid-plane, then upward optical transmission of light through clods will be related closely to the distance of the source below the mid-plane. Given also some charts which evaluate conveniently degree of the effect due to clouds for the purpose of reference and use of a person of the same trade or occupation are given also

Self-Assembled Core-Satellite Gold Nanoparticle Networks for Ultrasensitive Detection of Chiral Molecules by Recognition Tunneling Current.

Science.gov (United States)

Zhang, Yuanchao; Liu, Jingquan; Li, Da; Dai, Xing; Yan, Fuhua; Conlan, Xavier A; Zhou, Ruhong; Barrow, Colin J; He, Jin; Wang, Xin; Yang, Wenrong

2016-05-24

Chirality sensing is a very challenging task. Here, we report a method for ultrasensitive detection of chiral molecule l/d-carnitine based on changes in the recognition tunneling current across self-assembled core-satellite gold nanoparticle (GNP) networks. The recognition tunneling technique has been demonstrated to work at the single molecule level where the binding between the reader molecules and the analytes in a nanojunction. This process was observed to generate a unique and sensitive change in tunneling current, which can be used to identify the analytes of interest. The molecular recognition mechanism between amino acid l-cysteine and l/d-carnitine has been studied with the aid of SERS. The different binding strength between homo- or heterochiral pairs can be effectively probed by the copper ion replacement fracture. The device resistance was measured before and after the sequential exposures to l/d-carnitine and copper ions. The normalized resistance change was found to be extremely sensitive to the chirality of carnitine molecule. The results suggested that a GNP networks device optimized for recognition tunneling was successfully built and that such a device can be used for ultrasensitive detection of chiral molecules.

Predictors of Arrhythmic Events Detected by Implantable Loop Recorders in Renal Transplant Candidates

Energy Technology Data Exchange (ETDEWEB)

Silva, Rodrigo Tavares; Martinelli Filho, Martino, E-mail: martino@cardiol.br; Peixoto, Giselle de Lima; Lima, José Jayme Galvão de; Siqueira, Sérgio Freitas de; Costa, Roberto; Gowdak, Luís Henrique Wolff [Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP (Brazil); Paula, Flávio Jota de [Unidade de Transplante Renal - Divisão de Urologia do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP (Brazil); Kalil Filho, Roberto; Ramires, José Antônio Franchini [Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP (Brazil)

2015-11-15

The recording of arrhythmic events (AE) in renal transplant candidates (RTCs) undergoing dialysis is limited by conventional electrocardiography. However, continuous cardiac rhythm monitoring seems to be more appropriate due to automatic detection of arrhythmia, but this method has not been used. We aimed to investigate the incidence and predictors of AE in RTCs using an implantable loop recorder (ILR). A prospective observational study conducted from June 2009 to January 2011 included 100 consecutive ambulatory RTCs who underwent ILR and were followed-up for at least 1 year. Multivariate logistic regression was applied to define predictors of AE. During a mean follow-up of 424 ± 127 days, AE could be detected in 98% of patients, and 92% had more than one type of arrhythmia, with most considered potentially not serious. Sustained atrial tachycardia and atrial fibrillation occurred in 7% and 13% of patients, respectively, and bradyarrhythmia and non-sustained or sustained ventricular tachycardia (VT) occurred in 25% and 57%, respectively. There were 18 deaths, of which 7 were sudden cardiac events: 3 bradyarrhythmias, 1 ventricular fibrillation, 1 myocardial infarction, and 2 undetermined. The presence of a long QTc (odds ratio [OR] = 7.28; 95% confidence interval [CI], 2.01–26.35; p = 0.002), and the duration of the PR interval (OR = 1.05; 95% CI, 1.02–1.08; p < 0.001) were independently associated with bradyarrhythmias. Left ventricular dilatation (LVD) was independently associated with non-sustained VT (OR = 2.83; 95% CI, 1.01–7.96; p = 0.041). In medium-term follow-up of RTCs, ILR helped detect a high incidence of AE, most of which did not have clinical relevance. The PR interval and presence of long QTc were predictive of bradyarrhythmias, whereas LVD was predictive of non-sustained VT.

Predictors of Arrhythmic Events Detected by Implantable Loop Recorders in Renal Transplant Candidates

Directory of Open Access Journals (Sweden)

Rodrigo Tavares Silva

2015-11-01

Full Text Available AbstractBackground:The recording of arrhythmic events (AE in renal transplant candidates (RTCs undergoing dialysis is limited by conventional electrocardiography. However, continuous cardiac rhythm monitoring seems to be more appropriate due to automatic detection of arrhythmia, but this method has not been used.Objective:We aimed to investigate the incidence and predictors of AE in RTCs using an implantable loop recorder (ILR.Methods:A prospective observational study conducted from June 2009 to January 2011 included 100 consecutive ambulatory RTCs who underwent ILR and were followed-up for at least 1 year. Multivariate logistic regression was applied to define predictors of AE.Results:During a mean follow-up of 424 ± 127 days, AE could be detected in 98% of patients, and 92% had more than one type of arrhythmia, with most considered potentially not serious. Sustained atrial tachycardia and atrial fibrillation occurred in 7% and 13% of patients, respectively, and bradyarrhythmia and non-sustained or sustained ventricular tachycardia (VT occurred in 25% and 57%, respectively. There were 18 deaths, of which 7 were sudden cardiac events: 3 bradyarrhythmias, 1 ventricular fibrillation, 1 myocardial infarction, and 2 undetermined. The presence of a long QTc (odds ratio [OR] = 7.28; 95% confidence interval [CI], 2.01–26.35; p = 0.002, and the duration of the PR interval (OR = 1.05; 95% CI, 1.02–1.08; p < 0.001 were independently associated with bradyarrhythmias. Left ventricular dilatation (LVD was independently associated with non-sustained VT (OR = 2.83; 95% CI, 1.01–7.96; p = 0.041.Conclusions:In medium-term follow-up of RTCs, ILR helped detect a high incidence of AE, most of which did not have clinical relevance. The PR interval and presence of long QTc were predictive of bradyarrhythmias, whereas LVD was predictive of non-sustained VT.

Predictors of Arrhythmic Events Detected by Implantable Loop Recorders in Renal Transplant Candidates

Science.gov (United States)

Silva, Rodrigo Tavares; Martinelli Filho, Martino; Peixoto, Giselle de Lima; de Lima, José Jayme Galvão; de Siqueira, Sérgio Freitas; Costa, Roberto; Gowdak, Luís Henrique Wolff; de Paula, Flávio Jota; Kalil Filho, Roberto; Ramires, José Antônio Franchini

2015-01-01

Background The recording of arrhythmic events (AE) in renal transplant candidates (RTCs) undergoing dialysis is limited by conventional electrocardiography. However, continuous cardiac rhythm monitoring seems to be more appropriate due to automatic detection of arrhythmia, but this method has not been used. Objective We aimed to investigate the incidence and predictors of AE in RTCs using an implantable loop recorder (ILR). Methods A prospective observational study conducted from June 2009 to January 2011 included 100 consecutive ambulatory RTCs who underwent ILR and were followed-up for at least 1 year. Multivariate logistic regression was applied to define predictors of AE. Results During a mean follow-up of 424 ± 127 days, AE could be detected in 98% of patients, and 92% had more than one type of arrhythmia, with most considered potentially not serious. Sustained atrial tachycardia and atrial fibrillation occurred in 7% and 13% of patients, respectively, and bradyarrhythmia and non-sustained or sustained ventricular tachycardia (VT) occurred in 25% and 57%, respectively. There were 18 deaths, of which 7 were sudden cardiac events: 3 bradyarrhythmias, 1 ventricular fibrillation, 1 myocardial infarction, and 2 undetermined. The presence of a long QTc (odds ratio [OR] = 7.28; 95% confidence interval [CI], 2.01–26.35; p = 0.002), and the duration of the PR interval (OR = 1.05; 95% CI, 1.02–1.08; p < 0.001) were independently associated with bradyarrhythmias. Left ventricular dilatation (LVD) was independently associated with non-sustained VT (OR = 2.83; 95% CI, 1.01–7.96; p = 0.041). Conclusions In medium-term follow-up of RTCs, ILR helped detect a high incidence of AE, most of which did not have clinical relevance. The PR interval and presence of long QTc were predictive of bradyarrhythmias, whereas LVD was predictive of non-sustained VT. PMID:26351983

Automatic Mosaicking of Satellite Imagery Considering the Clouds

Science.gov (United States)

Kang, Yifei; Pan, Li; Chen, Qi; Zhang, Tong; Zhang, Shasha; Liu, Zhang

2016-06-01

With the rapid development of high resolution remote sensing for earth observation technology, satellite imagery is widely used in the fields of resource investigation, environment protection, and agricultural research. Image mosaicking is an important part of satellite imagery production. However, the existence of clouds leads to lots of disadvantages for automatic image mosaicking, mainly in two aspects: 1) Image blurring may be caused during the process of image dodging, 2) Cloudy areas may be passed through by automatically generated seamlines. To address these problems, an automatic mosaicking method is proposed for cloudy satellite imagery in this paper. Firstly, modified Otsu thresholding and morphological processing are employed to extract cloudy areas and obtain the percentage of cloud cover. Then, cloud detection results are used to optimize the process of dodging and mosaicking. Thus, the mosaic image can be combined with more clear-sky areas instead of cloudy areas. Besides, clear-sky areas will be clear and distortionless. The Chinese GF-1 wide-field-of-view orthoimages are employed as experimental data. The performance of the proposed approach is evaluated in four aspects: the effect of cloud detection, the sharpness of clear-sky areas, the rationality of seamlines and efficiency. The evaluation results demonstrated that the mosaic image obtained by our method has fewer clouds, better internal color consistency and better visual clarity compared with that obtained by traditional method. The time consumed by the proposed method for 17 scenes of GF-1 orthoimages is within 4 hours on a desktop computer. The efficiency can meet the general production requirements for massive satellite imagery.

Analysis on the status of the application of satellite remote sensing technology to nuclear safeguards

International Nuclear Information System (INIS)

Tao Zhangsheng; Zhao Yingjun

2008-01-01

Based on the application status of satellite remote sensing technology to nuclear safeguards, advantage of satellite remote sensing technology is analyzed, main types of satellite image used in nuclear safeguards are elaborated and the main application of satellite images is regarded to detect, verify and monitor nuclear activities; verify additional protocol declaration and design information, support performing complementary access inspections; investigate alleged undeclared activities based on open source or the third party information. Application examples of satellite image in nuclear safeguards to analyze nuclear facilities by other countries, the ability of remote sensing technology in nuclear safeguards is discussed. (authors)

Passivity based nonlinear attitude control of the Rømer satellite

DEFF Research Database (Denmark)

Quottrup, Michael Melholt; Krogh-Sørensen, J.; Wisniewski, Rafal

This paper suggests nonlinear attitude control of the Danish satellite Rømer. This satellite will be designed to fulfil two scientific objectives: The observation of stellar oscillations and the detection and localisation of gamma-ray bursts. The satellite will be equipped with a tetrahedron...... configuration of Wide Angle Telescopes for Cosmic Hard x-rays (WATCH), that server the dual purpose of X-ray detectors and momentum wheels. By employing passivity theory it is shown, that the satellite is a passive system. This paper shows, that global asymptotic can be obtained with a passive and an imput...... and output strictly passive system in a feedback interconnection. It is demonstrated in a simulation study that the resultant control has a potential for on-board implementation in the acquistion phase, where global stabillity of the control law is vital...

CONTRIBUTION OF SATELLITE-BORN INFORMATION TO CLIMATE SCIENCE

Directory of Open Access Journals (Sweden)

MIKA J.

2015-03-01

Full Text Available Observed climate processes play important role in understanding the ongoing changes in the climate system. Our paper intends to present this cross-section of climate science illustrated by selected satellite images and diagrams in four parts. (i. Technical possibilities of the observations are briefly surveyed first. Many satellite platforms and devices started working in the 1980 and 1990s, definitely for climate purposes. (ii. Climate forcing factors and their radiation effects are comprehended, including direct observation of solar irradiance and volcanic aerosol concentration allowing us to compare natural factors to the anthropogenic ones. (iii. Detection of changes in the Earth climate system follows next, including the atmosphere, the oceans and the cryosphere, as well. (iv. Finally, satellite-born results in validation of climate models are presented in three aspects: reconstruction of present climate, validation of simulated changes and investigation of feedback mechanisms driving climate sensitivity to the external forcing factors. The above possibilities of using satellite information in climate science are mostly illustrated by key figures of the IPCC AR5 Report (2013.

Impacts of satellite galaxies on the redshift-space distortions

Energy Technology Data Exchange (ETDEWEB)

Hikage, Chiaki [Kobayashi-Maskawa Institute, Nagoya University, Nagoya 464-8602 (Japan); Yamamoto, Kazuhiro, E-mail: hikage@kmi.nagoya-u.ac.jp, E-mail: kazuhiro@hiroshima-u.ac.jp [Department of Physical Sciences, Hiroshima University, Higashi-hiroshima, Kagamiyama 1-3-1, 739-8526 (Japan)

2013-08-01

We study the impacts of the satellite galaxies on the redshift-space distortions. In our multipole power spectrum analysis of the luminous red galaxies (LRGs) samples of the Sloan digital sky survey (SDSS), we have clearly detected the non-zero signature of the hexadecapole and tetrahexadecapole spectrum, which almost disappears in the power spectrum with the sample of the brightest LRGs only. We thus demonstrate that the satellite LRGs in multiple systems make a significant contribution to the multipole power spectrum though its fraction is small. The behavior can be understood by a simple halo model, in which the one-halo term, describing the Finger of God (FoG) effect from the satellite galaxies, makes the dominant contribution to the higher multipole spectra. We demonstrate that the small-scale information of higher multipole spectrum is useful for calibrating the satellite FoG effect and improves the measurement of the cosmic growth rate dramatically. We further demonstrate that the fiber collision in the galaxy survey influences the one-halo term and the higher multipole spectra, because the number of satellite galaxies in the halo occupation distribution (HOD) is changed. We also discuss about the impact of satellite galaxies on future high-redshift surveys targeting the H-alpha emitters.

CBERS-2B Brazilian remote sensing satellite to help to monitor the Bolivia-Brazil gas pipeline

Energy Technology Data Exchange (ETDEWEB)

Hernandes, Gilberto Luis Sanches [TBG Transportadora Brasileira Gasoduto Bolivia-Brasil, Rio de Janeiro, RJ (Brazil)

2009-07-01

This paper presents the results of CBERS-2B' Brazilian Remote Sensing Satellite to help to monitor the Bolivia-Brazil Gas Pipeline. The CBERS-2B is the third satellite launched in 2007 by the CBERS Program (China-Brazil Earth Resources Satellite) and the innovation was the HRC camera that produces high resolution images. It will be possible to obtain one complete coverage of the country every 130 days. In this study, 2 images from different parts of the Bolivia- Brazil Gas Pipeline were selected. Image processing involved the geometric registration of CBERS-2B satellite images with airborne images, contrast stretch transform and pseudo color. The analysis of satellite and airborne images in a GIS software to detect third party encroachment was effective to detect native vegetation removal, street construction, growth of urban areas, farming and residential/industrial land development. Very young, the CBERS-2B is a good promise to help to inspect the areas along the pipelines. (author)

On the robustness of EC-PC spike detection method for online neural recording.

Science.gov (United States)

Zhou, Yin; Wu, Tong; Rastegarnia, Amir; Guan, Cuntai; Keefer, Edward; Yang, Zhi

2014-09-30

Online spike detection is an important step to compress neural data and perform real-time neural information decoding. An unsupervised, automatic, yet robust signal processing is strongly desired, thus it can support a wide range of applications. We have developed a novel spike detection algorithm called "exponential component-polynomial component" (EC-PC) spike detection. We firstly evaluate the robustness of the EC-PC spike detector under different firing rates and SNRs. Secondly, we show that the detection Precision can be quantitatively derived without requiring additional user input parameters. We have realized the algorithm (including training) into a 0.13 μm CMOS chip, where an unsupervised, nonparametric operation has been demonstrated. Both simulated data and real data are used to evaluate the method under different firing rates (FRs), SNRs. The results show that the EC-PC spike detector is the most robust in comparison with some popular detectors. Moreover, the EC-PC detector can track changes in the background noise due to the ability to re-estimate the neural data distribution. Both real and synthesized data have been used for testing the proposed algorithm in comparison with other methods, including the absolute thresholding detector (AT), median absolute deviation detector (MAD), nonlinear energy operator detector (NEO), and continuous wavelet detector (CWD). Comparative testing results reveals that the EP-PC detection algorithm performs better than the other algorithms regardless of recording conditions. The EC-PC spike detector can be considered as an unsupervised and robust online spike detection. It is also suitable for hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

UV Spectrophotometry of the Galilean Satellites, Saturnian Satellites & Selected Asteroids

Science.gov (United States)

Nelson, Robert M.

leading face of Iapetus has not been well characterized because the time period where optimum detection of the dark material occurs only lasts about one-half day and past scheduling has not permitted data acquisition In this time-window. We wish to carefully arrange the observations to permit this critical measurement, as well as acquiring a few other orbital phase angles for Dione and Rhea. The Voyager spacecraft made a few broad-band measurements at 260 nm but IUE data are needed to fix the low solar phase angle data. These data will form the basis of a UV spectral geometric albedo set for these satellites.

Uncoupling of satellite DNA and centromeric function in the genus Equus.

Science.gov (United States)

Piras, Francesca M; Nergadze, Solomon G; Magnani, Elisa; Bertoni, Livia; Attolini, Carmen; Khoriauli, Lela; Raimondi, Elena; Giulotto, Elena

2010-02-12

In a previous study, we showed that centromere repositioning, that is the shift along the chromosome of the centromeric function without DNA sequence rearrangement, has occurred frequently during the evolution of the genus Equus. In this work, the analysis of the chromosomal distribution of satellite tandem repeats in Equus caballus, E. asinus, E. grevyi, and E. burchelli highlighted two atypical features: 1) several centromeres, including the previously described evolutionary new centromeres (ENCs), seem to be devoid of satellite DNA, and 2) satellite repeats are often present at non-centromeric termini, probably corresponding to relics of ancestral now inactive centromeres. Immuno-FISH experiments using satellite DNA and antibodies against the kinetochore protein CENP-A demonstrated that satellite-less primary constrictions are actually endowed with centromeric function. The phylogenetic reconstruction of centromere repositioning events demonstrates that the acquisition of satellite DNA occurs after the formation of the centromere during evolution and that centromeres can function over millions of years and many generations without detectable satellite DNA. The rapidly evolving Equus species gave us the opportunity to identify different intermediate steps along the full maturation of ENCs.

Uncoupling of satellite DNA and centromeric function in the genus Equus.

Directory of Open Access Journals (Sweden)

Francesca M Piras

2010-02-01

Full Text Available In a previous study, we showed that centromere repositioning, that is the shift along the chromosome of the centromeric function without DNA sequence rearrangement, has occurred frequently during the evolution of the genus Equus. In this work, the analysis of the chromosomal distribution of satellite tandem repeats in Equus caballus, E. asinus, E. grevyi, and E. burchelli highlighted two atypical features: 1 several centromeres, including the previously described evolutionary new centromeres (ENCs, seem to be devoid of satellite DNA, and 2 satellite repeats are often present at non-centromeric termini, probably corresponding to relics of ancestral now inactive centromeres. Immuno-FISH experiments using satellite DNA and antibodies against the kinetochore protein CENP-A demonstrated that satellite-less primary constrictions are actually endowed with centromeric function. The phylogenetic reconstruction of centromere repositioning events demonstrates that the acquisition of satellite DNA occurs after the formation of the centromere during evolution and that centromeres can function over millions of years and many generations without detectable satellite DNA. The rapidly evolving Equus species gave us the opportunity to identify different intermediate steps along the full maturation of ENCs.

A Study on the Use of Commercial Satellite Imagery for Monitoring of Yongbyon Nuclear Activities

Energy Technology Data Exchange (ETDEWEB)

Lee, Jung Hyun; Kim, Min Soo [Korea Institute of Nuclear Nonproliferation and Control Daejeon (Korea, Republic of)

2014-10-15

It is particularly useful for the areas that are hard to access, such as the DPRK. On April 2009, North Korea expelled IAEA inspectors and USA disabling team at Yongbyon. Since then, there is not much left except for satellite imagery analysis. In this paper, we focused on the growing role and importance of commercial satellite imagery analysis for detecting and identifying nuclear activities at Yongbyon. For this, we examined monitoring capability of commercial satellite imagery status of commercial satellite imagery analysis to monitor the Yongbyon nuclear site. And we suggested several recommendations for enhancing the monitoring and analyzing capability. Current commercial satellite imagery has proven effective in monitoring for Yongbyon nuclear activities, especially change detection including the new construction activities. But identification and technical analysis of the operation status is still limited. In case of North Korea, operation status of 5 MWe reactor should be clearly identified to assess its plutonium production capability and to set up the negotiation strategy. To enhance the monitoring capability, we need much more thermal infrared imagery and radar imagery.

Broadband, red-edge information from satellites improves early stress detection in a New Mexico conifer woodland

Science.gov (United States)

Jan U.H. Eitel; Lee A. Vierling; Marcy E. Litvak; Dan S. Long; Urs Schulthess; Alan A. Ager; Dan J. Krofcheck; Leo Stoscheck

2011-01-01

Multiple plant stresses can affect the health, esthetic condition, and timber harvest value of conifer forests. To monitor spatial and temporal dynamic forest stress conditions, timely, accurate, and cost-effective information is needed that could be provided by remote sensing. Recently, satellite imagery has become available via the RapidEye satellite constellation to...

Evolution in the lineament patterns associated to strong earthquakes revealed by satellite observations

Science.gov (United States)

Soto-Pinto, C. A.; Arellano-Baeza, A. A.; Ouzounov, D. P.

2011-12-01

We study the temporal evolution of the stress patterns in the crust by using high-resolution (10-300 m) satellite images from MODIS and ASTER satellite sensors. We are able to detect some changes in density and orientation of lineaments preceding earthquake events. A lineament is generally defined as a straight or a somewhat curved feature in the landscape visible in a satellite image as an aligned sequence of pixels of a contrasting intensity compared to the background. The system of lineaments extracted from the satellite images is not identical to the geological lineaments; nevertheless, it generally reflects the structure of the faults and fractures in the Earth's crust. Our analysis has shown that the system of lineaments is very dynamical, and the significant number of lineaments appeared approximately one month before an earthquake, while one month after the earthquake the lineament configuration returned to its initial state. These features were not observed in the test areas that are free of any seismic activity in that period (null hypothesis). We have designed a computational prototype capable to detect lineament evolution and to utilize both ASTER and MODIS satellite L1/L2. We will demonstrate the first successful test results for several Mw> 5 earthquakes in Chile, Peru, China, and California (USA).

The total satellite population of the Milky Way

Science.gov (United States)

Newton, Oliver; Cautun, Marius; Jenkins, Adrian; Frenk, Carlos S.; Helly, John C.

2018-05-01

The total number and luminosity function of the population of dwarf galaxies of the Milky Way (MW) provide important constraints on the nature of the dark matter and on the astrophysics of galaxy formation at low masses. However, only a partial census of this population exists because of the flux limits and restricted sky coverage of existing Galactic surveys. We combine the sample of satellites recently discovered by the Dark Energy Survey (DES) survey with the satellites found in Sloan Digital Sky Survey (SDSS) Data Release 9 (together these surveys cover nearly half the sky) to estimate the total luminosity function of satellites down to MV = 0. We apply a new Bayesian inference method in which we assume that the radial distribution of satellites independently of absolute magnitude follows that of subhaloes selected according to their peak maximum circular velocity. We find that there should be at least 124^{+40}_{-27}(68% CL, statistical error) satellites brighter than MV = 0 within 300kpc of the Sun. As a result of our use of new data and better simulations, and a more robust statistical method, we infer a much smaller population of satellites than reported in previous studies using earlier SDSS data only; we also address an underestimation of the uncertainties in earlier work by accounting for stochastic effects. We find that the inferred number of faint satellites depends only weakly on the assumed mass of the MW halo and we provide scaling relations to extend our results to different assumed halo masses and outer radii. We predict that half of our estimated total satellite population of the MW should be detected by the Large Synoptic Survey Telescope (LSST). The code implementing our estimation method is available online.†

Bottom Pressure Tides Along a Line in the Southeast Atlantic Ocean and Comparisons with Satellite Altimetry

Science.gov (United States)

Ray, Richard D.; Byrne, Deidre A.

2010-01-01

Seafloor pressure records, collected at 11 stations aligned along a single ground track of the Topex/Poseidon and Jason satellites, are analyzed for their tidal content. With very low background noise levels and approximately 27 months of high-quality records, tidal constituents can be estimated with unusually high precision. This includes many high-frequency lines up through the seventh-diurnal band. The station deployment provides a unique opportunity to compare with tides estimated from satellite altimetry, point by point along the satellite track, in a region of moderately high mesoscale variability. That variability can significantly corrupt altimeter-based tide estimates, even with 17 years of data. A method to improve the along-track altimeter estimates by correcting the data for nontidal variability is found to yield much better agreement with the bottom-pressure data. The technique should prove useful in certain demanding applications, such as altimetric studies of internal tides.

Synchronous observations of long-periodic geomagnetic pulsations on the ATS-6 satellite and on the Earth surface

International Nuclear Information System (INIS)

Barfild, Dzh.N.; Bondarenko, N.M.; Buloshnikov, A.M.; Gokhberg, M.B.; Kalisher, A.L.; Mak-Ferron, R.L.; Troitskaya, V.A.

1977-01-01

Geomagnetic pulsations of the Pi2 and Pc4 types recorded by the ATS-6 geostationary satellite and by observatories located near the geomagnetic longitude of the space satellite from the 24th of May, 1974 to the 1st of September, 1976 are compared. The periods of the Pi2 pulsations measured by the space satellite and on the Earth practically coincide, dynamic spectra and spectral densities are similar. The amplitude of the Pi2 pulsations recorded in auroral latitudes is several times wider than the amplitude measured by the ATS-6 while in middle latitudes the amplitude is much smaller than on the satellite. The Pc4 pulsations are not practically observed on the Earth for they are probably excited in narrow local areas of the magnitosphere. In order to arrive to the single-valued solution of the problem of the mechanism of the generation and localization of the pulsation source it is necessary to carry out simultaneous observations on the Earth and in the magnitosphere

Vegetation extraction from high-resolution satellite imagery using the Normalized Difference Vegetation Index (NDVI)

Science.gov (United States)

AlShamsi, Meera R.

2016-10-01

Over the past years, there has been various urban development all over the UAE. Dubai is one of the cities that experienced rapid growth in both development and population. That growth can have a negative effect on the surrounding environment. Hence, there has been a necessity to protect the environment from these fast pace changes. One of the major impacts this growth can have is on vegetation. As technology is evolving day by day, there is a possibility to monitor changes that are happening on different areas in the world using satellite imagery. The data from these imageries can be utilized to identify vegetation in different areas of an image through a process called vegetation detection. Being able to detect and monitor vegetation is very beneficial for municipal planning and management, and environment authorities. Through this, analysts can monitor vegetation growth in various areas and analyze these changes. By utilizing satellite imagery with the necessary data, different types of vegetation can be studied and analyzed, such as parks, farms, and artificial grass in sports fields. In this paper, vegetation features are detected and extracted through SAFIY system (i.e. the Smart Application for Feature extraction and 3D modeling using high resolution satellite ImagerY) by using high-resolution satellite imagery from DubaiSat-2 and DEIMOS-2 satellites, which provide panchromatic images of 1m resolution and spectral bands (red, green, blue and near infrared) of 4m resolution. SAFIY system is a joint collaboration between MBRSC and DEIMOS Space UK. It uses image-processing algorithms to extract different features (roads, water, vegetation, and buildings) to generate vector maps data. The process to extract green areas (vegetation) utilize spectral information (such as, the red and near infrared bands) from the satellite images. These detected vegetation features will be extracted as vector data in SAFIY system and can be updated and edited by end-users, such as

Using Satellite Data and Land Surface Models to Monitor and Forecast Drought Conditions in Africa and Middle East

Science.gov (United States)

Arsenault, K. R.; Shukla, S.; Getirana, A.; Peters-Lidard, C. D.; Kumar, S.; McNally, A.; Zaitchik, B. F.; Badr, H. S.; Funk, C. C.; Koster, R. D.; Narapusetty, B.; Jung, H. C.; Roningen, J. M.

2017-12-01

Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. In addition, these regions typically have sparse ground-based data networks, where sometimes remotely sensed observations may be the only data available. Long-term satellite records can help with determining historic and current drought conditions. In recent years, several new satellites have come on-line that monitor different hydrological variables, including soil moisture and terrestrial water storage. Though these recent data records may be considered too short for the use in identifying major droughts, they do provide additional information that can better characterize where water deficits may occur. We utilize recent satellite data records of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) and the European Space Agency's Advanced Scatterometer (ASCAT) soil moisture retrievals. Combining these records with land surface models (LSMs), NASA's Catchment and the Noah Multi-Physics (MP), is aimed at improving the land model states and initialization for seasonal drought forecasts. The LSMs' total runoff is routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics, which can provide an additional means of validation against in situ streamflow data. The NASA Land Information System (LIS) software framework drives the LSMs and HyMAP and also supports the capability to assimilate these satellite retrievals, such as soil moisture and TWS. The LSMs are driven for 30+ years with NASA's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS/UCSB Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall dataset. The seasonal water deficit forecasts are generated using downscaled and bias-corrected versions of NASA's Goddard Earth Observing System Model (GEOS-5), and NOAA's Climate Forecast System (CFSv2) forecasts

An Alternative Inter-Satellite Calibration of the UMD HIRS OLR Retrievals

Science.gov (United States)

Robertson, Franklin R.; Lee, Hai-Tien

2012-01-01

Outgoing Longwave Radiation (OLR) at the top-of-atmosphere (TOA) is a fundamental component of Earth's energy balance and represents the heat energy in the thermal bands rejected to space by the planet. Determination of OLR from satellites has a long and storied history, but the observational record remains largely fragmented with gaps in satellite measurements over the past three decades. Perhaps the most semi-continuous set of retrievals comes from the University of Maryland (UMD) algorithm that uses four HIRS (High Resolution Infrared Sounder) channels on the NOAA polar orbiting satellites to estimate OLR. This data set shows great promise in helping to bridge the discontinuous ERBS (Earth Radiation Budget Satellite) and CERES (Clouds and the Earth s Radiant Energy System) measurements. However, significant satellite inter-calibration biases persist with the present UMD data, principally outside the tropics. Difficulties relate to the combination of drift of the satellite equator crossing time through the diurnal cycle and changes in HIRS channel response function design. Here we show how an ad hoc recalibration of the UMD retrievals among the different satellites removes much of the remaining uncertainty due to diurnal drift of the satellite orbit. The adjusted HIRS data (using no other external information) show much better agreement with OLR from the European Center Interim Reanalysis (EC-Int), longer-term signals in the Global Energy and Water Cycle Experiment / Surface Radiation Budget (GEWEX/SRB) retrievals, and also agree well with ERBS and CERES OLR measurements. These results augur well for narrowing the uncertainties in multi-decadal estimates of this important climate variable.

Analysis of Specular Reflections Off Geostationary Satellites

Science.gov (United States)

Jolley, A.

2016-09-01

Many photometric studies of artificial satellites have attempted to define procedures that minimise the size of datasets required to infer information about satellites. However, it is unclear whether deliberately limiting the size of datasets significantly reduces the potential for information to be derived from them. In 2013 an experiment was conducted using a 14 inch Celestron CG-14 telescope to gain multiple night-long, high temporal resolution datasets of six geostationary satellites [1]. This experiment produced evidence of complex variations in the spectral energy distribution (SED) of reflections off satellite surface materials, particularly during specular reflections. Importantly, specific features relating to the SED variations could only be detected with high temporal resolution data. An update is provided regarding the nature of SED and colour variations during specular reflections, including how some of the variables involved contribute to these variations. Results show that care must be taken when comparing observed spectra to a spectral library for the purpose of material identification; a spectral library that uses wavelength as the only variable will be unable to capture changes that occur to a material's reflected spectra with changing illumination and observation geometry. Conversely, colour variations with changing illumination and observation geometry might provide an alternative means of determining material types.

Leveraging the NPS Femto Satellite for Alternative Satellite Communication Networks

Science.gov (United States)

2017-09-01

programmed for eventual integration with the Iridium Network , which is then tested. C. THESIS ORGANIZATION The thesis addresses these questions...NPS FEMTO SATELLITE FOR ALTERNATIVE SATELLITE COMMUNICATION NETWORKS by Faisal S. Alshaya September 2017 Co-Advisors: Steven J. Iatrou...TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE LEVERAGING THE NPS FEMTO SATELLITE FOR ALTERNATIVE SATELLITE COMMUNICATION NETWORKS 5

Feasibility of Using Mobile ECG Recording Technology to Detect Atrial Fibrillation in Low-Resource Settings.

Science.gov (United States)

Evans, Grahame F; Shirk, Arianna; Muturi, Peter; Soliman, Elsayed Z

2017-12-01

Screening for atrial fibrillation (AF), a major risk factor for stroke that is on the rise in Africa, is becoming increasingly critical. This study sought to examine the feasibility of using mobile electrocardiogram (ECG) recording technology to detect AF. In this prospective observational study, we used a mobile ECG recorder to screen 50 African adults (66% women; mean age 54.3 ± 20.5 years) attending Kijabe Hospital (Kijabe, Kenya). Five hospital health providers involved in this study's data collection process also completed a self-administered survey to obtain information on their access to the Internet and mobile devices, both factors necessary to implement ECG mobile technology. Outcome measures included feasibility (completion of the study and recruitment of the patients on the planned study time frame) and the yield of the screening by the mobile ECG technology (ability to detect previously undiagnosed AF). Patients were recruited in a 2-week period as planned; only 1 of the 51 patients approached refused to participate (98% acceptance rate). All of the 50 patients who agreed to participate completed the test and produced readable ECGs (100% study completion rate). ECG tracings of 4 of the 50 patients who completed the study showed AF (8% AF yield), and none had been previously diagnosed with AF. When asked about continuous access to Internet and personal mobile devices, almost all of the health care providers surveyed answered affirmatively. Using mobile ECG technology in screening for AF in low-resource settings is feasible, and can detect a significant proportion of AF cases that will otherwise go undiagnosed. Further study is needed to examine the cost-effectiveness of this approach for detection of AF and its effect on reducing the risk of stroke in developing countries. Copyright © 2016 World Heart Federation (Geneva). Published by Elsevier B.V. All rights reserved.

Using high resolution satellite multi-temporal interferometry for landslide hazard detection in tropical environments: the case of Haiti

Science.gov (United States)

Wasowski, Janusz; Nutricato, Raffaele; Nitti, Davide Oscar; Bovenga, Fabio; Chiaradia, Maria Teresa; Piard, Boby Emmanuel; Mondesir, Philemon

2015-04-01

Synthetic aperture radar (SAR) multi-temporal interferometry (MTI) is one of the most promising satellite-based remote sensing techniques for fostering new opportunities in landslide hazard detection and assessment. MTI is attractive because it can provide very precise quantitative information on slow slope displacements of the ground surface over huge areas with limited vegetation cover. Although MTI is a mature technique, we are only beginning to realize the benefits of the high-resolution imagery that is currently acquired by the new generation radar satellites (e.g., COSMO-SkyMed, TerraSAR-X). In this work we demonstrate the potential of high resolution X-band MTI for wide-area detection of slope instability hazards even in tropical environments that are typically very harsh (eg. coherence loss) for differential interferometry applications. This is done by presenting an example from the island of Haiti, a tropical region characterized by dense and rapidly growing vegetation, as well as by significant climatic variability (two rainy seasons) with intense precipitation events. Despite the unfavorable setting, MTI processing of nearly 100 COSMO-SkyMed (CSK) mages (2011-2013) resulted in the identification of numerous radar targets even in some rural (inhabited) areas thanks to the high resolution (3 m) of CSK radar imagery, the adoption of a patch wise processing SPINUA approach and the presence of many man-made structures dispersed in heavily vegetated terrain. In particular, the density of the targets resulted suitable for the detection of some deep-seated and shallower landslides, as well as localized, very slow slope deformations. The interpretation and widespread exploitation of high resolution MTI data was facilitated by Google EarthTM tools with the associated high resolution optical imagery. Furthermore, our reconnaissance in situ checks confirmed that MTI results provided useful information on landslides and marginally stable slopes that can represent a

Meteorological satellite systems

CERN Document Server

Tan, Su-Yin

2014-01-01

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

When Enrollments Bulge but Budgets Don't, Consider "Satellite Learning Centers."

Science.gov (United States)

Reecer, Marcia

1988-01-01

Describes Dade County (Florida) schools' answer to crowded classrooms and burgeoning primary enrollments: satellite learning centers built and maintained by local companies as employee childcare benefits. Each center is attached to a nearby "host" school that disburses funds, keeps student records, and supplies support services. (MLH)

Multi-satellite observations of magnetic fields in space plasmas

International Nuclear Information System (INIS)

Potemra, T.A.; Zanetti, L.J.; Bythrow, P.F.; Erlandson, R.E.

1987-01-01

The most common method of detecting electric currents in space has been by virtue of the magnetic perturbations they produce. A satellite can pass through a field-aligned ''Birkeland'' current and measure the in-situ magnetic perturbations. Satellite-borne magnetic field experiments may also be used to observe characteristics of resonant oscillations of the Earth's magnetic field at ULF frequencies. Examples of such measurements with magnetic field experiments on the Viking, AMPTE/CCE, and DMSP-F7 satellites will be presented. The Viking satellite, launched in February, 1986, is Sweden's first satellite and is in a polar orbit with 3.1 R/sub e/ apogee. AMPTE/CCE was launched in August, 1984, with satellites from West Germany and the United Kingdom, for the purpose of creating artificial comets in space. It is in an equatorial orbit with a 8.8 R/sub e/ apogee. The Defense Meteorological Satellite Program (DMSP)-F7 satellite was launched in October, 1983 into an 800 km circular sun-synchronous orbit in the 0830-2030 magnetic local time plane. Viking and AMPTE/CCE observed harmonic ULF pulsations when they were near the same flux tube, but separated by about 10 R/sub e/. These unique observations are used to investigate the characteristics and sources of multiple field line resonances of Alfven waves. On another occasion, Viking and DMSP-F7 observed similar magnetic perturbations at widely separated locations. The authors interpret these perturbations as due to a complicated system of large-scale stable Birkeland currents in the morning sector. This multi-satellite data set is in the early stages of exploration, but already confirms the usefulness of coordinated multi-position observations of magnetic fields in space

A service for the application of data quality information to NASA earth science satellite records

Science.gov (United States)

Armstrong, E. M.; Xing, Z.; Fry, C.; Khalsa, S. J. S.; Huang, T.; Chen, G.; Chin, T. M.; Alarcon, C.

2016-12-01

A recurring demand in working with satellite-based earth science data records is the need to apply data quality information. Such quality information is often contained within the data files as an array of "flags", but can also be represented by more complex quality descriptions such as combinations of bit flags, or even other ancillary variables that can be applied as thresholds to the geophysical variable of interest. For example, with Level 2 granules from the Group for High Resolution Sea Surface Temperature (GHRSST) project up to 6 independent variables could be used to screen the sea surface temperature measurements on a pixel-by-pixel basis. Quality screening of Level 3 data from the Soil Moisture Active Passive (SMAP) instrument can be become even more complex, involving 161 unique bit states or conditions a user can screen for. The application of quality information is often a laborious process for the user until they understand the implications of all the flags and bit conditions, and requires iterative approaches using custom software. The Virtual Quality Screening Service, a NASA ACCESS project, is addressing these issues and concerns. The project has developed an infrastructure to expose, apply, and extract quality screening information building off known and proven NASA components for data extraction and subset-by-value, data discovery, and exposure to the user of granule-based quality information. Further sharing of results through well-defined URLs and web service specifications has also been implemented. The presentation will focus on overall description of the technologies and informatics principals employed by the project. Examples of implementations of the end-to-end web service for quality screening with GHRSST and SMAP granules will be demonstrated.

Satellite-based trends of solar radiation and cloud parameters in Europe

Science.gov (United States)

Pfeifroth, Uwe; Bojanowski, Jedrzej S.; Clerbaux, Nicolas; Manara, Veronica; Sanchez-Lorenzo, Arturo; Trentmann, Jörg; Walawender, Jakub P.; Hollmann, Rainer

2018-04-01

Solar radiation is the main driver of the Earth's climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation, top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe and covers the time period from 1992 to 2015. A high correlation between these three variables has been found over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records, which are mostly derived independently from each other. The results of this study indicate that one of the main reasons for the positive trend in surface solar radiation since the 1990's is a decrease in cloud coverage even if an aerosol contribution cannot be completely ruled out.

Multi-decadal record of ice dynamics on Daugaard Jensen Gletscher, East Greenland, from satellite imagery and terrestrial measurements

DEFF Research Database (Denmark)

Stearns, L.A.; Hamilton, G.S.; Reeh, Niels

2005-01-01

The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained in approxima......The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained...

Boomerang Satellites

Science.gov (United States)

Hesselbrock, Andrew; Minton, David A.

2017-10-01

We recently reported that the orbital architecture of the Martian environment allows for material in orbit around the planet to ``cycle'' between orbiting the planet as a ring, or as coherent satellites. Here we generalize our previous analysis to examine several factors that determine whether satellites accreting at the edge of planetary rings will cycle. In order for the orbiting material to cycle, tidal evolution must decrease the semi-major axis of any accreting satellites. In some systems, the density of the ring/satellite material, the surface mass density of the ring, the tidal parameters of the system, and the rotation rate of the primary body contribute to a competition between resonant ring torques and tidal dissipation that prevent this from occurring, either permanently or temporarily. Analyzing these criteria, we examine various bodies in our solar system (such as Saturn, Uranus, and Eris) to identify systems where cycling may occur. We find that a ring-satellite cycle may give rise to the current Uranian ring-satellite system, and suggest that Miranda may have formed from an early, more massive Uranian ring.

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

Science.gov (United States)

Stubenrauch, C. J.; Rossow, W. B.; Kinne, S.; Ackerman, S.; Cesana, G.; Chepfer, H.; Getzewich, B.; Di Girolamo, L.; Guignard, A.; Heidinger, A.;

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

Directory of Open Access Journals (Sweden)

Wei Jin

2016-12-01

Full Text Available Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC, atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation

Science.gov (United States)

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-01-01

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261

Optical neural network system for pose determination of spinning satellites

Science.gov (United States)

Lee, Andrew; Casasent, David

1990-01-01

An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

Possibility of continuous monitoring of environment around the nuclear plant using satellite remote sensing

International Nuclear Information System (INIS)

Sasaki, Takanori; Tanabu, Yoshimine; Fujita, Shigetaka; Zhao Wenhui

2008-01-01

Interest in nuclear power generation is increasing by rising of power demand and environmental concern. It is important more and more to confirm and show the safety operation of nuclear plants, which is useful to remove anxiety of residents. Satellite remote sensing is one of the way of it. Large observation width and long and continuous observation period are advantage of satellite remote sensing. In addition, it is very important to be able to monitor without visitation on the site. We have continued local area environmental analysis using various satellites. MODIS on Terra and Aqua which are NASA satellites received by Hachinohe Institute of Technology is mainly used. According to these results, we have shown that combined analysis of various information parameters such as land surface temperature, geographical changes, vegetation, etc. is very effective to monitor environmental changes. In these analyses, error detection is very important. Therefore, enough storage data with continuously monitoring in usual state is necessary. Moreover, it is thought that the confirmation of stable operation of plants by means of continuous monitoring can contribute to reduce residents' anxiety of nuclear power plant. Additionally, in the case that the change of influence on surroundings is detected, it is possible to grasp the situation and take measure in early stage by error detection. In this paper, as an possible example of continuous monitoring using satellite remote sensing, we introduce the result of analysis and investigation of which changes of sea surface temperature and chlorophyll concentration on the sea around power plant. (author)

Detecting hidden volcanic explosions from Mt. Cleveland Volcano, Alaska with infrasound and ground-couples airwaves

Science.gov (United States)

De Angelis, Slivio; Fee, David; Haney, Matthew; Schneider, David

2012-01-01

In Alaska, where many active volcanoes exist without ground-based instrumentation, the use of techniques suitable for distant monitoring is pivotal. In this study we report regional-scale seismic and infrasound observations of volcanic activity at Mt. Cleveland between December 2011 and August 2012. During this period, twenty explosions were detected by infrasound sensors as far away as 1827 km from the active vent, and ground-coupled acoustic waves were recorded at seismic stations across the Aleutian Arc. Several events resulting from the explosive disruption of small lava domes within the summit crater were confirmed by analysis of satellite remote sensing data. However, many explosions eluded initial, automated, analyses of satellite data due to poor weather conditions. Infrasound and seismic monitoring provided effective means for detecting these hidden events. We present results from the implementation of automatic infrasound and seismo-acoustic eruption detection algorithms, and review the challenges of real-time volcano monitoring operations in remote regions. We also model acoustic propagation in the Northern Pacific, showing how tropospheric ducting effects allow infrasound to travel long distances across the Aleutian Arc. The successful results of our investigation provide motivation for expanded efforts in infrasound monitoring across the Aleutians and contributes to our knowledge of the number and style of vulcanian eruptions at Mt. Cleveland.

Pemanfaatan Data ARR (Automatic Rainfall Recorder) untuk Peningkatan Efektifitas Model Hujan Satelit (Studi Kasus DAS Indragiri)

OpenAIRE

Hendra, Yuli; Fauzi, Manyuk; Sutikno, Sigit

2015-01-01

The availability of data on hydrological modeling always become a problem considering the incompleteness and the imprecision of data. As the development of technology, many models of hidrology using data acquired from the satellite have emerged. The accuracy and the model correlation was still unachieved from the previous research using satellite data. This problems was caused by the unstable weather conditions thus the process of recording and dowloading of the satellite data become less opt...

Gigabit Satellite Network for NASA's Advanced Communication Technology Satellite (ACTS)

Science.gov (United States)

Hoder, Douglas; Bergamo, Marcos

1996-01-01

The advanced communication technology satellite (ACTS) gigabit satellite network provides long-haul point-to-point and point-to-multipoint full-duplex SONET services over NASA's ACTS. at rates up to 622 Mbit/s (SONET OC-12), with signal quality comparable to that obtained with terrestrial fiber networks. Data multiplexing over the satellite is accomplished using time-division multiple access (TDMA) techniques coordinated with the switching and beam hopping facilities provided by ACTS. Transmissions through the satellite are protected with Reed-Solomon encoding. providing virtually error-free transmission under most weather conditions. Unique to the system are a TDMA frame structure and satellite synchronization mechanism that allow: (a) very efficient utilization of the satellite capacity: (b) over-the-satellite dosed-loop synchronization of the network in configurations with up to 64 ground stations: and (c) ground station initial acquisition without collisions with existing signalling or data traffic. The user interfaces are compatible with SONET standards, performing the function of conventional SONET multiplexers and. as such. can be: readily integrated with standard SONET fiber-based terrestrial networks. Management of the network is based upon the simple network management protocol (SNMP). and includes an over-the-satellite signalling network and backup terrestrial internet (IP-based) connectivity. A description of the ground stations is also included.

Monitoring coastal inundation with Synthetic Aperture Radar satellite data

Science.gov (United States)

Suzuoki, Yukihiro; Rangoonwala, Amina; Ramsey, Elijah W.

2011-01-01

Maps representing the presence and absence of surface inundation in the Louisiana coastal zone were created from available satellite scenes acquired by the Japanese Aerospace Exploration Agency's Advanced Land Observing Satellite and by the European Space Agency's Envisat from late 2006 through summer 2009. Detection of aboveground surface flooding relied on the well-documented and distinct signature of decreased backscatter in Synthetic Aperture Radar (SAR), which is indicative of inundated marsh in the Gulf of Mexico. Even though decreases in backscatter were distinctive, the multiplicity of possible interactions between changing flood depths and canopy height yielded complex SAR-based representations of the marshes.

An SDR based AIS receiver for satellites

DEFF Research Database (Denmark)

Larsen, Jesper Abildgaard; Mortensen, Hans Peter; Nielsen, Jens Frederik Dalsgaard

2011-01-01

For a few years now, there has been a high interest in monitoring the global ship traffic from space. A few satellite, capable of listening for ship borne AIS transponders have already been launched, and soon the AAUSAT3, carrying two different types of AIS receivers will also be launched. One...... of the AIS receivers onboard AAUSAT3 is an SDR based AIS receiver. This paper serves to describe the background of the AIS system, and how the SDR based receiver has been integrated into the AAUSAT3 satellite. Amongst some of the benefits of using an SDR based receiver is, that due to its versatility, new...... detection algorithms are easily deployed, and it is easily adapted the new proposed AIS transmission channels....

Robust satellite techniques for monitoring volcanic eruptions

Energy Technology Data Exchange (ETDEWEB)

Pergola, N.; Pietrapertosa, C. [Consiglio Nazionale delle Ricerche, Istituto di Metodologie Avanzate, Tito Scalo, PZ (Italy); Lacava, T.; Tramutoli, V. [Potenza Universita' della Basilicata, Potenza (Italy). Dipt. di Ingegneria e Fisica dell' Ambiente

2001-04-01

Through this paper the robust approach to monitoring volcanic aerosols by satellite is applied to an extended set of events affecting Stromboli and Etna volcanoes to assess its performance in automated detection of eruptive clouds and in monitoring pre-eruptive emission activities. Using only NOAA/AVHRR data at hand (without any specific atmospheric model or ancillary ground-based measurements) the proposed method automatically discriminates meteorological from eruptive volcanic clouds and, in several cases, identified pre-eruptive anomalies in the emission rates not identified by traditional methods. The main merit of this approach is its effectiveness in recognising field anomalies also in the presence of a highly variable surface background as well as its intrinsic exportability not only on different geographic areas but also on different satellite instrumental packages. In particular, the possibility to extend the proposed method to the incoming new MSG/SEVIRI satellite package (which is going to fly next year) with its improved spectral (specific bands for SO{sub 2}) and temporal (up to 15 min) resolutions has been evaluated representing the natural continuation of this work.

Ship Detection Using Transfer Learned Single Shot Multi Box Detector

Directory of Open Access Journals (Sweden)

Nie Gu-Hong

2017-01-01

Full Text Available Ship detection in satellite images is a challenging task. In this paper, we introduce a transfer learned Single Shot MultiBox Detector (SSD for ship detection. To this end, a state-of-the-art object detection model pre-trained from a large number of natural images was transfer learned for ship detection with limited labeled satellite images. To the best of our knowledge, this could be one of the first studies which introduce SSD into ship detection on satellite images. Experiments demonstrated that our method could achieve 87.9% AP at 47 FPS using NVIDIA TITAN X. In comparison with Faster R-CNN, 6.7% AP improvement could be achieved. Effects of the observation resolution has also been studied with the changing input sizes among 300 × 300, 600 × 600 and 900 × 900. It has been noted that the detection accuracy declined sharply with the decreasing resolution that is mainly caused by the missing small ships.

ELF and VLF signatures of sprites registered onboard the low altitude satellite DEMETER

Directory of Open Access Journals (Sweden)

J. Błęcki

2009-06-01

Full Text Available We report the observation of ELF and VLF signature of sprites recorded on the low altitude satellite DEMETER during thunderstorm activity. At an altitude of ~700 km, waves observed on the E-field spectrograms at mid-to-low latitudes during night time are mainly dominated by up-going 0+ whistlers. During the night of 20 July 2007 two sprites have been observed around 20:10:08 UT from the observatory located on the top of the mountain Śnieżka in Poland (50°44'09" N, 15°44'21" E, 1603 m and, ELF and VLF data have been recorded by the satellite at about 1200 km from the region of thunderstorm activity. During this event, the DEMETER instruments were switched in the burst mode and it was possible to register the wave forms. It is shown that the two sprites have been triggered by two intense +CG lightning strokes (100 kA occurring during the same millisecond but not at the same location. Despite the distance DEMETER has recorded at the same time intense and unusual ELF and VLF emissions. It is shown that the whistler wave propagates from the thunderstorm regions in the Earth-ionosphere guide and enters in the ionosphere below the satellite. They last several tens of milliseconds and the intensity of the ELF waveform is close to 1 mV/m. A particularly intense proton whistler is also associated with these emissions.

Comparison between remotely-sensed sea-surface temperature (AVHRR and in situ records in San Matías Gulf (Patagonia, Argentina

Directory of Open Access Journals (Sweden)

Gabriela N Williams

2014-03-01

Full Text Available In situ records of sea surface temperature collected between 2005 and 2009 were used to compare, for the first time, the temperature estimated by the Multichannel algorithms (MCSST of the Advanced Very High Resolution Radiometer (AVHRR sensors in San Matías Gulf, in the north of the Argentinean Patagonian Continental Shelf (between 40°47'-42°13'S. Match-ups between in situ records and satellite sea surface temperature (SST were analyzed. In situ records came from fixed stations and oceanographic cruises, while satellite data came from different NOAA satellites. The fitting of temperature data to a Standard Major Axis (SMA type II regression model indicated that a high proportion of the total variance (0.53< r² <0.99 was explained by this model showing a high correlation between in situ data and satellite estimations. The mean differences between satellite and in situ data for the full data set were 1.64 ± 1.49°C. Looking separately into in situ data from different sources and day and night estimates from different NOAA satellites, the differences were between 0.30 ± 0.60°C and 2.60 ± 1.50°C. In this paper we discuss possible reasons for the above-mentioned performance of the MCSST algorithms in the study area.

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

Science.gov (United States)

Benzouai, Siham; Smara, Youcef

2010-12-01

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

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

Science.gov (United States)

Liang, Yu-Li

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

Ten Years of Forest Cover Change in the Sierra Nevada Detected Using Landsat Satellite Image Analysis

Science.gov (United States)

Potter, Christopher S.

2014-01-01

A detailed geographic record of recent vegetation regrowth and disturbance patterns in forests of the Sierra Nevada remains a gap that can be filled with remote sensing data. Landsat (TM) imagery was analyzed to detect 10 years of recent changes (between 2000 and 2009) in forest vegetation cover for areas burned by wildfires between years of 1995 to 1999 in the region. Results confirmed the prevalence of regrowing forest vegetation during the period 2000 and 2009 over 17% of the combined burned areas.

A Fiducial Reference Stie for Satellite Altimetry in Crete, Greece

Science.gov (United States)

Mertikas, Stelios; Donlon, Craig; Mavrocordatos, Constantin; Bojkov, Bojan; Femenias, Pierre; Parrinello, Tommaso; Picot, Nicolas; Desjonqueres, Jean-Damien; Andersen, Ole Baltazar

2016-08-01

With the advent of diverse satellite altimeters and variant measuring techniques, it has become mature in the scientific community, that an absolute reference Cal/Val site is regularly maintained to define, monitor, control the responses of any altimetric system.This work sets the ground for the establishment of a Fiducial Reference Site for ESA satellite altimetry in Gavdos and West Crete, Greece. It will consistently and reliably determine (a) absolute altimeter biases and their drifts; (b) relative bias among diverse missions; but also (c) continuously and independently connect different missions, on a common and reliable reference and also to SI-traceable measurements. Results from this fiducial reference site will be based on historic Cal/Val site measurement records, and will be the yardstick for building up capacity for monitoring climate change. This will be achieved by defining and assessing any satellite altimeter measurements to known, controlled and absolute reference signals with different techniques, processes and instrumentation.

Detecting Historical Vegetation Changes in the Dunhuang Oasis Protected Area Using Landsat Images

Directory of Open Access Journals (Sweden)

Xiuxia Zhang

2017-09-01

Full Text Available Abstract: Given its proximity to an artificial oasis, the Donghu Nature Reserve in the Dunhuang Oasis has faced environmental pressure and vegetation disturbances in recent decades. Satellite vegetation indices (VIs can be used to detect such changes in vegetation if the satellite images are calibrated to surface reflectance (SR values. The aim of this study was to select a suitable VI based on the Landsat Climate Data Record (CDR products and the absolute radiation-corrected results of Landsat L1T images to detect the spatio-temporal changes in vegetation for the Donghu Reserve during 1986–2015. The results showed that the VI difference (ΔVI images effectively reduced the changes in the source images. Compared with the other VIs, the soil-adjusted vegetation index (SAVI displayed greater robustness to atmospheric effects in the two types of SR images and was more responsive to vegetation changes caused by human factors. From 1986 to 2015, the positive changes in vegetation dominated the overall change trend, with changes in vegetation in the reserve decreasing during 1990–1995, increasing until 2005–2010, and then decreasing again. The vegetation changes were mainly distributed at the edge of the artificial oasis outside the reserve. The detected changes in vegetation in the reserve highlight the increased human pressure on the reserve.

Comprehensive Comparisons of Satellite Data, Signals, and Measurements between the BeiDou Navigation Satellite System and the Global Positioning System †

Science.gov (United States)

Jan, Shau-Shiun; Tao, An-Lin

2016-01-01

The Chinese BeiDou navigation satellite system (BDS) aims to provide global positioning service by 2020. The combined use of BDS and Global Positioning System (GPS) is proposed to provide navigation service with more stringent requirements. Actual satellite data, signals and measurements were collected for more than one month to analyze the positioning service qualities from both BDS and GPS. In addition to the conversions of coordinate and timing system, five data quality analysis (DQA) methods, three signal quality analysis (SQA) methods, and four measurement quality analysis (MQA) methods are proposed in this paper to improve the integrated positioning performance of BDS and GPS. As shown in the experiment results, issues related to BDS and GPS are resolved by the above proposed quality analysis methods. Thus, the anomalies in satellite data, signals and measurements can be detected by following the suggested resolutions to enhance the positioning performance of the combined use of BDS and GPS in the Asia Pacific region. PMID:27187403

Ventricular Tachycardia Detected by Implantable Loop Recorder in a Child with Recurrent Syncope

Directory of Open Access Journals (Sweden)

İsa Özyılmaz

2014-06-01

Full Text Available In this article, we present a 10-year-old boy who was admitted to the hospital with recurrent syncope. There was no remarkable finding in patient’s physical examination, family history, and the diagnostic 12-lead electrocardiogram (ECG, chest x-ray, ECG Holter monitoring, event recording, echocardiography, coronary computed tomography (CT angiography, Ajmaline test for the diagnosis of Brugada syndrome, brain magnetic resonance imaging, and sleep/wake electroencephalogram. We started beta-blocker therapy because the patient had exercise-induced syncope. An Implantable loop recorder (ILR was inserted to the patient. Three years later, polymorphic ventricular tachycardia called torsades de pointes was detected by the ILR during syncope occurred with exercise. The patient had been taking high-dose betablocker treatment, an implantable cardioverter defibrillator was implanted into the patient. ILR can play an important role in the diagnosis of life-threatening arrhythmia in children with unexplained syncope. (The Me­di­cal Bul­le­tin of Ha­se­ki 2014; 52: 123-5

Centriolar satellites

DEFF Research Database (Denmark)

Tollenaere, Maxim A X; Mailand, Niels; Bekker-Jensen, Simon

2015-01-01

Centriolar satellites are small, microscopically visible granules that cluster around centrosomes. These structures, which contain numerous proteins directly involved in centrosome maintenance, ciliogenesis, and neurogenesis, have traditionally been viewed as vehicles for protein trafficking...... highlight newly discovered regulatory mechanisms targeting centriolar satellites and their functional status, and we discuss how defects in centriolar satellite components are intimately linked to a wide spectrum of human diseases....

NPOESS Environmental Data Record (EDR) Production

Science.gov (United States)

Hughes, R.; Grant, K. D.

2009-12-01

The National Oceanic and Atmospheric Administration (NOAA), Department of Defense (DoD), and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation weather and environmental satellite system; the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NPOESS replaces the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA and the Defense Meteorological Satellite Program (DMSP) managed by the DoD. The NPOESS satellites carry a suite of sensors that collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The ground data processing segment for NPOESS is the Interface Data Processing Segment (IDPS), developed by Raytheon Intelligence and Information Systems. The IDPS processes NPOESS satellite data to provide environmental data products (aka, Environmental Data Records or EDRs) to NOAA and DoD processing centers operated by the United States government. The IDPS will process EDRs beginning with the NPOESS Preparatory Project (NPP) and continuing through the lifetime of the NPOESS system. Northrop Grumman Aerospace Systems Algorithms and Data Products (A&DP) organization is responsible for the algorithms that produce the EDRs, including their quality aspects. Together, IDPS and A&DP must support the calibration, validation, and data quality improvement initiatives of the NPOESS program to ensure the production of atmospheric and environmental products that meet strict requirements for accuracy and precision. In support of this activity, A&DP and IDPS continually updates the estimated performance of the NPOESS system with respect to both latency and data quality, using the latest operational implementation of the data processing software and information from instrument test activities. This presentation will illustrate and describe the processing chains that create the data products, as well as describe the

Results of the Ongoing Monitoring of the Position of a Geostationary Telecommunication Satellite by the Method of Spatially Separated Basis Receiving of Digital Satellite Television Signals

Science.gov (United States)

Bushuev, F.; Kaliuzhnyi, M.; Sybiryakova, Y.; Shulga, O.; Moskalenko, S.; Balagura, O.; Kulishenko, V.

2016-10-01

The results of the ongoing monitoring of the position of geostationary telecommunication satellite Eutelsat-13B (13° East) are presented in the article. The results were obtained using a radio engineering complex (RC) of four stations receiving digital satellite television and a data processing centre. The stations are located in Kyiv, Mukachevo, Kharkiv and Mykolaiv. The equipment of each station allows synchronous recording (by the GPS) of fragments of DVB-S signal from the quadrature detector output of the satellite television receiver. Samples of the complex signal are archived and sent to the data processing center through the Internet. Here three linearly independent slant range differences (Δr) for three pairs of the stations are determined as a result of correlation processing of received signals. Every second measured values of Δr are used to calculate Cartesian coordinates (XYZ) of the satellite in the coordinate system WGS84 by multilateration method. The time series of Δr, X, Y and Z obtained during continuous observations from March to May 2015 are presented in the article. Single-measurement errors of Δr, X, Y and Z are equal to 2.6 m, 3540 m, 705 m and 455 m, respectively. The complex is compared with known analogues. Ways of reduction of measurement errors of satellite coordinates are considered. The radio engineering complex could be considered a prototype of a system of independent ongoing monitoring of the position of geostationary telecommunication satellites.

Detection of ionospheric perturbations associated with Japanese earthquakes on the basis of reception of LF transmitter signals on the satellite DEMETER

Directory of Open Access Journals (Sweden)

F. Muto

2008-02-01

Full Text Available There have been recently reported a lot of electromagnetic phenomena associated with earthquakes (EQs. Among these, the ground-based reception of subionospheric waves from VLF/LF transmitters, is recognized as a promising tool to investigate the ionospheric perturbations associated with EQs. This paper deals with the corresponding whistler-mode signals in the upper ionosphere from those VLF/LF transmitters, which is the counterpart of subionospheric signals. The whistler-mode VLF/LF transmitter signals are detected on board the French satellite, DEMETER launched on 29 June 2004. We have chosen several large Japanese EQs including the Miyagi-oki EQ (16 August 2005; M=7.2, depth=36 km, and the target transmitter is a Japanese LF transmitter (JJY whose transmitter frequency is 40 kHz. Due to large longitudinal separation of each satellite orbit (2500 km, we have to adopt a statistical analysis over a rather long period (such as 3 weeks or one month to have reliable data set. By analyzing the spatial distribution of JJY signal intensity (in the form of signal to noise ratio SNR during a period of 4 months including the Miyagi-oki EQ, we have found significant changes in the intensity; generally the SNR is significantly depleted before the EQ, which is considered to be a precursory ionospheric signature of the EQ. This abnormal effect is reasonably explained in terms of either (1 enhanced absorption of whistler-mode LF signals in the lower ionosphere due to the lowering of the lower ionosphere, or (2 nonlinear wave-wave scattering. Finally, this analysis suggests an important role of satellite observation in the study of lithosphere-atmosphere-ionosphere coupling.

Image Positioning Accuracy Analysis for Super Low Altitude Remote Sensing Satellites

Directory of Open Access Journals (Sweden)

Ming Xu

2012-10-01

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

High Bandwidth Optical Links for Micro-Satellite Support

Science.gov (United States)

Chao, Tien-Hsin (Inventor); Wilson, Keith E. (Inventor); Coste, Keith (Inventor)

2016-01-01

A method, systems, apparatus and device enable high bandwidth satellite communications. An onboard tracking detector, installed in a low-earth orbit satellite, detects a position of an incoming optical beam received/transmitted from a first ground station of one or more ground stations. Tracker electronics determine orientation information of the incoming optical beam based on the position. Control electronics receive the orientation information from the tracker electronics, and control a waveguide drive electronics. The waveguide drive electronics control a voltage that is provided to an electro-optic waveguide beam steering device. The electro-optic waveguide beam steering device steers an outgoing optical beam to one of the one or more ground stations based on the voltage.

Congestion control and routing over satellite networks

Science.gov (United States)

Cao, Jinhua

Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE

Satellite Imagery Assisted Road-Based Visual Navigation System

Science.gov (United States)

Volkova, A.; Gibbens, P. W.

2016-06-01

There is a growing demand for unmanned aerial systems as autonomous surveillance, exploration and remote sensing solutions. Among the key concerns for robust operation of these systems is the need to reliably navigate the environment without reliance on global navigation satellite system (GNSS). This is of particular concern in Defence circles, but is also a major safety issue for commercial operations. In these circumstances, the aircraft needs to navigate relying only on information from on-board passive sensors such as digital cameras. An autonomous feature-based visual system presented in this work offers a novel integral approach to the modelling and registration of visual features that responds to the specific needs of the navigation system. It detects visual features from Google Earth* build a feature database. The same algorithm then detects features in an on-board cameras video stream. On one level this serves to localise the vehicle relative to the environment using Simultaneous Localisation and Mapping (SLAM). On a second level it correlates them with the database to localise the vehicle with respect to the inertial frame. The performance of the presented visual navigation system was compared using the satellite imagery from different years. Based on comparison results, an analysis of the effects of seasonal, structural and qualitative changes of the imagery source on the performance of the navigation algorithm is presented. * The algorithm is independent of the source of satellite imagery and another provider can be used

A Multiple-Channel Sub-Band Transient Detection System

Energy Technology Data Exchange (ETDEWEB)

David A. Smith

1998-11-01

We have developed a unique multiple-channel sub-band transient detection system to record transient electromagnetic signals in carrier-dominated radio environments; the system has been used to make unique observations of weak, transient HF signals. The detection system has made these observations possible through improved sensitivity compared to conventional broadband transient detection systems; the sensitivity improvement is estimated to be at least 20 dB. The increase in sensitivity has been achieved through subdivision of the band of interest (an 18 MHz tunable bandwidth) into eight sub-band independent detection channels, each with a 400 kHz bandwidth and its own criteria. The system generates a system trigger signal when a predetermined number of channels (typically five) trigger within a predetermined window of time (typically 100 ~s). Events are recorded with a broadband data acquisition system sampling at 50 or 100 Msample/s, so despite the fact that the detection system operates on portions of the signal confined to narrow bands, data acquisition is broadband. Between May and September of 1994, the system was used to detect and record over six thousand transient events in the frequency band from 3 to 30 MHz. Approximately 500 of the events have been characterized as paired bursts of radio noise with individual durations of 2 to 10 ps and separations between the bursts of 5 to 160 ps. The paired transients are typically 5 to 40 dB brighter than the background electromagnetic spectrum between carrier signals. We have termed these events SubIonospheric Pulse Pairs (SIPPS) and presently have no explanation as to their source. Our observations of SIPPS resemble observations of TransIonospheric Pulse Pairs (TIPPs) recorded by the Blackboard instrument on the ALEXIS satellite; the source of TIPP events is also unknown. Most of the recorded SIPP events do not exhibit frequency dispersion, implying propagation along a line-of-sight (groundwave) path; but seven of

IAEA Safeguards: Cost/benefit analysis of commercial satellite imagery

International Nuclear Information System (INIS)

Andersson, Christer

1999-03-01

A major milestone in the efforts to strengthen the Safeguards System was reached in May 1997 when the Board of Governors approved a 'Model Protocol Additional to Safeguards Agreements'. The Protocol provides the legal basis necessary to enhance the Agency's ability to detect undeclared nuclear material and activities by using information available from open sources to complement the declarations made by Member States. Commercially available high-resolution satellite data has emerged as one potential complementary open information source to support the traditional and extended Safeguard activities of IAEA. This document constitutes a first report from SSC Satellitbild giving the Agency tentative and initial estimates of the potential cost and time-savings possible with the new proposed technology. The initial cost/benefit simulation will be further finalised in the following 'Implementation Blueprint' study. The general foundation and starting point for the cost/benefit calculation is to simulate a new efficient and relatively small 'imagery unit' within the IAEA, capable of performing advanced image processing as a tool for various safeguards tasks. The image processing capacity is suggested to be task- and interpretation-oriented. The study was performed over a period of 1,5 weeks in late 1998, and is based upon interviews of IAEA staff, reviews of existing IAEA documentation as well as from SSC Satellitbild's long-standing experience of satellite imagery and field missions. The cost/benefit analysis is based on a spreadsheet simulation of five potential applications of commercial satellite imagery: Reference information; Confirmation of Agency acquired and Member State supplied data; Change detection and on-going monitoring; Assessing open source information available to the Agency; Detecting undeclared activities and undeclared sites. The study confirms that the proposed concept of a relatively small 'imagery unit' using high-resolution data will be a sound and

Coherent Change Detection with COSMO SkyMed Data-experimental Results

OpenAIRE

A. Mishra; D. Chaudhuri; C. Bhattacharya; Y.S. Rao

2013-01-01

Change detection is a technique in which we try to find changes between two acquisitions. These acquisitions can be from different platforms and sensors. Acquisition from satellite using synthetic aperture radar (SAR) is of immense interest to military applications. Satellite has the ability to peep into the enemy territory while SAR has the capability of day and night operations, being an active sensor. Coherent change detection (CCD) can be used to detect minute changes between two images. ...

Improvements on Near Real Time Detection of Volcanic Ash Emissions for Emergency Monitoring with Limited Satellite Bands

Directory of Open Access Journals (Sweden)

Torge Steensen

2015-03-01

Full Text Available Quantifying volcanic ash emissions syneruptively is an important task for the global aviation community. However, due to the near real time nature of volcano monitoring, many parameters important for accurate ash mass estimates cannot be obtained easily. Even when using the best possible estimates of those parameters, uncertainties associated with the ash masses remain high, especially if the satellite data is only available in the traditional 10.8 and 12.0 μm bands. To counteract this limitation, we developed a quantitative comparison between the ash extents in satellite and model data. The focus is the manual cloud edge definition based on the available satellite reverse absorption (RA data as well as other knowledge like pilot reports or ground-based observations followed by an application of the Volcanic Ash Retrieval on the defined subset with an RA threshold of 0 K. This manual aspect, although subjective to the experience of the observer, can show a significant improvement as it provides the ability to highlight ash that otherwise would be obscured by meteorological clouds or, by passing over different surfaces with unaccounted temperatures, might be lost entirely and thus remains undetectable for an automated satellite approach. We show comparisons to Volcanic Ash Transport and Dispersion models and outline a quantitative match as well as percentages of overestimates based on satellite or dispersion model data which can be converted into a level of reliability for near real time volcano monitoring. 

NASA/DARPA advanced communications technology satellite project for evaluation of telemedicine outreach using next-generation communications satellite technology: Mayo Foundation participation.

Science.gov (United States)

Gilbert, B K; Mitchell, M P; Bengali, A R; Khandheria, B K

1999-08-01

To describe the development of telemedicine capabilities-application of remote consultation and diagnostic techniques-and to evaluate the feasibility and practicality of such clinical outreach to rural and underserved communities with limited telecommunications infrastructures. In 1992, Mayo Foundation (Rochester, Minn, Jacksonville, Fla, and Scottsdale, Ariz), the National Aeronautics and Space Administration, and the Defense Advanced Research Projects Agency collaborated to create a complex network of fiberoptic landlines, video recording systems, satellite terminals, and specially developed data translators linking Mayo sites with other locations in the continental United States on an on-demand basis. The purpose was to transmit data via the asynchronous transfer mode (ATM) digital communications protocol over the Advanced Communications Technology Satellite. The links were intended to provide a conduit for transmission of data for patient-specific consultations between physicians, evaluation of medical imagery, and medical education for clinical staffs at remote sites. Low-data-rate (LDR) experiments went live late in 1993. Mayo Clinic Rochester successfully provided medical consultation and services to 2 small regional medical facilities. High-data-rate (HDR) experiments included studies of remote digital echocardiography, store-and-forward telemedicine, cardiac catheterization, and teleconsultation for congenital heart disease. These studies combined landline data transmission with use of the satellite. The complexity of the routing paths and network components, immaturity of available software, and inexperience with existing telecommunications caused significant study delays. These experiments demonstrated that next-generation satellite technology can provide batch and real-time imagery for telemedicine. The first-generation of the ATM and satellite network technology used in these experiments created several technical problems and inconveniences that should

Wave excitation in electron beam experiment on Japanese satellite JIKIKEN (EXOS-B)

International Nuclear Information System (INIS)

Kawashima, N.

1982-01-01

This chapter reports on a beam-plasma interaction experiment conducted in the magnetosphere by emitting an electron beam (100-200 eV, 0.25-1.0 mA) from the JIKIKEN satellite. Topics considered include instrumentation, wave excitation, and the charging of the satellite. Various types of wave emission are detected by low frequency and high frequency wave detectors. Waves near upper-hybrid frequency and at electron cyclotron frequency are detected in a low L-value region, which will be useful diagnostic means for plasma density and magnetic field. Vehicle charging up to the beam energy is observed outside the plasmapause. The main objectives of the Controlled Beam Experiment (CBE) are to control the satellite potential by an electron beam emission, and to study the wave excitation (linear and non-linear wave phenomena due to the beam-plasma interaction). It is concluded that waves excited in the beamplasma interaction are strongly dependent on plasma and other parameters in the magnetosphere so that it will provide important knowledge of the magnetosphere plasma processes

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

Science.gov (United States)

Arellano-Baeza, A. A.; Urzua, L.

2011-12-01

Chile has enormous potential to use the geothermal resources for electric energy generation. The main geothermal fields are located in the Central Andean Volcanic Chain in the North, between the Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT and ASTER satellites have been used to delineate the geological structures related to the Calerias geothermal field located at the northern end of the Southern Volcanic Zone of Chile. It was done by applying the lineament extraction technique developed by authors. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields.

Elements of the tsunami precursors' detection physics

Science.gov (United States)

Novik, Oleg; Ruzhin, Yuri; Ershov, Sergey; Volgin, Max; Smirnov, Fedor

ionosphere from the buoy, balloon and satellite complexes. The balloon and buoy complexes will transmit data to a shore station over satellite link. The frequency ranges and sensitivity thresholds of all of the sensors of the LOAMS will be adapted to the characteristics of expected seismic signals according to the numerical research above. Computational methods and statistical analysis (e.g. seismic changes of coherence of spatially distributed sensors of different nature) of the recorded multidimensional time series will be used for prognostic interpretation. The multilevel recordings will provide a stable noise (e.g. ionosphere Pc pulsations, hard sea, industry) and seismic event detection. An intensive heat flow typical for tectonically active lithosphere zones may be considered as an energy source for advanced modifications of the LOAMS. The latter may be used as a warning system for continental and marine technologies, e.g. a sea bottom geothermal energy production. Indeed, seismic distraction of the nuclear power station Fukushima I demonstrates that similar technology hardly is able to solve the energy problems in seismically active regions. On the other hand, the LOAMS may be considered as a scientific observatory for development of the seaquake/tsunami precursor physics, i.e. seismo-hydro-electromagnetics.

Detection of extremely high bit density signals with a narrow track width GMR head in double layered perpendicular recording media

International Nuclear Information System (INIS)

Kiya, T.; Honda, N.; Ariake, J.; Ouchi, K.; Iwasaki, S.

2001-01-01

Recording resolution, medium noise and thermal stability have been investigated for double layered perpendicular magnetic recording media. The recording performance was improved by introducing a stacked intermediate layer between a soft magnetic backlayer and a storage layer due to increased crystal orientation with a small magnetic domain size and suppressed initial growing layer of the storage layer. The reproduced output at an extremely high linear density of 950 kFRPI was detected by using a contact-type CF-SPT head for write and a GMR head with a narrow read track width of 0.4 μm

Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

Directory of Open Access Journals (Sweden)

Shimelis B. Gebere

2015-09-01

Full Text Available Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an alternative source over these regions. This study evaluated the performance of three high-resolution satellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM 3B42, the Global Satellite Mapping of Precipitation (GSMaP_MVK+, and the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN at daily, monthly, and seasonal time scales against rain gauge records over data-scarce parts of Eastern Ethiopia. TRMM 3B42 rain products show relatively better performance at the three time scales, while PERSIANN did much better than GSMaP. At the daily time scale, TRMM correctly detected 88% of the rainfall from the rain gauge. The correlation at the monthly time scale also revealed that the TRMM has captured the observed rainfall better than the other two. For Belg (short rain and Kiremt (long rain seasons, the TRMM did better than the others by far. However, during Bega (dry season, PERSIANN showed a relatively good estimate. At all-time scales, noticing the bias, TRMM tends to overestimate, while PERSIANN and GSMaP tend to underestimate the rainfall. The overall result suggests that monthly and seasonal TRMM rainfall performed better than daily rainfall. It has also been found that both GSMaP and PERSIANN performed better in relatively flat areas than mountainous areas. Before the practical use of TRMM, the RMSE value needs to be improved by considering the topography of the study area or adjusting the bias.

Revisiting "Narrow Bipolar Event" intracloud lightning using the FORTE satellite

Science.gov (United States)

Jacobson, A. R.; Light, T. E. L.

2012-02-01

The lightning stroke called a "Narrow Bipolar Event", or NBE, is an intracloud discharge responsible for significant charge redistribution. The NBE occurs within 10-20 μs, and some associated process emits irregular bursts of intense radio noise, fading at shorter timescales, sporadically during the charge transfer. In previous reports, the NBE has been inferred to be quite different from other forms of lightning strokes, in two ways: First, the NBE has been inferred to be relatively dark (non-luminous) compared to other lightning strokes. Second, the NBE has been inferred to be isolated within the storm, usually not participating in flashes, but when it is in a flash, the NBE has been inferred to be the flash initiator. These two inferences have sufficiently stark implications for NBE physics that they should be subjected to further independent test, with improved statistics. We attempt such a test with both optical and radio data from the FORTE satellite, and with lightning-stroke data from the Los Alamos Sferic Array. We show rigorously that by the metric of triggering the PDD optical photometer aboard the FORTE satellite, NBE discharges are indeed less luminous than ordinary lightning. Referred to an effective isotropic emitter at the cloud top, NBE light output is inferred to be less than ~3 × 108 W. To address isolation of NBEs, we first expand the pool of geolocated intracloud radio recordings, by borrowing geolocations from either the same flash's or the same storm's other recordings. In this manner we generate a pool of ~2 × 105 unique and independent FORTE intracloud radio recordings, whose slant range from the satellite can be inferred. We then use this slant range to calculate the Effective Radiated Power (ERP) at the radio source, in the passband 26-49 MHz. Stratifying the radio recordings by ERP into eight bins, from a lowest bin (140 kW), we document a trend for the radio recordings to become more isolated in time as the ERP increases. The highest

Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively.

Science.gov (United States)

Shimamoto, Shoichi; Waldman, Zachary J; Orosz, Iren; Song, Inkyung; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sharan, Ashwini; Wu, Chengyuan; Sperling, Michael R; Weiss, Shennan A

2018-01-01

To develop and validate a detector that identifies ripple (80-200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). iEEG recordings from 16 patients were first band-pass filtered (80-600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of

Creation of an Accurate Algorithm to Detect Snellen Best Documented Visual Acuity from Ophthalmology Electronic Health Record Notes.

Science.gov (United States)

Mbagwu, Michael; French, Dustin D; Gill, Manjot; Mitchell, Christopher; Jackson, Kathryn; Kho, Abel; Bryar, Paul J

2016-05-04

Visual acuity is the primary measure used in ophthalmology to determine how well a patient can see. Visual acuity for a single eye may be recorded in multiple ways for a single patient visit (eg, Snellen vs. Jäger units vs. font print size), and be recorded for either distance or near vision. Capturing the best documented visual acuity (BDVA) of each eye in an individual patient visit is an important step for making electronic ophthalmology clinical notes useful in research. Currently, there is limited methodology for capturing BDVA in an efficient and accurate manner from electronic health record (EHR) notes. We developed an algorithm to detect BDVA for right and left eyes from defined fields within electronic ophthalmology clinical notes. We designed an algorithm to detect the BDVA from defined fields within 295,218 ophthalmology clinical notes with visual acuity data present. About 5668 unique responses were identified and an algorithm was developed to map all of the unique responses to a structured list of Snellen visual acuities. Visual acuity was captured from a total of 295,218 ophthalmology clinical notes during the study dates. The algorithm identified all visual acuities in the defined visual acuity section for each eye and returned a single BDVA for each eye. A clinician chart review of 100 random patient notes showed a 99% accuracy detecting BDVA from these records and 1% observed error. Our algorithm successfully captures best documented Snellen distance visual acuity from ophthalmology clinical notes and transforms a variety of inputs into a structured Snellen equivalent list. Our work, to the best of our knowledge, represents the first attempt at capturing visual acuity accurately from large numbers of electronic ophthalmology notes. Use of this algorithm can benefit research groups interested in assessing visual acuity for patient centered outcome. All codes used for this study are currently available, and will be made available online at https://phekb.org.

Satellite myths

Science.gov (United States)

Easton, Roger L.; Hall, David

2008-01-01

Richard Corfield's article “Sputnik's legacy” (October 2007 pp23-27) states that the satellite on board the US Vanguard rocket, which exploded during launch on 6 December 1957 two months after Sputnik's successful take-off, was “a hastily put together contraption of wires and circuitry designed only to send a radio signal back to Earth”. In fact, the Vanguard satellite was developed over a period of several years and put together carefully using the best techniques and equipment available at the time - such as transistors from Bell Laboratories/Western Electric. The satellite contained not one but two transmitters, in which the crystal-controlled oscillators had been designed to measure both the temperature of the satellite shell and of the internal package.

Communication satellite applications

Science.gov (United States)

Pelton, Joseph N.

The status and future of the technologies, numbers and services provided by communications satellites worldwide are explored. The evolution of Intelsat satellites and the associated earth terminals toward high-rate all-digital telephony, data, facsimile, videophone, videoconferencing and DBS capabilities are described. The capabilities, services and usage of the Intersputnik, Eutelsat, Arabsat and Palapa systems are also outlined. Domestic satellite communications by means of the Molniya, ANIK, Olympus, Intelsat and Palapa spacecraft are outlined, noting the fast growth of the market and the growing number of different satellite manufacturers. The technical, economic and service definition issues surrounding DBS systems are discussed, along with presently operating and planned maritime and aeronautical communications and positioning systems. Features of search and rescue and tracking, data, and relay satellite systems are summarized, and services offered or which will be offered by every existing or planned communication satellite worldwide are tabulated.

Onsets of Solar Proton Events in Satellite and Ground Level Observations: A Comparison

Science.gov (United States)

He, Jing; Rodriguez, Juan V.

2018-03-01

The early detection of solar proton event onsets is essential for protecting humans and electronics in space, as well as passengers and crew at aviation altitudes. Two commonly compared methods for observing solar proton events that are sufficiently large and energetic to be detected on the ground through the creation of secondary radiation—known as ground level enhancements (GLEs)—are (1) a network of ground-based neutron monitors (NMs) and (2) satellite-based particle detectors. Until recently, owing to the different time resolution of the two data sets, it has not been feasible to compare these two types of observations using the same detection algorithm. This paper presents a comparison between the two observational platforms using newly processed >100 MeV 1 min count rates and fluxes from National Oceanic and Atmospheric Administration's Geostationary Operational Environmental Satellite (GOES) 8-12 satellites, and 1 min count rates from the Neutron Monitor Database. We applied the same detection algorithm to each data set (tuned to the different background noise levels of the instrument types). Seventeen SPEs with GLEs were studied: GLEs 55-70 from Solar Cycle 23 and GLE 71 from Solar Cycle 24. The median difference in the event detection times by GOES and NM data is 0 min, indicating no innate benefit in time of either system. The 10th, 25th, 75th, and 90th percentiles of the onset time differences (GOES minus NMs) are -7.2 min, -1.5 min, 2.5 min, and 4.2 min, respectively. This is in contrast to previous studies in which NM detections led GOES by 8 to 52 min without accounting for different alert protocols.

The growing impact of satellite data in daily life

Science.gov (United States)

Stramondo, Salvatore

2015-04-01

Satellite images have a growing role in our daily life. Weather previsions, telecommunications, environmental planning, disaster mitigation and monitoring: these are only some of the fieldworks where space remote sensing data, and related processing techniques, provide extremely useful information to policy/decision makers, scientists, or to the "simple" citizen. The demonstration of the level of attention provided by the International Community to the impact of new technologies and satellite Earth Observation, in particular, onto everyday life is testified by the recent and forthcoming project calls. Horizon 2020, for instance, identified "Societal challenges" and "Science with and for Society" among the main pillars. In sub-themes we may read references to the "Environment", "Secure societies", "Climate changes", and many others, most of which soliciting the use of remote sensing technologies. In such scenario the scientists should be conscious about the capabilities and the implications in applying new technologies. Recent examples might be explanatory. Satellite data properly managed can be used to measure millimetric and/or centimetric movements of buildings and infrastructures. It has been demonstrated how long term monitoring of urban areas detecting pre-collapse deformations might provide useful hints to prevent such dramatic events. Or, in different frameworks, satellite data can be an advanced instrument for intelligence and military purposes. With such premises, ethic issues assume a key role to properly address the use of satellite technologies.

Detecting oscillatory patterns and time lags from proxy records with non-uniform sampling: Some pitfalls and possible solutions

Science.gov (United States)

Donner, Reik

2013-04-01

Time series analysis offers a rich toolbox for deciphering information from high-resolution geological and geomorphological archives and linking the thus obtained results to distinct climate and environmental processes. Specifically, on various time-scales from inter-annual to multi-millenial, underlying driving forces exhibit more or less periodic oscillations, the detection of which in proxy records often allows linking them to specific mechanisms by which the corresponding drivers may have affected the archive under study. A persistent problem in geomorphology is that available records do not present a clear signal of the variability of environmental conditions, but exhibit considerable uncertainties of both the measured proxy variables and the associated age model. Particularly, time-scale uncertainty as well as the heterogeneity of sampling in the time domain are source of severe conceptual problems that may lead to false conclusions about the presence or absence of oscillatory patterns and their mutual phasing in different archives. In my presentation, I will discuss how one can cope with non-uniformly sampled proxy records to detect and quantify oscillatory patterns in one or more data sets. For this purpose, correlation analysis is reformulated using kernel estimates which are found superior to classical estimators based on interpolation or Fourier transform techniques. In order to characterize non-stationary or noisy periodicities and their relative phasing between different records, an extension of continuous wavelet transform is utilized. The performance of both methods is illustrated for different case studies. An extension to explicitly considering time-scale uncertainties by means of Bayesian techniques is briefly outlined.

Combined Geometric and Neural Network Approach to Generic Fault Diagnosis in Satellite Reaction Wheels

DEFF Research Database (Denmark)

Baldi, P.; Blanke, Mogens; Castaldi, P.

2015-01-01

This paper suggests a novel diagnosis scheme for detection, isolation and estimation of faults affecting satellite reaction wheels. Both spin rate measurements and actuation torque defects are dealt with. The proposed system consists of a fault detection and isolation module composed by a bank of...

Micro-satellite for space debris observation by optical sensors

Science.gov (United States)

Thillot, Marc; Brenière, Xavier; Midavaine, Thierry

2017-11-01

The purpose of this theoretical study carried out under CNES contract is to analyze the feasibility of small space debris detection and classification with an optical sensor on-board micro-satellite. Technical solutions based on active and passive sensors are analyzed and compared. For the most appropriated concept an optimization was made and theoretical performances in terms of number of detection versus class of diameter were calculated. Finally we give some preliminary physical sensor features to illustrate the concept (weight, volume, consumption,…).

History of Satellite TV Broadcasting and Satellite Broadcasting Market in Turkey

Directory of Open Access Journals (Sweden)

Mihalis KUYUCU

2015-09-01

Full Text Available The present study analyses the satellite broadcasting that is the first important development that emerged as a result of digitalization in communication technologies and its reflections in Turkey. As the first milestone in the globalization of television broadcasting, satellite broadcasting provided substantial contribution towards the development of the media. Satellite bro adcasting both increased the broadcasting quality and geographical coverage of the television media. A conceptual study was carried out in the first part of the study in connection with the history of satellite broadcasting in Turkey and across the world. In the research part of the study, an analysis was performed on 160 television channels that broadcast in Turkey via Turksat Satellite. Economic structure of the television channels broadcasting in Turkey via satellite was studied and an analysis was perfo rmed on the operational structure of the channels. As a result of the study, it was emphasized that the television channels broadcasting via satellite platform also use other platforms for the purpose of spreading their broadcasts and television channel ow ners make investments in different branches of the media, too. Capital owners invest in different business areas other than the media although television channels broadcasting via Turksat mostly focus on thematic broadcasting and make effort to generate ec onomic income from advertisements. Delays are encountered in the course of the convergence between the new media and television channels that broadcast only from the satellite platform and such television channels experience more economic problems than the other channels. New media and many TV broadcasting platforms emerged as a result of the developments in the communication technologies. In television broadcasting, satellite platform is not an effective platform on its own. Channels make effort to reach t o more people by using other platforms in addition to

VHR satellite imagery for humanitarian crisis management: a case study

Science.gov (United States)

Bitelli, Gabriele; Eleias, Magdalena; Franci, Francesca; Mandanici, Emanuele

2017-09-01

During the last years, remote sensing data along with GIS have been largely employed for supporting emergency management activities. In this context, the use of satellite images and derived map products has become more common also in the different phases of humanitarian crisis response. In this work very high resolution satellite imagery was processed to assess the evolution of Za'atari Refugee Camp, built in Jordan in 2012 by the UN Refugee Agency to host Syrian refugees. Multispectral satellite scenes of the Za'atari area were processed by means of object-based classifications. The main aim of the present work is the development of a semiautomated procedure for multi-temporal camp monitoring with particular reference to the dwellings detection. Whilst in the emergency mapping domain automation of feature extraction is widely investigated, in the field of humanitarian missions the information is often extracted by means of photointerpretation of the satellite data. This approach requires time for the interpretation; moreover, it is not reliable enough in complex situations, where features of interest are often small, heterogeneous and inconsistent. Therefore, the present paper discusses a methodology to obtain information for assisting humanitarian crisis management, using a semi-automatic classification approach applied to satellite imagery.

Relative tracking control of constellation satellites considering inter-satellite link

Science.gov (United States)

Fakoor, M.; Amozegary, F.; Bakhtiari, M.; Daneshjou, K.

2017-11-01

In this article, two main issues related to the large-scale relative motion of satellites in the constellation are investigated to establish the Inter Satellite Link (ISL) which means the dynamic and control problems. In the section related to dynamic problems, a detailed and effective analytical solution is initially provided for the problem of satellite relative motion considering perturbations. The direct geometric method utilizing spherical coordinates is employed to achieve this solution. The evaluation of simulation shows that the solution obtained from the geometric method calculates the relative motion of the satellite with high accuracy. Thus, the proposed analytical solution will be applicable and effective. In the section related to control problems, the relative tracking control system between two satellites will be designed in order to establish a communication link between the satellites utilizing analytical solution for relative motion of satellites with respect to the reference trajectory. Sliding mode control approach is employed to develop the relative tracking control system for body to body and payload to payload tracking control. Efficiency of sliding mode control approach is compared with PID and LQR controllers. Two types of payload to payload tracking control considering with and without payload degree of freedom are designed and suitable one for practical ISL applications is introduced. Also, Fuzzy controller is utilized to eliminate the control input in the sliding mode controller.

Mobile satellite service communications tests using a NASA satellite

Science.gov (United States)

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

1995-01-01

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

Satellite Geomagnetism

DEFF Research Database (Denmark)

Olsen, Nils; Stolle, Claudia

2012-01-01

Observations of Earth’s magnetic field from space began more than 50 years ago. A continuous monitoring of the field using low Earth orbit (LEO) satellites, however, started only in 1999, and three satellites have taken highprecision measurements of the geomagnetic field during the past decade....... The unprecedented time-space coverage of their data opened revolutionary new possibilities for monitoring, understanding, and exploring Earth’s magnetic field. In the near future, the three-satellite constellation Swarm will ensure continuity of such measurement and provide enhanced possibilities to improve our...... ability to characterize and understand the many sources that contribute to Earth’s magnetic field. In this review, we summarize investigations of Earth’s interior and environment that have been possible through the analysis of high-precision magnetic field observations taken by LEO satellites....

An orbit determination algorithm for small satellites based on the magnitude of the earth magnetic field

Science.gov (United States)

Zagorski, P.; Gallina, A.; Rachucki, J.; Moczala, B.; Zietek, S.; Uhl, T.

2018-06-01

Autonomous attitude determination systems based on simple measurements of vector quantities such as magnetic field and the Sun direction are commonly used in very small satellites. However, those systems always require knowledge of the satellite position. This information can be either propagated from orbital elements periodically uplinked from the ground station or measured onboard by dedicated global positioning system (GPS) receiver. The former solution sacrifices satellite autonomy while the latter requires additional sensors which may represent a significant part of mass, volume, and power budget in case of pico- or nanosatellites. Hence, it is thought that a system for onboard satellite position determination without resorting to GPS receivers would be useful. In this paper, a novel algorithm for determining the satellite orbit semimajor-axis is presented. The methods exploit only the magnitude of the Earth magnetic field recorded onboard by magnetometers. This represents the first step toward an extended algorithm that can determine all orbital elements of the satellite. The method is validated by numerical analysis and real magnetic field measurements.

New Methods for Air Quality Model Evaluation with Satellite Data

Science.gov (United States)

Holloway, T.; Harkey, M.

2015-12-01

Despite major advances in the ability of satellites to detect gases and aerosols in the atmosphere, there remains significant, untapped potential to apply space-based data to air quality regulatory applications. Here, we showcase research findings geared toward increasing the relevance of satellite data to support operational air quality management, focused on model evaluation. Particular emphasis is given to nitrogen dioxide (NO2) and formaldehyde (HCHO) from the Ozone Monitoring Instrument aboard the NASA Aura satellite, and evaluation of simulations from the EPA Community Multiscale Air Quality (CMAQ) model. This work is part of the NASA Air Quality Applied Sciences Team (AQAST), and is motivated by ongoing dialog with state and federal air quality management agencies. We present the response of satellite-derived NO2 to meteorological conditions, satellite-derived HCHO:NO2 ratios as an indicator of ozone production regime, and the ability of models to capture these sensitivities over the continental U.S. In the case of NO2-weather sensitivities, we find boundary layer height, wind speed, temperature, and relative humidity to be the most important variables in determining near-surface NO2 variability. CMAQ agreed with relationships observed in satellite data, as well as in ground-based data, over most regions. However, we find that the southwest U.S. is a problem area for CMAQ, where modeled NO2 responses to insolation, boundary layer height, and other variables are at odds with the observations. Our analyses utilize a software developed by our team, the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS): a free, open-source program designed to make satellite-derived air quality data more usable. WHIPS interpolates level 2 satellite retrievals onto a user-defined fixed grid, in effect creating custom-gridded level 3 satellite product. Currently, WHIPS can process the following data products: OMI NO2 (NASA retrieval); OMI NO2 (KNMI retrieval); OMI

Validation of ozone profile retrievals derived from the OMPS LP version 2.5 algorithm against correlative satellite measurements

Science.gov (United States)

Kramarova, Natalya A.; Bhartia, Pawan K.; Jaross, Glen; Moy, Leslie; Xu, Philippe; Chen, Zhong; DeLand, Matthew; Froidevaux, Lucien; Livesey, Nathaniel; Degenstein, Douglas; Bourassa, Adam; Walker, Kaley A.; Sheese, Patrick

2018-05-01

The Limb Profiler (LP) is a part of the Ozone Mapping and Profiler Suite launched on board of the Suomi NPP satellite in October 2011. The LP measures solar radiation scattered from the atmospheric limb in ultraviolet and visible spectral ranges between the surface and 80 km. These measurements of scattered solar radiances allow for the retrieval of ozone profiles from cloud tops up to 55 km. The LP started operational observations in April 2012. In this study we evaluate more than 5.5 years of ozone profile measurements from the OMPS LP processed with the new NASA GSFC version 2.5 retrieval algorithm. We provide a brief description of the key changes that had been implemented in this new algorithm, including a pointing correction, new cloud height detection, explicit aerosol correction and a reduction of the number of wavelengths used in the retrievals. The OMPS LP ozone retrievals have been compared with independent satellite profile measurements obtained from the Aura Microwave Limb Sounder (MLS), Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) and Odin Optical Spectrograph and InfraRed Imaging System (OSIRIS). We document observed biases and seasonal differences and evaluate the stability of the version 2.5 ozone record over 5.5 years. Our analysis indicates that the mean differences between LP and correlative measurements are well within required ±10 % between 18 and 42 km. In the upper stratosphere and lower mesosphere (> 43 km) LP tends to have a negative bias. We find larger biases in the lower stratosphere and upper troposphere, but LP ozone retrievals have significantly improved in version 2.5 compared to version 2 due to the implemented aerosol correction. In the northern high latitudes we observe larger biases between 20 and 32 km due to the remaining thermal sensitivity issue. Our analysis shows that LP ozone retrievals agree well with the correlative satellite observations in characterizing vertical, spatial and temporal

Interim Service ISDN Satellite (ISIS) simulator development for advanced satellite designs and experiments

Science.gov (United States)

Pepin, Gerard R.

1992-01-01

The simulation development associated with the network models of both the Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) and the Full Service ISDN Satellite (FSIS) architectures is documented. The ISIS Network Model design represents satellite systems like the Advanced Communications Technology Satellite (ACTS) orbiting switch. The FSIS architecture, the ultimate aim of this element of the Satellite Communications Applications Research (SCAR) Program, moves all control and switching functions on-board the next generation ISDN communications satellite. The technical and operational parameters for the advanced ISDN communications satellite design will be obtained from the simulation of ISIS and FSIS engineering software models for their major subsystems. Discrete event simulation experiments will be performed with these models using various traffic scenarios, design parameters, and operational procedures. The data from these simulations will be used to determine the engineering parameters for the advanced ISDN communications satellite.

Direct Satellite Data Acquisition and its Application for Large -scale Monitoring Projects in Russia

Science.gov (United States)

Gershenzon, O.

2011-12-01

ScanEx RDC created an infrastructure (ground stations network) to acquire and process remote sensing data from different satellites: Terra, Aqua, Landsat, IRS-P5/P6, SPOT 4/5, FORMOSAT-2, EROS A/B, RADARSAT-1/2, ENVISAT-1. It owns image archives from these satellites as well as from SPOT-2 and CARTOSAT-2. ScanEx RDC builds and delivers remote sensing ground stations (working with up to 15 satellites); and owns the ground stations network to acquire data for Russia and surrounding territory. ScanEx stations are the basic component in departmental networks of remote sensing data acquisition for different state authorities (Roshydromet, Ministry of Natural Recourses, Emercom) and University- based remote sensing data acquisition and processing centers in Russia and abroad. ScanEx performs large-scale projects in collaboration with government agencies to monitor forests, floods, fires, sea surface pollution, and ice situation in Northern Russia. During 2010-2011 ScanEx conducted daily monitoring of wild fires in Russia detecting and registering thermal anomalies using data from Terra, Aqua, Landsat and SPOT satellites. Detailed SPOT 4/5 data is used to analyze burnt areas and to assess damage caused by fire. Satellite data along with other information about fire situation in Russia was daily updated and published via free-access Internet geoportal. A few projects ScanEx conducted together with environmental NGO. Project "Satellite monitoring of Especially Protected Natural Areas of Russia and its results visualization on geoportal was conducted in cooperation with NGO "Transparent World". The project's goal was to observe natural phenomena and economical activity, including illegal, by means of Earth remote sensing data. Monitoring is based on multi-temporal optical space imagery of different spatial resolution. Project results include detection of anthropogenic objects that appeared in the vicinity or even within the border of natural territories, that have never been

Satellite monitoring of cyanobacterial harmful algal bloom ...

Science.gov (United States)

Cyanobacterial harmful algal blooms (cyanoHABs) cause extensive problems in lakes worldwide, including human and ecological health risks, anoxia and fish kills, and taste and odor problems. CyanoHABs are a particular concern because of their dense biomass and the risk of exposure to toxins in both recreational waters and drinking source waters. Successful cyanoHAB assessment by satellites may provide a first-line of defense indicator for human and ecological health protection. In this study, assessment methods were developed to determine the utility of satellite technology for detecting cyanoHAB occurrence frequency at locations of potential management interest. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was evaluated to prepare for the equivalent Sentinel-3 Ocean and Land Colour Imager (OLCI) launched in 2016. Based on the 2012 National Lakes Assessment site evaluation guidelines and National Hydrography Dataset, there were 275,897 lakes and reservoirs greater than 1 hectare in the 48 U.S. states. Results from this evaluation show that 5.6 % of waterbodies were resolvable by satellites with 300 m single pixel resolution and 0.7 % of waterbodies were resolvable when a 3x3 pixel array was applied based on minimum Euclidian distance from shore. Satellite data was also spatially joined to US public water surface intake (PWSI) locations, where single pixel resolution resolved 57% of PWSI and a 3x3 pixel array resolved 33% of

Simulation of TanDEM-X interferograms for urban change detection

Science.gov (United States)

Welte, Amelie; Hammer, Horst; Thiele, Antje; Hinz, Stefan

2017-10-01

Damage detection after natural disasters is one of the remote sensing tasks in which Synthetic Aperture Radar (SAR) sensors play an important role. Since SAR is an active sensor, it can record images at all times of day and in all weather conditions, making it ideally suited for this task. While with the newer generation of SAR satellites such as TerraSAR-X or COSMOSkyMed amplitude change detection has become possible even for urban areas, interferometric phase change detection has not been published widely. This is mainly because of the long revisit times of common SAR sensors leading to temporal decorrelation. This situation has changed dramatically with the advent of the TanDEM-X constellation, which can create single-pass interferograms from space at very high resolutions, avoiding temporal decorrelation almost completely. In this paper the basic structures that are present for any building in InSAR phases, i.e. layover, shadow, and roof areas, are examined. Approaches for their extraction from TanDEM-X interferograms are developed using simulated SAR interferograms. The extracted features of the building signature will in the future be used for urban change detection in real TanDEM-X High Resolution Spotlight interferograms.

Handbook of satellite applications

CERN Document Server

Madry, Scott; Camacho-Lara, Sergio

2017-01-01

The first edition of this ground breaking reference work was the most comprehensive reference source available about the key aspects of the satellite applications field. This updated second edition covers the technology, the markets, applications and regulations related to satellite telecommunications, broadcasting and networking—including civilian and military systems; precise satellite navigation and timing networks (i.e. GPS and others); remote sensing and meteorological satellite systems. Created under the auspices of the International Space University based in France, this brand new edition is now expanded to cover new innovative small satellite constellations, new commercial launching systems, innovation in military application satellites and their acquisition, updated appendices, a useful glossary and more.

Satellite image collection optimization

Science.gov (United States)

Martin, William

2002-09-01

Imaging satellite systems represent a high capital cost. Optimizing the collection of images is critical for both satisfying customer orders and building a sustainable satellite operations business. We describe the functions of an operational, multivariable, time dynamic optimization system that maximizes the daily collection of satellite images. A graphical user interface allows the operator to quickly see the results of what if adjustments to an image collection plan. Used for both long range planning and daily collection scheduling of Space Imaging's IKONOS satellite, the satellite control and tasking (SCT) software allows collection commands to be altered up to 10 min before upload to the satellite.

Threshold-based system for noise detection in multilead ECG recordings

International Nuclear Information System (INIS)

Jekova, Irena; Krasteva, Vessela; Christov, Ivaylo; Abächerli, Roger

2012-01-01

This paper presents a system for detection of the most common noise types seen on the electrocardiogram (ECG) in order to evaluate whether an episode from 12-lead ECG is reliable for diagnosis. It implements criteria for estimation of the noise corruption level in specific frequency bands, aiming to identify the main sources of ECG quality disruption, such as missing signal or limited dynamics of the QRS components above 4 Hz; presence of high amplitude and steep artifacts seen above 1 Hz; baseline drift estimated at frequencies below 1 Hz; power–line interference in a band ±2 Hz around its central frequency; high-frequency and electromyographic noises above 20 Hz. All noise tests are designed to process the ECG series in the time domain, including 13 adjustable thresholds for amplitude and slope criteria which are evaluated in adjustable time intervals, as well as number of leads. The system allows flexible extension toward application-specific requirements for the noise levels in acceptable quality ECGs. Training of different thresholds’ settings to determine different positive noise detection rates is performed with the annotated set of 1000 ECGs from the PhysioNet database created for the Computing in Cardiology Challenge 2011. Two implementations are highlighted on the receiver operating characteristic (area 0.968) to fit to different applications. The implementation with high sensitivity (Se = 98.7%, Sp = 80.9%) appears as a reliable alarm when there are any incidental problems with the ECG acquisition, while the implementation with high specificity (Sp = 97.8%, Se = 81.8%) is less susceptible to transient problems but rather validates noisy ECGs with acceptable quality during a small portion of the recording. (paper)

NOAA Climate Data Record (CDR) of Gridded Satellite Data from ISCCP B1 (GridSat-B1) Infrared Channel Brightness Temperature, Version 2

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Gridded Satellite (GridSat-B1) data provides a uniform set of quality controlled geostationary satellite observations for the visible, infrared window and...

Wave excitation in the experiment with an electron beam at the Dzhajkiken Exos-B Japanese satellite

International Nuclear Information System (INIS)

Kavashima, N.

1985-01-01

An experiment on investigation of beam-plasma interaction in the magnetosphere is carried out at the ''Dzhajkiken (Exos-B)'' japanese satellite. 100-200 eV and 0.25-1 μA electron beam was injected into the magnetosphere. Using LF and HF detectors in low altitude range waves with the frequencies close to the upper hybrid and electron frequencies are recorded. Beyond the plasmapause the satellite was charged to the potential corresponding to the beam energy

Detecting settlement expansion using hyper-temporal SAR time-series

CSIR Research Space (South Africa)

Kleynhans, W

2014-07-01

Full Text Available The detection of new informal settlements in South Africa using time-series data derived from coarse resolution satellite imagery has recently been an active area of research. Most of the previous methods presented using hyper-temporal satellite...

Observations of urban and suburban environments with global satellite scatterometer data

Science.gov (United States)

Nghiem, S. V.; Balk, D.; Rodriguez, E.; Neumann, G.; Sorichetta, A.; Small, C.; Elvidge, C. D.

A global and consistent characterization of land use and land change in urban and suburban environments is crucial for many fundamental social and natural science studies and applications. Presented here is a dense sampling method (DSM) that uses satellite scatterometer data to delineate urban and intraurban areas at a posting scale of about 1 km. DSM results are analyzed together with information on population and housing censuses, with Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, and with Defense Meteorological Satellite Program (DMSP) night-light data. The analyses include Dallas-Fort Worth and Phoenix in the United States, Bogotá in Colombia, Dhaka in Bangladesh, Guangzhou in China, and Quito in Ecuador. Results show that scatterometer signatures correspond to buildings and infrastructures in urban and suburban environments. City extents detected by scatterometer data are significantly smaller than city light extents, but not all urban areas are detectable by the current SeaWinds scatterometer on the QuikSCAT satellite. Core commercial and industrial areas with high buildings and large factories are identified as high-backscatter centers. Data from DSM backscatter and DMSP nighttime lights have a good correlation with population density. However, the correlation relations from the two satellite datasets are different for different cities indicating that they contain complementary information. Together with night-light and census data, DSM and satellite scatterometer data provide new observations to study global urban and suburban environments and their changes. Furthermore, the capability of DSM to identify hydrological channels on the Greenland ice sheet and ecological biomes in central Africa demonstrates that DSM can be used to observe persistent structures in natural environments at a km scale, providing contemporaneous data to study human impacts beyond urban and suburban areas.

Computing and Visualizing Reachable Volumes for Maneuvering Satellites

Science.gov (United States)

Jiang, M.; de Vries, W.; Pertica, A.; Olivier, S.

2011-09-01

Detecting and predicting maneuvering satellites is an important problem for Space Situational Awareness. The spatial envelope of all possible locations within reach of such a maneuvering satellite is known as the Reachable Volume (RV). As soon as custody of a satellite is lost, calculating the RV and its subsequent time evolution is a critical component in the rapid recovery of the satellite. In this paper, we present a Monte Carlo approach to computing the RV for a given object. Essentially, our approach samples all possible trajectories by randomizing thrust-vectors, thrust magnitudes and time of burn. At any given instance, the distribution of the "point-cloud" of the virtual particles defines the RV. For short orbital time-scales, the temporal evolution of the point-cloud can result in complex, multi-reentrant manifolds. Visualization plays an important role in gaining insight and understanding into this complex and evolving manifold. In the second part of this paper, we focus on how to effectively visualize the large number of virtual trajectories and the computed RV. We present a real-time out-of-core rendering technique for visualizing the large number of virtual trajectories. We also examine different techniques for visualizing the computed volume of probability density distribution, including volume slicing, convex hull and isosurfacing. We compare and contrast these techniques in terms of computational cost and visualization effectiveness, and describe the main implementation issues encountered during our development process. Finally, we will present some of the results from our end-to-end system for computing and visualizing RVs using examples of maneuvering satellites.

Computing and Visualizing Reachable Volumes for Maneuvering Satellites

International Nuclear Information System (INIS)

Jiang, M.; de Vries, W.H.; Pertica, A.J.; Olivier, S.S.

2011-01-01

Detecting and predicting maneuvering satellites is an important problem for Space Situational Awareness. The spatial envelope of all possible locations within reach of such a maneuvering satellite is known as the Reachable Volume (RV). As soon as custody of a satellite is lost, calculating the RV and its subsequent time evolution is a critical component in the rapid recovery of the satellite. In this paper, we present a Monte Carlo approach to computing the RV for a given object. Essentially, our approach samples all possible trajectories by randomizing thrust-vectors, thrust magnitudes and time of burn. At any given instance, the distribution of the 'point-cloud' of the virtual particles defines the RV. For short orbital time-scales, the temporal evolution of the point-cloud can result in complex, multi-reentrant manifolds. Visualization plays an important role in gaining insight and understanding into this complex and evolving manifold. In the second part of this paper, we focus on how to effectively visualize the large number of virtual trajectories and the computed RV. We present a real-time out-of-core rendering technique for visualizing the large number of virtual trajectories. We also examine different techniques for visualizing the computed volume of probability density distribution, including volume slicing, convex hull and isosurfacing. We compare and contrast these techniques in terms of computational cost and visualization effectiveness, and describe the main implementation issues encountered during our development process. Finally, we will present some of the results from our end-to-end system for computing and visualizing RVs using examples of maneuvering satellites.

Field and Satellite Observations of the Formation and Distribution of Arctic Atmospheric Bromine Above a Rejuvenated Sea Ice Cover

Science.gov (United States)

Nghiem, Son V.; Rigor, Ignatius G.; Richter, Andreas; Burrows, John P.; Shepson, Paul B.; Bottenheim, Jan; Barber, David G.; Steffen, Alexandra; Latonas, Jeff; Wang, Feiyue;

Global change. Taking stock of a catastrophe. The use of satellite data for environmental protection and in developing countries

International Nuclear Information System (INIS)

Anon.

1993-10-01

The individual contributions deal primarily with the development of the climate; they want to render environmental processes transparent. Satellite data play an important part in forecasts of climate development: only satellites permit to realize the global dimension of climate. The numerous illustrations in the form of satellite images are to aid thinking in global dimensions. The use of environment satellites is a step beyond climate research. Further contributions discuss the uses of environment satellites during nature disasters, for the detection of environmental polluters and for the analysis of forest die-back in industrialized countries or rainforest clearfelling in the Amazon region. (KW) [de

Automatic Cloud and Shadow Detection in Optical Satellite Imagery Without Using Thermal Bands—Application to Suomi NPP VIIRS Images over Fennoscandia

Directory of Open Access Journals (Sweden)

Eija Parmes

2017-08-01

Full Text Available In land monitoring applications, clouds and shadows are considered noise that should be removed as automatically and quickly as possible, before further analysis. This paper presents a method to detect clouds and shadows in Suomi NPP satellite’s VIIRS (Visible Infrared Imaging Radiometer Suite satellite images. The proposed cloud and shadow detection method has two distinct features when compared to many other methods. First, the method does not use the thermal bands and can thus be applied to other sensors which do not contain thermal channels, such as Sentinel-2 data. Secondly, the method uses the ratio between blue and green reflectance to detect shadows. Seven hundred and forty-seven VIIRS images over Fennoscandia from August 2014 to April 2016 were processed to train and develop the method. Twenty four points from every tenth of the images were used in accuracy assessment. These 1752 points were interpreted visually to cloud, cloud shadow and clear classes, then compared to the output of the cloud and shadow detection. The comparison on VIIRS images showed 94.2% correct detection rates and 11.1% false alarms for clouds, and respectively 36.1% and 82.7% for shadows. The results on cloud detection were similar to state-of-the-art methods. Shadows showed correctly on the northern edge of the clouds, but many shadows were wrongly assigned to other classes in some cases (e.g., to water class on lake and forest boundary, or with shadows over cloud. This may be due to the low spatial resolution of VIIRS images, where shadows are only a few pixels wide and contain lots of mixed pixels.

The DNSC08GRA global marine gravity field from double retracked satellite altimetry

DEFF Research Database (Denmark)

Andersen, Ole Baltazar; Knudsen, Per; Berry, P.A.M.

2010-01-01

Satellite radar altimetry has been monitoring the earth's oceans from space for several decades. However, only the GEOSAT and ERS-1 geodetic mission data recorded more than a decade ago provide altimetry with adequate spatial coverage to derive a high-resolution marine gravity field. The original...

Development of a standardized Intranet database of formulation records for nonsterile compounding, Part 2.

Science.gov (United States)

Haile, Michael; Anderson, Kim; Evans, Alex; Crawford, Angela

2012-01-01

In part 1 of this series, we outlined the rationale behind the development of a centralized electronic database used to maintain nonsterile compounding formulation records in the Mission Health System, which is a union of several independent hospitals and satellite and regional pharmacies that form the cornerstone of advanced medical care in several areas of western North Carolina. Hospital providers in many healthcare systems require compounded formulations to meet the needs of their patients (in particular, pediatric patients). Before a centralized electronic compounding database was implemented in the Mission Health System, each satellite or regional pharmacy affiliated with that system had a specific set of formulation records, but no standardized format for those records existed. In this article, we describe the quality control, database platform selection, description, implementation, and execution of our intranet database system, which is designed to maintain, manage, and disseminate nonsterile compounding formulation records in the hospitals and affiliated pharmacies of the Mission Health System. The objectives of that project were to standardize nonsterile compounding formulation records, create a centralized computerized database that would increase healthcare staff members' access to formulation records, establish beyond-use dates based on published stability studies, improve quality control, reduce the potential for medication errors related to compounding medications, and (ultimately) improve patient safety.

Trends in communications satellites

CERN Document Server

Curtin, Denis J

1979-01-01

Trends in Communications Satellites offers a comprehensive look at trends and advances in satellite communications, including experimental ones such as NASA satellites and those jointly developed by France and Germany. The economic aspects of communications satellites are also examined. This book consists of 16 chapters and begins with a discussion on the fundamentals of electrical communications and their application to space communications, including spacecraft, earth stations, and orbit and wavelength utilization. The next section demonstrates how successful commercial satellite communicati

The Infrared Astronomical Satellite (IRAS) mission

Science.gov (United States)

Neugebauer, G.; Habing, H. J.; Van Duinen, R.; Aumann, H. H.; Beichman, C. A.; Baud, B.; Beintema, D. A.; Boggess, N.; Clegg, P. E.; De Jong, T.

1984-01-01

The Infrared Astronomical Satellite (IRAS) consists of a spacecraft and a liquid helium cryostat that contains a cooled IR telescope. The telescope's focal plane assembly is cooled to less than 3 K, and contains 62 IR detectors in the survey array which are arranged so that every source crossing the field of view can be seen by at least two detectors in each of four wavelength bands. The satellite was launched into a 900 km-altitude near-polar orbit, and its cryogenic helium supply was exhausted on November 22, 1983. By mission's end, 72 percent of the sky had been observed with three or more hours-confirming scans, and 95 percent with two or more hours-confirming scans. About 2000 stars detected at 12 and 25 microns early in the mission, and identified in the SAO (1966) catalog, have a positional uncertainty ellipse whose axes are 45 x 9 arcsec for an hours-confirmed source.

A 25-year Record of Antarctic Ice Sheet Elevation and Mass Change

Science.gov (United States)

Shepherd, A.; Muir, A. S.; Sundal, A.; McMillan, M.; Briggs, K.; Hogg, A.; Engdahl, M.; Gilbert, L.

2017-12-01

Since 1992, the European Remote-Sensing (ERS-1 and ERS-2), ENVISAT, and CryoSat-2 satellite radar altimeters have measured the Antarctic ice sheet surface elevation, repeatedly, at approximately monthly intervals. These data constitute the longest continuous record of ice sheet wide change. In this paper, we use these observations to determine changes in the elevation, volume and mass of the East Antarctic and West Antarctic ice sheets, and of parts of the Antarctic Peninsula ice sheet, over a 25-year period. The root mean square difference between elevation rates computed from our survey and 257,296 estimates determined from airborne laser measurements is 54 cm/yr. The longevity of the satellite altimeter data record allows to identify and chart the evolution of changes associated with meteorology and ice flow, and we estimate that 3.6 % of the continental ice sheet, and 21.7 % of West Antarctica, is in a state of dynamical imbalance. Based on this partitioning, we estimate the mass balance of the East and West Antarctic ice sheet drainage basins and the root mean square difference between these and independent estimates derived from satellite gravimetry is less than 5 Gt yr-1.

Structure and performance of a real-time algorithm to detect tsunami or tsunami-like alert conditions based on sea-level records analysis

Directory of Open Access Journals (Sweden)

L. Bressan

2011-05-01

Full Text Available The goal of this paper is to present an original real-time algorithm devised for detection of tsunami or tsunami-like waves we call TEDA (Tsunami Early Detection Algorithm, and to introduce a methodology to evaluate its performance. TEDA works on the sea level records of a single station and implements two distinct modules running concurrently: one to assess the presence of tsunami waves ("tsunami detection" and the other to identify high-amplitude long waves ("secure detection". Both detection methods are based on continuously updated time functions depending on a number of parameters that can be varied according to the application. In order to select the most adequate parameter setting for a given station, a methodology to evaluate TEDA performance has been devised, that is based on a number of indicators and that is simple to use. In this paper an example of TEDA application is given by using data from a tide gauge located at the Adak Island in Alaska, USA, that resulted in being quite suitable since it recorded several tsunamis in the last years using the sampling rate of 1 min.

Theory of satellite geodesy applications of satellites to geodesy

CERN Document Server

Kaula, William M

2000-01-01

The main purpose of this classic text is to demonstrate how Newtonian gravitational theory and Euclidean geometry can be used and developed in the earth's environment. The second is to collect and explain some of the mathematical techniques developed for measuring the earth by satellite.Book chapters include discussions of the earth's gravitational field, with special emphasis on spherical harmonies and the potential of the ellipsoid; matrices and orbital geometry; elliptic motion, linear perturbations, resonance, and other aspects of satellite orbit dynamics; the geometry of satellite obser

IAEA Safeguards: Cost/benefit analysis of commercial satellite imagery

Energy Technology Data Exchange (ETDEWEB)

Andersson, Christer [SSC Satellitbild AB, Kiruna (Sweden)

1999-03-01

A major milestone in the efforts to strengthen the Safeguards System was reached in May 1997 when the Board of Governors approved a `Model Protocol Additional to Safeguards Agreements`. The Protocol provides the legal basis necessary to enhance the Agency`s ability to detect undeclared nuclear material and activities by using information available from open sources to complement the declarations made by Member States. Commercially available high-resolution satellite data has emerged as one potential complementary open information source to support the traditional and extended Safeguard activities of IAEA. This document constitutes a first report from SSC Satellitbild giving the Agency tentative and initial estimates of the potential cost and time-savings possible with the new proposed technology. The initial cost/benefit simulation will be further finalised in the following `Implementation Blueprint` study. The general foundation and starting point for the cost/benefit calculation is to simulate a new efficient and relatively small `imagery unit` within the IAEA, capable of performing advanced image processing as a tool for various safeguards tasks. The image processing capacity is suggested to be task- and interpretation-oriented. The study was performed over a period of 1,5 weeks in late 1998, and is based upon interviews of IAEA staff, reviews of existing IAEA documentation as well as from SSC Satellitbild`s long-standing experience of satellite imagery and field missions. The cost/benefit analysis is based on a spreadsheet simulation of five potential applications of commercial satellite imagery: Reference information; Confirmation of Agency acquired and Member State supplied data; Change detection and on-going monitoring; Assessing open source information available to the Agency; Detecting undeclared activities and undeclared sites. The study confirms that the proposed concept of a relatively small `imagery unit` using high-resolution data will be a sound and

Satellite Control Laboratory

DEFF Research Database (Denmark)

Wisniewski, Rafal; Bak, Thomas

2001-01-01

The Satellite Laboratory at the Department of Control Engineering of Aalborg University (SatLab) is a dynamic motion facility designed for analysis and test of micro spacecraft. A unique feature of the laboratory is that it provides a completely gravity-free environment. A test spacecraft...... of the laboratory is to conduct dynamic tests of the control and attitude determination algorithms during nominal operation and in abnormal conditions. Further it is intended to use SatLab for validation of various algorithms for fault detection, accommodation and supervisory control. Different mission objectives...... can be implemented in the laboratory, e.g. three-axis attitude control, slew manoeuvres, spins stabilization using magnetic actuation and/or reaction wheels. The spacecraft attitude can be determined applying magnetometer measurements...

Satellite DNA Sequences in Canidae and Their Chromosome Distribution in Dog and Red Fox.

Science.gov (United States)

Vozdova, Miluse; Kubickova, Svatava; Cernohorska, Halina; Fröhlich, Jan; Rubes, Jiri

2016-01-01

Satellite DNA is a characteristic component of mammalian centromeric heterochromatin, and a comparative analysis of its evolutionary dynamics can be used for phylogenetic studies. We analysed satellite and satellite-like DNA sequences available in NCBI for 4 species of the family Canidae (red fox, Vulpes vulpes, VVU; domestic dog, Canis familiaris, CFA; arctic fox, Vulpes lagopus, VLA; raccoon dog, Nyctereutes procyonoides procyonoides, NPR) by comparative sequence analysis, which revealed 86-90% intraspecies and 76-79% interspecies similarity. Comparative fluorescence in situ hybridisation in the red fox and dog showed signals of the red fox satellite probe in canine and vulpine autosomal centromeres, on VVUY, B chromosomes, and in the distal parts of VVU9q and VVU10p which were shown to contain nucleolus organiser regions. The CFA satellite probe stained autosomal centromeres only in the dog. The CFA satellite-like DNA did not show any significant sequence similarity with the satellite DNA of any species analysed and was localised to the centromeres of 9 canine chromosome pairs. No significant heterochromatin block was detected on the B chromosomes of the red fox. Our results show extensive heterogeneity of satellite sequences among Canidae and prove close evolutionary relationships between the red and arctic fox. © 2017 S. Karger AG, Basel.

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