Search results for "change detection"

showing 10 items of 68 documents

Correcting AVHRR Long Term Data Record V3 estimated LST from orbital drift effects

2012

Abstract NOAA (National Oceanic and Atmospheric Administration) satellite series is known to suffer from what is known as the orbital drift effect. The Long Term Data Record (LTDR [Pedelty et al., 2007]), which provides AVHRR (Advanced Very High Resolution Radiometer) data from these satellites for the 80s and the 90s, is also affected by this orbital drift. To correct this effect on Land Surface Temperature (LST) time series, a novel method is presented here, which consists in adjusting retrieved LST time series on the basis of statistical information extracted from the time series themselves. This method is as simple and straightforward as possible, in order to be implemented easily for s…

Polynomial regression010504 meteorology & atmospheric sciencesBasis (linear algebra)Series (mathematics)PixelAdvanced very-high-resolution radiometer0211 other engineering and technologiesSoil ScienceGeology02 engineering and technologyResidual01 natural sciences13. Climate actionEnvironmental scienceSatelliteComputers in Earth SciencesChange detection021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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Radiometric correction effects in Landsat multi‐date/multi‐sensor change detection studies

2006

Radiometric corrections serve to remove the effects that alter the spectral characteristics of land features, except for actual changes in ground target, becoming mandatory in multi‐sensor, multi‐date studies. In this paper, we evaluate the effects of two types of radiometric correction methods (absolute and relative) for the determination of land cover changes, using Landsat TM and Landsat ETM+ images. In addition, we present an improvement made to the relative correction method addressed. Absolute correction includes a cross‐calibration between TM and ETM+ images, and the application of an atmospheric correction protocol. Relative correction normalizes the images using pseudo‐invariant fe…

Oceanografía Hidrología Recursos HídricosRadiometric correctionRadiometric correctionLand cover changeCiencias de la Tierra y relacionadas con el Medio AmbienteMulti sensorGeographyThematic MapperLandsat TMGeneral Earth and Planetary Sciencespseudo‐invariant featuresCIENCIAS NATURALES Y EXACTASChange detectionRemote sensingInternational Journal of Remote Sensing
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The attentional blink demonstrates automatic deviance processing in vision.

2011

Rare deviations in serial visual stimulation are accompanied by an occipital N2 in the event-related potential [the visual mismatch negativity (vMMN)]. Recent research suggests that the vMMN reflects automatic processing of information on the sensory level as a basis for change detection. To directly test the hypothesis that the vMMN is independent from attention, a rapid-serial-visual-presentation paradigm was applied: Either 300 ms or 700 ms after the presentation of a target (T1) a rare position change was embedded in the stimulation which elicited a vMMN. In another condition participants had to detect a second target (T2) after T1: Importantly, within 300 ms after T1, T2 detection was …

AdultCerebral CortexMaleGeneral NeuroscienceMismatch negativityAutomatic processingDeviance (statistics)Attentional BlinkReaction TimeVisual PerceptionHumansAttentional blinkFemalePsychologySensory levelEvoked PotentialsChange detectionPhotic StimulationVision OcularCognitive psychologyNeuroreport
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A support vector domain method for change detection in multitemporal images

2010

This paper formulates the problem of distinguishing changed from unchanged pixels in multitemporal remote sensing images as a minimum enclosing ball (MEB) problem with changed pixels as target class. The definition of the sphere-shaped decision boundary with minimal volume that embraces changed pixels is approached in the context of the support vector formalism adopting a support vector domain description (SVDD) one-class classifier. SVDD maps the data into a high dimensional feature space where the spherical support of the high dimensional distribution of changed pixels is computed. Unlike the standard SVDD, the proposed formulation of the SVDD uses both target and outlier samples for defi…

PixelComputer sciencebusiness.industryFeature vectorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONThresholdingMultispectral pattern recognitionSupport vector machineKernel methodArtificial IntelligenceComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingOutlierDecision boundaryComputer visionComputer Vision and Pattern RecognitionArtificial intelligencebusinessSoftwareChange detectionPattern Recognition Letters
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Discovering single classes in remote sensing images with active learning

2012

When dealing with supervised target detection, the acquisition of labeled samples is one of the most critical phases: the samples must be yet representative of the class of interest, but must also be found among a vast majority of non-target examples. Moreover, the efficiency of the search is also an issue, since the samples labeled as background are not used by target detectors such as the support vector data description (SVDD). In this work we propose a competitive and effective approach to identify the most relevant training samples for one-class classification based on the use of an active learning strategy. The SVDD classifier is first trained with insufficient target examples. It is t…

Active learningComputer scienceActive learning (machine learning)business.industryPattern recognitionSemi-supervised learningRemote sensingMachine learningcomputer.software_genreSupport vector machineActive learningLife ScienceSupport Vector Data DescriptionArtificial intelligencebusinessClassifier (UML)computerChange detection2012 IEEE International Geoscience and Remote Sensing Symposium
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Kernel Anomalous Change Detection for Remote Sensing Imagery

2020

Anomalous change detection (ACD) is an important problem in remote sensing image processing. Detecting not only pervasive but also anomalous or extreme changes has many applications for which methodologies are available. This paper introduces a nonlinear extension of a full family of anomalous change detectors. In particular, we focus on algorithms that utilize Gaussian and elliptically contoured (EC) distribution and extend them to their nonlinear counterparts based on the theory of reproducing kernels' Hilbert space. We illustrate the performance of the kernel methods introduced in both pervasive and ACD problems with real and simulated changes in multispectral and hyperspectral imagery w…

FOS: Computer and information sciencesComputer scienceGaussianComputer Vision and Pattern Recognition (cs.CV)Multispectral imageComputer Science - Computer Vision and Pattern Recognition0211 other engineering and technologiesMachine Learning (stat.ML)02 engineering and technologysymbols.namesakeStatistics - Machine LearningElectrical and Electronic Engineering021101 geological & geomatics engineeringbusiness.industryHilbert spaceHyperspectral imagingPattern recognitionNonlinear systemKernel methodKernel (image processing)13. Climate actionsymbolsGeneral Earth and Planetary SciencesArtificial intelligencebusinessChange detection
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Automatic processing of rare versus novel auditory stimuli reveal different mechanisms of auditory change detection

2012

Automatic detection of rare stimuli or changes in an auditory stimulation can distract ongoing task processing by attracting attention away from task relevant information. Typically, the effectiveness of auditory change detection is tested by rare and unpredictable deviations (compared with an otherwise regular auditory presentation) or by rare environmental sounds. The present study demonstrates that both types of stimuli are capable of triggering automatic orientation of attention and that rare environmental sounds are more effective than deviations in distraction of attention. This finding suggests different mechanisms underlying the detection of auditory change. Moreover, novelty as con…

AdultMalemedicine.medical_specialtyTime FactorsComputer sciencePhotic StimulationAutomatic processingAudiologyElectroencephalographybehavioral disciplines and activitiesTask (project management)Young AdultOrientation (mental)DistractionReaction TimemedicineHumansAttentionskin and connective tissue diseasesEvoked Potentialsmedicine.diagnostic_testGeneral NeuroscienceNoveltyElectroencephalographySoundAcoustic StimulationAuditory PerceptionFemalesense organsPhotic Stimulationpsychological phenomena and processesChange detectionNeuroReport
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Drowned Landscapes: The Rediscovered Archaeological Heritage of the Mosul Dam Reservoir

2023

Like natural catastrophes or armed conflicts, resource extraction projects herald the alteration or destruction of natural and cultural landscapes alike. Dam construction is a major threat to cultural heritage in Western Asian archaeology. One event may result in obliterating hundreds of sites, most of which never reappear or do so only sporadically following cyclical water fluctuation. Destruction of sites remains ongoing, necessitating constant assessment of damage and the establishment of strategies of documentation and maintenance. This paper proposes a new paradigm for future safeguarding and, more widely, a new tool for managing contiguous terrestrial and lacustrine cultural zones. It…

Cultural StudiesArcheologyHistoryMosul Lakedamendangered archaeologycultural heritageGISlandscape archaeologyremote sensingKurdistan region of Iraqupper Mesopotamiaarchaeological surveychange detectionSettore L-OR/05 - Archeologia E Storia Dell'Arte Del Vicino Oriente Antico
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Multitemporal Unmixing of Medium-Spatial-Resolution Satellite Images: A Case Study Using MERIS Images for Land-Cover Mapping

2011

Data from current medium-spatial-resolution imaging spectroradiometers are used for land-cover mapping and land-cover change detection at regional to global scales. However, few landscapes are homogeneous at these scales, and this creates the so-called mixed-pixel problem. In this context, this study explores the use of the linear spectral mixture model to extract subpixel land-cover composition from medium-spatial-resolution data. In particular, a time series of MEdium Resolution Imaging Spectrometer (MERIS) full-resolution (FR; pixel size of 300 m) images acquired over The Netherlands is used to illustrate this study. The Netherlands was selected because of the following: 1) the fragmenta…

aerosolMETIS-304171Computer scienceImaging spectrometerContext (language use)Land coverStellar classificationLaboratory of Geo-information Science and Remote Sensingpixelmodis dataLaboratorium voor Geo-informatiekunde en Remote SensingElectrical and Electronic EngineeringImage resolutionRemote sensingPixelSpectrometerVegetationPE&RCspectral mixture analysisSubpixel renderingSpectroradiometerThematic mapITC-ISI-JOURNAL-ARTICLEGeneral Earth and Planetary SciencesChange detection
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Nonlinear Cook distance for Anomalous Change Detection

2020

In this work we propose a method to find anomalous changes in remote sensing images based on the chronochrome approach. A regressor between images is used to discover the most {\em influential points} in the observed data. Typically, the pixels with largest residuals are decided to be anomalous changes. In order to find the anomalous pixels we consider the Cook distance and propose its nonlinear extension using random Fourier features as an efficient nonlinear measure of impact. Good empirical performance is shown over different multispectral images both visually and quantitatively evaluated with ROC curves.

FOS: Computer and information sciencesComputer Science - Machine LearningComputer scienceComputer Vision and Pattern Recognition (cs.CV)Multispectral imageComputer Science - Computer Vision and Pattern Recognition0211 other engineering and technologies02 engineering and technologyMeasure (mathematics)Machine Learning (cs.LG)Kernel (linear algebra)symbols.namesake0502 economics and businessCook's distance021101 geological & geomatics engineering050208 financePixelbusiness.industry05 social sciencesPattern recognitionNonlinear systemFourier transformKernel (image processing)Computer Science::Computer Vision and Pattern RecognitionsymbolsArtificial intelligencebusinessChange detection
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