- 标题
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A Novel Tool for Unsupervised Flood Mapping Using Sentinel-1 Images
摘要: In this paper, we present a novel method for mapping flooded areas exploiting Sentinel-1 ground range detected products. The work introduces two novelties. As first, the input products. In fact, as far we know, no applications using these products has been so far presented in literature. Secondly, a new unsupervised methodology, based on the usage of opportune layers combined in a fuzzy decision system, is presented. Experimental results, obtained both on the single SAR image and on a couple of acquisitions in a change detection framework showed that our method is able to outperform the most popular classification techniques in terms of standard assessment parameters.
关键词: flooding,sentinel-1,classification,fuzzy systems,Synthetic aperture radar
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Oil Slick Detection in the Offshore Domain: Evaluation of Polarization-Dependent Sar Parameters
摘要: Remote sensing technology is an essential link in the global monitoring of the ocean surface and radars are efficient sensors for detecting marine pollution. When used operationally, a tradeoff must usually be made between the covered area and the quantity of information collected by the radar. To identify the most appropriate imaging mode, a methodology based on Receiver Operating Characteristic (ROC) curve analysis has been applied to an original dataset collected by an airborne system, SETHI, characterized by a very low instrument noise floor. The dataset was acquired during an oil spill clean-up exercise carried out in 2015 in the North Sea. Various polarization-dependent quantities are investigated and a relative ordering of the main polarimetric parameters is reported. VV offers the best tradeoff between the benefit of detection performance and the instrument and data requirements. When the sensor has a sufficiently low noise floor, HV is also recommended because it provides strong slick-sea contrast. Among all the investigated quad-polarimetric settings, no significant added value compared to single-polarized data was found.
关键词: NESZ,noise floor,sea,spill,detection,SAR,noise,slick,radar,marine pollution,probability of detection,oil,ROC curves,probability of false alarm,ocean,polarization
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Temporal Difference and Density-Based Learning Method Applied for Deforestation Detection Using ALOS-2/PALSAR-2
摘要: Remote sensing has established as key technology for monitoring of environmental degradation such as forest clearing. One of the state-of-the-art microwave EO systems for forest monitoring is Japan’s L-band ALOS-2/PALSAR-2 which provides outstanding means for observing tropical forests due its cloud and canopy penetration capability. However, the complexity of the physical backscattering properties of forests and the associated spatial and temporal variabilities, render straightforward change detection methods based on simple thresholding rather inaccurate with high false alarm rates. In this paper, we develop a framework to alleviate problems caused by forest backscatter variability. We define three essential elements, namely “structures of density”, “speed of change”, and “expansion patterns” which are obtained by differential computing between two repeat-pass PALSAR-2 images. To improve both the detection and assessing of deforestation, a “deforestation behavior pattern” is sought through temporal machine learning mechanism of the three proposed elements. Our results indicate that the use of “structure of density” can introduce a more robust performance for detecting deforestation. Meanwhile, “speed of change” and “expansion pattern” are capable to provide additional information with respect to the drivers of deforestation and the land-use change.
关键词: Density-Based,Temporal Difference Learning,Synthetic Aperture Radar (SAR)
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Sea Ice Change Detection in SAR Images Based on Collaborative Representation
摘要: Sea ice change detection from synthetic aperture radar (SAR) images is important for navigation safety and natural resource extraction. This paper proposed a sea ice change detection method from SAR images based on collaborative representation. First, neighborhood-based ratio is used to generate a difference image (DI). Then, some reliable samples are selected from the DI by hierarchical fuzzy C-means (FCM) clustering. Finally, based upon these samples, collaborative representation method is utilized to classify pixels from the original SAR images into unchanged and changed class. From there, the final change map can be obtained. Experimental results on two real sea ice datasets demonstrate the superiority of the proposed method over two closely related methods.
关键词: sea ice change detection,synthetic aperture radar,clustering method,collaborative representation
更新于2025-09-23 15:23:52
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GLRT Detection of Micromotion Targets for the Multichannel SAR-GMTI System
摘要: This letter investigates the micromotion target detection problem for the multichannel synthetic aperture radar (SAR)- ground moving target indication system. The multichannel SAR signal models of the micromotion target and the ground clutter in the raw data domain are established firstly. Then the generalized likelihood ratio test (GLRT) of the micromotion target is derived. Based on the analysis of the probability density functions of the test statistics, theoretical detection performance dependent on the micromotion parameters is provided. Simulated heterogeneous SAR data validate the effectiveness of the GLRT detector.
关键词: Ground moving target indication (GMTI),synthetic aperture radar (SAR),micromotion
更新于2025-09-23 15:23:52
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Imbalanced Learning-Based Automatic SAR Images Change Detection by Morphologically Supervised PCA-Net
摘要: Change detection is a quite challenging task due to the imbalance between unchanged and changed class. In addition, the traditional difference map generated by log-ratio is subject to the speckle, which will reduce the accuracy. In this letter, an imbalanced learning-based change detection is proposed based on PCA network (PCA-Net), where a supervised PCA-Net is designed to obtain the robust features directly from given multitemporal synthetic aperture radar (SAR) images instead of a difference map. Furthermore, to tackle with the imbalance between changed and unchanged classes, we propose a morphologically supervised learning method, where the knowledge in the pixels near the boundary between two classes is exploited to guide network training. Finally, our proposed PCA-Net can be trained by the data sets with available reference maps and applied to a new data set, which is quite practical in change detection projects. Our proposed method is veri?ed on ?ve sets of multiple temporal SAR images. It is demonstrated from the experiment results that with the knowledge in training samples from the boundary, the learned features bene?t change detection and make the proposed method outperform than supervised methods trained by randomly drawing samples.
关键词: Change detection,imbalance learning,synthetic aperture radar (SAR) images,PCA network (PCA-Net)
更新于2025-09-23 15:23:52
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Sensitive Damage Detection of Reinforced Concrete Bridge Slab by ``Time-Variant Deconvolution'' of SHF-Band Radar Signal
摘要: In this paper, we focus on ground-penetrating radar (GPR) for infrastructural health monitoring, especially for the monitoring of reinforced concrete (RC) bridge slab. Due to the demand of noncontact and high-speed monitoring technique which can handle vast amounts of aging infrastructures, GPR is a promising tool. However, because radar images consist of many reflected waves, they are usually difficult to interpret. Furthermore, the spatial resolution of system is not enough considering the thickness of target damages, cracks, and segregation are millimeter-to-centimeter order while the wavelength of ordinary GPR ultrahigh-frequency band is over 10 cm. To address these problems, for the purpose of sensitive damage detection, we propose a new algorithm based on deconvolution utilizing a super high-frequency (SHF) band system. First, a distribution of reflection coefficient is inversely estimated by 1-D bridge slab model. Because concrete is found to be a lossy medium at SHF band, we consider the attenuation of signal in deconvolution. The algorithm is called 'time-variant deconvolution' in this paper. After the validation by simulation, the effects of the algorithm and frequency band on damage detection accuracy are evaluated by a field experiment. Though the results show a 1-mm horizontal crack is not detected by measured waves, when it is filled with water, it is detected by time-variant deconvolution. Moreover, the 1-mm dried crack is detected only by time-variant deconvolution at SHF band, which greatly emphasizes the peaks of the reflection coefficient of the crack.
关键词: thin cracks and segregation detection,Ground-penetrating radar (GPR),infrastructural health monitoring,time-variant deconvolution
更新于2025-09-23 15:23:52
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Polarimetric Interferometric SAR Change Detection Discrimination
摘要: A coherent change detection (CCD) image, computed from a geometrically matched, temporally separated pair of complex-valued synthetic aperture radar (SAR) image sets, conveys the pixel-level equivalence between the two observations. Low-coherence values in a CCD image are typically due to either some physical change in the corresponding pixels or a low signal-to-noise observation. A CCD image does not directly convey the nature of the change that occurred to cause low coherence. In this paper, we introduce a mathematical framework for discriminating between different types of change within a CCD image. We utilize the extra degrees of freedom and information from polarimetric interferometric SAR (PolInSAR) data and PolInSAR processing techniques to define a 29-dimensional feature vector that contains information capable of discriminating between different types of change in a scene. We also propose two change-type discrimination functions that can be trained with feature vector training data and demonstrate change-type discrimination on an example image set for three different types of change. Furthermore, we also describe and characterize the performance of the two proposed change-type discrimination functions by way of receiver operating characteristic curves, confusion matrices, and pass matrices.
关键词: polarimetric interferometric synthetic aperture radar (PolInSAR),H/A/α filter,probabilistic feature fusion (PFF) model,feature vector,Coherent change detection (CCD),optimum coherence (OC),H/A/α decomposition
更新于2025-09-23 15:23:52
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Sensitivity Analysis of Multifrequency MIMP SAR Data From Rice Paddies
摘要: The determination of the accurate composition ratio of scattering mechanisms (volume scattering, double-bounce scattering, and surface scattering) within a radar backscatter is essential to validate current polarimetric decomposition techniques. Multiincidence angle and multipolarimetric synthetic aperture radar (MIMP SAR) observations at the X- and L-bands were applied to rice paddies at late vegetative stage in Niigata City in Japan in 2014 and 2016, respectively. In this paper, multifrequency MIMP SAR analysis is introduced based on the observation results. The approach, combined with theoretical characterization of the data by a discrete scatterer model, showed that rice panicles affect the backscatter from rice paddies. Contrary to expectation, an effect of transmissivity by using different bands is not obvious. The similar level of copolarization (HH and VV) backscatter at X- and L-bands could be explained by the effective size of rice panicles. They are the most characteristic scatters in rice paddy field with respect to multiple frequency polarimetric sensing. In addition, HV shows a distinct sensitivity to the mean orientation angle and the size of panicles regardless of the wavelength. The mean orientation angle affects the polarimetric randomness under azimuthal symmetry, whereas the size of panicles directly affects the attenuation of the volume scattering from the grains. The multifrequency MIMP SAR analysis also indicated the importance of considering the backscatter and attenuation in the interpretation of the backscattering cross section from vegetated fields.
关键词: rice paddies.,multifrequency multiincidence angle and multipolarimetric synthetic aperture radar (MIMP SAR),Discrete scatterer model (DSM)
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - First GMTI Results of the MIRANDA-35 Sensor
摘要: Frequency-modulated continuous-wave (FMCW) synthetic aperture radar (SAR) are nowadays frequently exploited for producing electro-magnetic images of the earth surface. In this paper, we present first ground moving target indication (GMTI) results of the 2016 campaign with the FMCW airborne system MIRANDA-35, and quantify the overall performances. More precisely, two specific operating modes, namely the along-track interferometry (ATI) and exo-clutter processing (EXO), are discussed in more detail. The system proved to be capable of providing GMTI products with reliable detection rates and acceptable false alarm rates.
关键词: FMCW,GMTI,SAR,Ground Moving Target Indication,Synthetic Aperture Radar,Exo-Clutter,Frequency-Modulated Continuous-Wave,Interferometry
更新于2025-09-23 15:23:52