- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Multi-Spectral Ship Detection Using Optical, Hyperspectral, and Microwave SAR Remote Sensing Data in Coastal Regions
摘要： The necessity of efficient monitoring of ships in coastal regions has been increasing over time. Multi-satellite observations make it possible to effectively monitor vessels. This study presents the results of ship detection methodology, applied to optical, hyperspectral, and microwave satellite images in the seas around the Korean Peninsula. Spectral matching algorithms are used to detect ships using hyperspectral images with hundreds of spectral channels and investigate the similarity between the spectra and in-situ measurements. In the case of SAR (Synthetic Aperture Radar) images, the Constant False Alarm Rate (CFAR) algorithm is used to discriminate the vessels from the backscattering coefficients of Sentinel-1B SAR and ALOS-2 PALSAR2 images. Validation results exhibited that the locations of the satellite-detected vessels showed good agreement with real-time location data within the Sentinel-1B coverage in the Korean coastal region. This study presented the probability of detection values of optical and SAR-based ship detection and discussed potential causes of the errors. This study also suggested a possibility for real-time operational use of vessel detection from multi-satellite images based on optical, hyperspectral, and SAR remote sensing, particularly in the inaccessible coastal regions off North Korea, for comprehensive coastal management and sustainability.
关键词： ship detection,coastal region,hyperspectral,sustainability,optical remote sensing,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 - A Simulation Based Approach to Estimating the Three Dimensional Structure of the Harvard Forest with Multi-Modal Remote Sensing
摘要： Tracking carbon as it enters and exits each stage of the carbon cycle is necessary to help build understanding of the cycle's mechanics and its effect on climate. Satellite and airplane-based remote sensing technologies have shown promising results in aiding in human understanding of our planet, including vegetative areas. The Harvard Forest has been studied in various ways over the course of the last century. In particular, synthetic aperture radar, LiDAR, and passive optical sensors have each been used to study the Harvard Forest. Employing a form of data fusion, we present an approach to estimate a forest stand's mean canopy height and biomass for each component tree species while employing minimal ground measurements. We present an approach where a database of simulated forest stands is generated containing both homogeneous stands and heterogeneous stands with up to four tree species present in a given stand. Each simulated stand is compared to an input stand on a number of criteria and a figure of similarity is calculated. In the case that a simulated stand isn't found with a figure of similarity below a set threshold, an iterative process is employed to modify the most similar stand to improve the factor of similarity by modifying the stand's species composition, tree densities, heights, and biomasses. A simulated stand, either pre-existing or developed dynamically will be considered a reasonable representation of the physical forest stand and the 3-D structure of the simulated stand will be reported as an estimate for that of the physical forest stand. This method relies heavily on our sensor simulators, including our fractal-based tree geometry generator, as well as SAR, IfSAR, LiDAR, and Optical simulators. We have previously investigated the ability of our method to differentiate between coniferous and deciduous trees in the same forest stand. We propose to extend this to a maximum of four different tree species, and to validate our approach in the Harvard Forest, a heavily studied region in central Massachusetts.
关键词： Harvard Forest,Forest Parameter Estimation,IfSAR,Heterogeneous Forests,SAR,LiDAR
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 - End-to-End Simulator of Geosynchronous SAR Data for System Performance Assessment
摘要： The paper describes an end-to-end simulator for Geosynchronous SAR data. The tool is composed of two modules: a raw data time domain simulator and a processor for the generation of the L1 products. The simulated raw data include the effects of atmospheric and clutter decorrelation. The end-to-end simulator is a powerful and flexible tool to be used during the system design phase for the verification of the expected performance.
关键词： APS,clutter,decorrelation,Geosynchronous SAR,end-to-end simulator
更新于2025-09-23 15:23:52
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Analysis of impacting factors on polarimetric SAR oil spill detection
摘要： Polarimetric synthetic aperture radar (SAR) oil spill detection parameters conformity coefficient (μ), Muller matrix parameters (|C|, B0), the eigenvalues of simplified coherency matrix (λnos) and the influence of SAR observing parameters, ocean environment and noise level are investigated. Radarsat-2 data are used to make systematic analysis of polarimetric parameters for different incidences, wind speeds, noise levels and the ocean phenomena (oil slick and look likes). The influence of the SAR observing parameters, the ocean environment and the noise level on the typical polarimetric SAR parameter conformity coefficient has been analyzed. The results indicate that conformity coefficient cannot be simply used for oil spill detection, which represents the image signal to the noise level to some extent. When the signals are below the noise level for the oil slick and the look likes, the conformity coefficients are negative; while the signals above the noise level corresponds to positive conformity coefficients. For dark patches (low wind and biogenic slick) with the signal below the noise, polarization features such as conformity coefficient cannot separate them with oil slick. For the signal above the noise, the oil slick, the look likes (low wind and biogenic slick) and clean sea all have positive conformity coefficients, among which, the oil slick has the smallest conformity coefficient, the look likes the second, and the clean sea the largest value. For polarimetric SAR data oil spill detection, the noise plays a significant role. So the polarimetric SAR data oil spill detection should be carried out on the basis of noise consideration.
关键词： oil spill,conformity coefficient,multi-polarimetric SAR,noise
更新于2025-09-23 15:23:52
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Remote Sensing Image Registration based on Phase Congruency Feature Detection and Spatial Constraint Matching
摘要： In this paper, a novel remote sensing image registration method based on phase congruency (PC) and spatial constraint is proposed. PC can provide intrinsic and meaningful image features, even when there are complex intensity changes or noise. Image features will be well detected from the corresponding PC images by the SAR-SIFT operator. It means that the feature detection methods in the frequency domain (PC) and the spatial domain (SAR-SIFT operator) are combined. To further improve the result of registration, spatial constraints, including point and line constraint, are established by utilizing the position and orientation information. Then, one to more matches can be removed and the influence of adjacent point can be greatly eliminated. The experimental results demonstrate that our method can obtain a better registration performance with higher accuracy and more correct correspondences than the state-of-the-art methods, such as SIFT, SAR-SIFT, SURF, PSO-SIFT, RIFT, and GLPM.
关键词： remote sensing,spatial constraint,SAR-SIFT operator,image registration,Phase congruency
更新于2025-09-23 15:23:52
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[IEEE 2018 12th International Conference on Communications (COMM) - Bucharest (2018.6.14-2018.6.16)] 2018 International Conference on Communications (COMM) - Supervized Change Detection for SAR Imagery Based on Processing of a Low Size Training Data Set by an Ensemble of Self-Organizing Maps
摘要： This paper presents a new method to improve accuracy of supervised change detection in Synthetic Aperture Radar (SAR) imagery. The model is based on the idea to apply a low size labeled dataset to the input of an Ensemble of Self-Organizing Maps (ESOM) for training data generation (TDG). The resulted synthetic data set produced by ESOM substitutes the initial authentically labeled sample set and it is used to train a supervised change detection classifier. The proposed method is evaluated using a TerraSAR-X image of 400x400 pixels acquired in the Fukushima region, Japan, before and after tsunami. As change detection classifiers we have comparatively considered Support Vector Machine (SVM), Nearest Neighbor (NN), the three-Nearest Neighbors (3-NN), and Likelihood Bayes classifier. The experimental results have confirmed the effectiveness of the proposed approach using only 100 authentic labeled pixels.
关键词： SAR images,ensemble of self-organizing maps (ESOM),virtual training data generation(VTDG),change detection
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 - Normalized Compression Distance for SAR Image Change Detection
摘要： With a continuous increase in multi-temporal synthetic aperture radar (SAR) images, leading to enable mapping applications for Earth environmental observation, the number of algorithms for detection of different types of terrain changes has greatly expanded. In this paper, a SAR image change detection method based on normalized compression distance (NCD) is proposed. The procedure mainly consists in dividing two time series images in patches, computing a collection of similarities corresponding to each pair of patches and generating the change map with a histogram-based threshold. The experimental results were computed using 2 Sentinel 1A images over the city of Bucharest, Romania and 2 TerraSAR-X images over the Elbe River and its surrounding area, Germany.
关键词： Change detection,SAR,NCD,satellite image time series (SITS)
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 - Spacecraft Formation Design for Bistatic SAR with GEO Illuminator and LEO Receiver
摘要： The bistatic synthetic aperture radar (BiSAR) system consists of a geosynchronous Earth orbit (GEO) illuminator and a low Earth orbit (LEO) receiver. Compared with GEO SAR, it offers great advantages of higher signal-to-noise ratio (SNR) and finer spatial resolution with lower system complexity. The concept also raises significant technical challenges. The spacecraft formation has great effect on radar performance, such as spatial resolution, the angle of two-dimensional (2-D) resolution direction and noise-equivalent sigma zero (NESZ). This paper establishes the relationship between the imaging performance and the formation parameters. Then, a novel design method of spacecraft formation is presented, identifying the principal formation design choices and constraints. Finally, simulation results are provided for typical observational tasks, to verify the effectiveness of the proposed method.
关键词： imaging performance,spacecraft formation,bistatic SAR,geosynchronous
更新于2025-09-23 15:23:52