A New Method for Identification and Analysis of Persistent Scatterers in Series of SAR Images

2008 ◽  
Author(s):  
Mario Costantini ◽  
Salvatore Falco ◽  
Fabio Malvarosa ◽  
Federico Minati
Keyword(s):  
New Method ◽  
Sar Images ◽  
Persistent Scatterers ◽  
In Series

A New Method of Ship Detection for SAR Images

2011 ◽  
Vol 3 (9) ◽  
pp. 64-71 ◽  
Author(s):  
Huozhen Hu ◽  
Jinwen Tian ◽  
Guangming Dai ◽  
Maocai Wang ◽  
Yi Peng
Keyword(s):  
New Method ◽  
Sar Images ◽  
Ship Detection

scholarly journals URBAN MONITORING BASED ON SENTINEL-1 DATA USING PERMANENT SCATTERER INTERFEROMETRY AND SAR TOMOGRAPHY

2018 ◽  
Vol XLII-3 ◽  
pp. 235-238 ◽  
Author(s):  
M. Crosetto ◽  
A. Budillon ◽  
A. Johnsy ◽  
G. Schirinzi ◽  
N. Devanthéry ◽  
...  
Keyword(s):  
Urban Areas ◽  
Test Site ◽  
Persistent Scatterer Interferometry ◽  
Sar Images ◽  
Persistent Scatterers ◽  
Persistent Scatterer ◽  
Deformation Component ◽  
Urban Monitoring ◽  
Comparison Of The Results ◽  
Azimuth Resolution

A lot of research and development has been devoted to the exploitation of satellite SAR images for deformation measurement and monitoring purposes since Differential Interferometric Synthetic Apertura Radar (InSAR) was first described in 1989. In this work, we consider two main classes of advanced DInSAR techniques: Persistent Scatterer Interferometry and Tomographic SAR. Both techniques make use of multiple SAR images acquired over the same site and advanced procedures to separate the deformation component from the other phase components, such as the residual topographic component, the atmospheric component, the thermal expansion component and the phase noise. TomoSAR offers the advantage of detecting either single scatterers presenting stable proprieties over time (Persistent Scatterers) and multiple scatterers interfering within the same range-azimuth resolution cell, a significant improvement for urban areas monitoring. This paper addresses a preliminary inter-comparison of the results of both techniques, for a test site located in the metropolitan area of Barcelona (Spain), where interferometric Sentinel-1 data were analysed.

scholarly journals Development of the Modularity Measure for Assembly Process Structures

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Vladimir Modrak ◽  
Zuzana Soltysova
Keyword(s):  
System Design ◽  
Design Principle ◽  
Singular Value ◽  
New Method ◽  
Assembly Process ◽  
System Property ◽  
In Series ◽  
Modularity Index

This study is aimed at exploring the problem of quantification of process modularity degree. Modularity as a system design principle is apprehended here as the extent to which processes can be decomposed into modules to be executed in parallel and/or in series. For this purpose, a new method is proposed to measure relative modularity of different assembly process structures. This method is compared with other relative modularity measures, namely singular value modularity index, degree of process module, and process module independence, in order to verify its effectiveness. For this purpose, selected representative types of assembly process structures are used. This testing proved that the proposed relative modularity indicator for manufacturing and/or assembly process structures reflects the expected system property in adequate way.

scholarly journals MYI Floes Identification Based on the Texture and Shape Feature from Dual-Polarized Sentinel-1 Imagery

2020 ◽  
Vol 12 (19) ◽  
pp. 3221
Author(s):  
Shiyi Chen ◽  
Mohammed Shokr ◽  
Xinqing Li ◽  
Yufang Ye ◽  
Zhilun Zhang ◽  
...  
Keyword(s):  
Visual Analysis ◽  
Open Water ◽  
New Method ◽  
The Arctic ◽  
First Year ◽  
Ancillary Data ◽  
Sar Images ◽  
Morphological Image Processing ◽  
Automated Algorithms ◽  
Fine Resolution

The Northwest Passage (NWP) in the Arctic is usually covered with hazardous multi-year ice (MYI) and seasonal first-year ice (FYI) in winter, with possible thin ice and open-water areas during transition seasons. Ice classification is important for both marine navigation and climate change studies. Satellite-based Synthetic Aperture Radar (SAR) systems have shown advantages of retrieving this information. Operational ice mapping relies on visual analysis of SAR images along with ancillary data. However, these maps estimate ice types and concentrations within large-size polygons of a few tens or hundreds of kilometers, which are subjectively identified and selected by analysts. This study aims at developing an automated algorithm to identify individual MYI floes from SAR images then classify the rest of the image as FYI and other ice types. The algorithm identifies the MYI floes using extended-maximum operator, morphological image processing, and a few geometrical features. Classifying the rest of the image uses texture and neural network model. The input data is a set of Sentinel-1 A/B Extended Wide (EW) mode images, acquired between September and March 2016–2019. Although the overall accuracy (for all type classification) from the new method scored 93.26%, the accuracy from using the texture classifier only was 75.81%. The kappa coefficient from the former was higher than the latter by 0.25. Compared with the operational ice charts from the Canadian Ice Service, ice type maps from the new method show better distribution of MYI at the fine scale of individual floes. Comparison against MYI concentration from two automated algorithms that use a combination of coarse-resolution passive and active microwave data also confirms the advantage of resolving MYI floes from the fine-resolution SAR.

scholarly journals Publication announcement

1905 ◽  
Vol 76 (507) ◽  
pp. 87-87
Keyword(s):  
Carbon Dioxide ◽  
Free Surface ◽  
Special Reference ◽  
Atmospheric Carbon Dioxide ◽  
New Method ◽  
Caustic Alkali ◽  
Physiological Processes ◽  
Thermal Emissivity ◽  
In Series

Researches on some of the Physiological Processes of Green Leaves, with special Reference to the Interchange of Energy between the Leaf and its Surroundings. By HORACE T. BROWN, LL.D., F.R.S., and F. Escombe. On a New Method for the Determination of Atmospheric Carbon Dioxide. based on the Rate of its Absorption by a Free Surface of a Solution of Caustic Alkali. By HORACE T. BROWN, LL.D., F.R.S., and F. Escombe On the Variations in the Amount of Carbon Dioxide in the Air of Kew during the Years 1898-1901. By HORACE T. BROWN, LL.D., F.R.S., and F. EscOMBE. On the Thermal Emissivity of a Green Leaf in Still and Moving Air. By HORACE T. BROWN, LL.D., F.R.S., and W. E. WILSON, D.Sc., F.R.S. These papers, which formed the basis of the Bakerian Lecture, delivered by Dr. Horace T. Brown, on March 23, 1905, are published in Series B of 'Proceedings,' April, 1905.

A New Method of Block Adjustment of Airborne SAR Images with Few GCPs

2011 ◽  
Vol 32 (12) ◽  
pp. 2842-2847
Author(s):  
Jing Ma ◽  
Hong-jian You ◽  
Hui Long ◽  
Chi-biao Ding
Keyword(s):  
New Method ◽  
Sar Images ◽  
Airborne Sar

Speech Emotion Recognition on Small Sample Learning by Hybrid WGAN-LSTM Networks

2021 ◽  
Author(s):  
Cunwei Sun ◽  
Luping Ji ◽  
Hailing Zhong
Keyword(s):  
Emotion Recognition ◽  
Language Processing ◽  
Short Term Memory ◽  
Small Sample ◽  
New Method ◽  
Small Samples ◽  
Speech Emotion Recognition ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
In Series

The speech emotion recognition based on the deep networks on small samples is often a very challenging problem in natural language processing. The massive parameters of a deep network are much difficult to be trained reliably on small-quantity speech samples. Aiming at this problem, we propose a new method through the systematical cooperation of Generative Adversarial Network (GAN) and Long Short Term Memory (LSTM). In this method, it utilizes the adversarial training of GAN’s generator and discriminator on speech spectrogram images to implement sufficient sample augmentation. A six-layer convolution neural network (CNN), followed in series by a two-layer LSTM, is designed to extract features from speech spectrograms. For accelerating the training of networks, the parameters of discriminator are transferred to our feature extractor. By the sample augmentation, a well-trained feature extraction network and an efficient classifier could be achieved. The tests and comparisons on two publicly available datasets, i.e., EMO-DB and IEMOCAP, show that our new method is effective, and it is often superior to some state-of-the-art methods.

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