Filters








320 Hits in 9.1 sec

Change Detection from Synthetic Aperture Radar Images via Graph-Based Knowledge Supplement Network [article]

Junjie Wang, Feng Gao, Junyu Dong, Shan Zhang, Qian Du
2022 arXiv   pre-print
Synthetic aperture radar (SAR) image change detection is a vital yet challenging task in the field of remote sensing image analysis.  ...  To solve the problem, we propose a Graph-based Knowledge Supplement Network (GKSNet).  ...  To handle the above-mentioned problems, we propose a Graph-based Knowledge Supplement Network (GKSNet) for SAR image change detection.  ... 
arXiv:2201.08954v2 fatcat:d2owbydspjgtjcicurv47bvlii

Change Detection from Synthetic Aperture Radar Images via Graph-Based Knowledge Supplement Network

Junjie Wang, Feng Gao, Junyu Dong, Shan Zhang, Qian Du
2022 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
Synthetic aperture radar (SAR) image change detection is a vital yet challenging task in the field of remote sensing image analysis.  ...  To solve the problem, we propose a graph-based knowledge supplement network (GKSNet).  ...  To this end, we proposed a graph-based knowledge supplement network, termed GKSNet. On the one hand, image features from a labeled dataset are projected into a graph.  ... 
doi:10.1109/jstars.2022.3146167 fatcat:a732pgcfebdn7h6cpfap2ucpsq

Multitemporal Change Detection Analysis in an Urbanized Environment Based upon Sentinel-1 Data

Lars Gruenhagen, Carsten Juergens
2022 Remote Sensing  
To retrospectively quantify such land cover changes, this study analysed synthetic aperture radar images of the Sentinel-1 satellites by applying the Google Earth Engine.  ...  This approach uses synthetic aperture radar data that are rarely considered in previously existing land cover change services.  ...  Land cover change analysis can be done with optical data, e.g., in Jürgens 2000 [13] , but also as in this study with active synthetic aperture radar (SAR) data.  ... 
doi:10.3390/rs14041043 fatcat:x2divvfaqvbqtaowobk4cuoaqi

Implementation of Fog computing for reliable E-health applications

Razvan Craciunescu, Albena Mihovska, Mihail Mihaylov, Sofoklis Kyriazakos, Ramjee Prasad, Simona Halunga
2015 2015 49th Asilomar Conference on Signals, Systems and Computers  
In this paper we follow-up on recent massive MTC concepts combining advanced MAC protocols with Compressed Sensing (CS) based multiuser detection.  ...  network is expected to support up to 1000x more connections per cell with reduced latency below 1 ms.  ...  aperture radar (SAR) images are acquired.  ... 
doi:10.1109/acssc.2015.7421170 dblp:conf/acssc/CraciunescuMMKP15 fatcat:qm6mki5z6bcvrfimkmqjyrxaxm

GB-InSAR monitoring and observational method for landslide emergency management: the Montaguto earthflow (AV, Italy)

F. Ferrigno, G. Gigli, R. Fanti, N. Casagli
2015 NHESSD  
A monitoring activity using GB-InSAR (Ground Based Interferometric Synthetic Aperture Radar) system began, in order to investigate the landslide kinematics, to plan urgent safety measures for risk mitigation  ...  community by increasing scientific knowledge.  ...  The synthetic aperture is formed by moving the radar head along a linear rail.  ... 
doi:10.5194/nhessd-3-7247-2015 fatcat:vgjdbmf7nvgqhhqsiwizv7r6lq

Ping-pong beam training for reciprocal channels with delay spread

Elisabeth de Carvalho, Jorgen Bach Andersen
2015 2015 49th Asilomar Conference on Signals, Systems and Computers  
The proposed detection scheme does not assume prior knowledge on image statistics and draws all inferences from the data measurements. .  ...  Both single-and multi-aperture radar configurations are considered and the detection performance evaluation of each configuration is carried out using electromagnetic modeling data.  ...  aperture radar (SAR) images are acquired.  ... 
doi:10.1109/acssc.2015.7421451 dblp:conf/acssc/CarvalhoA15 fatcat:mqokuvnh3zg45licnfbgxyvxfu

Deep Learning Meets SAR [article]

Xiao Xiang Zhu, Sina Montazeri, Mohsin Ali, Yuansheng Hua, Yuanyuan Wang, Lichao Mou, Yilei Shi, Feng Xu, Richard Bamler
2021 arXiv   pre-print
Although deep learning has been introduced in Synthetic Aperture Radar (SAR) data processing, despite successful first attempts, its huge potential remains locked.  ...  of unstructured data, e.g., knowledge graphs and social networks, in real life that cannot be directly processed by a deep CNN.  ...  Moreover recurrent units in RGNNs (Recurrent Graph Neural Network) [47] [48] have also been proven to obtain achievements in learning from graphs. III.  ... 
arXiv:2006.10027v2 fatcat:s3tiroz4qve6nbhavtz77fbis4

Detecting Emergence, Growth, and Senescence of Wetland Vegetation with Polarimetric Synthetic Aperture Radar (SAR) Data

Alisa Gallant, Shannon Kaya, Lori White, Brian Brisco, Mark Roth, Walt Sadinski, Jennifer Rover
2014 Water  
We investigated the use of multitemporal polarimetric synthetic aperture radar (SAR) data acquired with Canada's Radarsat-2 system to track within-season changes in wetland vegetation and surface water  ...  We used ground-based monitoring data and other ancillary information to assess the limits and consistency of the SAR data for tracking seasonal changes in wetlands.  ...  We appreciate helpful input from Jennifer Corcoran (National Aeronautics and Space Administration) and three anonymous reviewers on an earlier version of this paper.  ... 
doi:10.3390/w6030694 fatcat:q3qaklkwq5azdl4hqm3g2nopkm

Generic framework for vessel detection and tracking based on distributed marine radar image data

Gregor Siegert, Julian Hoth, Paweł Banyś, Frank Heymann
2018 CEAS Space Journal  
This tracker is conditioned on measurements extracted from radar images.  ...  In this article, we present a framework to assess the current situation picture based on marine radar image processing.  ...  In [16] and [30] AIS data are fused with Synthetic Aperture Radar (SAR) imagery and/ or coastal radar to provide a reliable and precise situation picture for large-scale maritime surveillance.  ... 
doi:10.1007/s12567-018-0208-6 fatcat:tmsmksmldfa3nos7bqyrtg5gpe

Integrated radar and lidar analysis reveals extensive loss of remaining intact forest on Sumatra 2007–2010

M. B. Collins, E. T. A. Mitchard
2015 Biogeosciences Discussions  
Forests with high above ground biomass (AGB), including those growing on peat swamps, have historically not been thought suitable for biomass mapping and change detection using Synthetic Aperture Radar  ...  However, by integrating L-band (λ = 0.23 m) SAR with lidar data from the ALOS and ICESat earth-observing satellites respectively, and 56 forest plots, we were able to create a forest biomass and change  ...  It also can be undertaken using active sensing technologies such as synthetic aperture radar (SAR) acquired at low (e.g. L-band) frequencies.  ... 
doi:10.5194/bgd-12-8573-2015 fatcat:gbwidajofbdvbcjhuh2hzect4y

Integrated radar and lidar analysis reveals extensive loss of remaining intact forest on Sumatra 2007–2010

M. B. Collins, E. T. A. Mitchard
2015 Biogeosciences  
</strong> Forests with high above-ground biomass (AGB), including those growing on peat swamps, have historically not been thought suitable for biomass mapping and change detection using synthetic aperture  ...  radar (SAR).  ...  It also can be undertaken using active sensing technologies such as synthetic aperture radar (SAR) acquired at low (e.g. L-band) frequencies.  ... 
doi:10.5194/bg-12-6637-2015 fatcat:7dtetg6uwnahxg4347key26pxu

2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70

2021 IEEE Transactions on Instrumentation and Measurement  
Article numbers are based on specified topic areas and corresponding codes associated with the publication.  ...  -that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Chang, H., +, TIM 2021 1005909 Permittivity Extraction From Synthetic Aperture Radar (SAR) Images of Multilayered Media.  ... 
doi:10.1109/tim.2022.3156705 fatcat:dmqderzenrcopoyipv3v4vh4ry

A Multi-Scale Deep Neural Network for Water Detection from SAR Images in the Mountainous Areas

Lifu Chen, Peng Zhang, Jin Xing, Zhenhong Li, Xuemin Xing, Zhihui Yuan
2020 Remote Sensing  
Water detection from Synthetic Aperture Radar (SAR) images has been widely utilized in various applications.  ...  To address this challenge, a new end-to-end framework based on deep learning has been proposed to automatically classify water and shadow areas in SAR images.  ...  Introduction Detecting water bodies from Synthetic Aperture Radar (SAR) images has been a very active research field [1] .  ... 
doi:10.3390/rs12193205 fatcat:5yedpdnzhjfazp63wfvzu5iw6q

A Survey of Change Detection Methods Based on Remote Sensing Images for Multi-Source and Multi-Objective Scenarios

Yanan You, Jingyi Cao, Wenli Zhou
2020 Remote Sensing  
Based on the survey, a general change detection framework, including change information extraction, data fusion, and analysis of multi-objective scenarios modules, is summarized.  ...  However, diverse multi-source features and change patterns bring challenges to the change detection in urban cases.  ...  Meanwhile, multi-source satellite sensors provide a variety of RS images for change detection, such as synthetic aperture radar (SAR) [11, 12] , multispectral [13] , and hyperspectral images [14, 15  ... 
doi:10.3390/rs12152460 fatcat:itc5ixwgrffuzgzyj2yrycaree

Defense Advanced Research Projects Agency (Darpa) Fiscal Year 2016 Budget Estimates

Department Of Defense Comptroller's Office
2015 Zenodo  
The Video-rate Synthetic Aperture Radar (ViSAR) program seeks to develop a real-time spotlight synthetic aperture radar (SAR) imaging sensor that will provide imagery of a region to allow high-resolution  ...  Insight will enable detection of threat networks through combination and analysis of information from imaging and non-imaging sensors and other sources.  ... 
doi:10.5281/zenodo.1215366 fatcat:cqn5tyfixjanzp5x3tgfkpedri
« Previous Showing results 1 — 15 out of 320 results