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Multimodal hyperspectral remote sensing: an overview and perspective

Yanfeng Gu, Tianzhu Liu, Guoming Gao, Guangbo Ren, Yi Ma, Jocelyn Chanussot, Xiuping Jia
2021 Science China Information Sciences  
Keywords hyperspectral image processing, multitemporal hyperspectral imaging, hyperspectral video imaging, hyperspectral stereo imaging, multimodal hyperspectral remote sensing imaging Citation Gu Y F,  ...  Multimodal hyperspectral remote sensing: an overview and perspective. Sci China Inf Sci, 2021, 64(2): 121301, https://doi.  ...  In this paper, we try to set forth a new perspective of multimodal hyperspectral remote sensing from the point of imaging detection, and give an overview of relevant data processing as comprehensive as  ... 
doi:10.1007/s11432-020-3084-1 fatcat:tivcc4l5efh5zg62t37stswqgu

2020 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 13

2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., +, JSTARS 2020 6260-6276 Change Detection in Heterogeneous Optical and SAR Remote Sensing Images Via Deep Homogeneous Feature Fusion.  ...  ., +, JSTARS 2020 6260-6276 Change Detection in Heterogeneous Optical and SAR Remote Sensing Images Via Deep Homogeneous Feature Fusion.  ...  A New Deep-Learning-Based Approach for Earthquake-Triggered Landslide Detection From Single-Temporal RapidEye Satellite Imagery. Yi, Y., +, JSTARS 2020  ... 
doi:10.1109/jstars.2021.3050695 fatcat:ycd5qt66xrgqfewcr6ygsqcl2y

2021 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 14

2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
., +, JSTARS 2021 283-299 Oil Spill Detection Based on Multiscale Multidimensional Residual CNN for Optical Remote Sensing Imagery.  ...  ., +, JSTARS 2021 9071-9078 Oil Spill Detection Based on Multiscale Multidimensional Residual CNN for Optical Remote Sensing Imagery.  ...  ., Hyperspectral Image Superresolution via Deep Structure and Texture Interfusion; JSTARS 2021 8665-8678 Hu, J., see Feng, D., JSTARS 2021 12212-12223 Hu, J., Shen, X., Yu, H., Shang, X., Guo, Q.,  ... 
doi:10.1109/jstars.2022.3143012 fatcat:dnetkulbyvdyne7zxlblmek2qy

Remote Sensing and Local Knowledge of Hydrocarbon Exploitation: The Case of Bovanenkovo, Yamal Peninsula, West Siberia, Russia

T. Kumpula, B.C. Forbes, F. Stammler
2010 Arctic  
These range from physical obstructions, such as roads, railways, and pipelines, to direct and indirect ecological impacts, such as changes in vegetation and habitats and campsites that have been used seasonally  ...  Very-high-resolution Quickbird-2 imagery revealed the most impacts, but could not detect indigenous herders and non-indigenous industrial workers.  ...  Spectral and spatial resolution limitations of standard optical remote de la Terre (SPOT), Advanced Spaceborne Thermal Emistheir application to terrestrial oil spill detection.  ... 
doi:10.14430/arctic972 fatcat:qsmy2exv5fdkrl6v64ay4lhz3e

Marine SAR Analyses and Interpretation System— MARSAIS [chapter]

Johnny Johannessen, Torill Hamre, Rene Garello, Roland Romeiser, Stefan Kern, Bertrand Chapron, Ian Robinson, Susanne Ufermann, Valerie Cummins, Niamh Connolly, Kostas Nittis, Leonidas Perivoliotis (+1 others)
2003 Elsevier Oceanography Series  
Use of synergetic remote sensing observations, in particular from optical remote sensing, is also considered in this context.  ...  In a marine coastal ocean monitoring and prediction system, multisensor in-situ and remote sensing observations (of coastal currents, fronts, eddies, upwelling patterns, internal waves, phytoplankton distribution  ...  Furthermore, its capabilities to detect and locate oil spills, bathymetric features in shallow water, and ships have also lead to systematic use of SAR images in operational surveillance associated with  ... 
doi:10.1016/s0422-9894(03)80023-5 fatcat:7tqtn5zggbcwbbygdih7vrpnzi

Multisource and Multitemporal Data Fusion in Remote Sensing [article]

Pedram Ghamisi, Behnood Rasti, Naoto Yokoya, Qunming Wang, Bernhard Hofle, Lorenzo Bruzzone, Francesca Bovolo, Mingmin Chi, Katharina Anders, Richard Gloaguen, Peter M. Atkinson, Jon Atli Benediktsson
2018 arXiv   pre-print
processing of remotely sensed data.  ...  Such an increase in remote sensing and ancillary datasets, however, opens up the possibility of utilizing multimodal datasets in a joint manner to further improve the performance of the processing approaches  ...  In this way, unsupervised change detection can become a way to increase the amount of supervision that can be injected in the learning of a multitemporal classifier.  ... 
arXiv:1812.08287v1 fatcat:hmojxdoaybc6vjeto5s3x7b6z4

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
SAR Imaging on Arbitrary Region of Interest; TGRS Oct. 2019 7995-8010 Hu, T., see Kang, Z., TGRS Jan. 2019 181-193 Hu, T., Wu, Y., Zheng, G., Zhang, D., Zhang, Y., and Li, Y., Tropical Cyclone Center  ...  ., Chang, L., and Hanssen, R.F., Incorporating Temporary Coherent Li, X., Yeo, T.S., Yang, Y., Chi, C., Zuo, F., Hu, X., and Pi, Y., Refo-cusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight  ...  of the Deepwater Horizon Oil Spill.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

Challenges and Opportunities of Multimodality and Data Fusion in Remote Sensing

M. Dalla Mura, S. Prasad, F. Pacifici, P. Gamba, J. Chanussot, J. A. Benediktsson
2015 Proceedings of the IEEE  
, earthquakes, oil-spills in seas), and give insights to potential exploitation of resources (oil fields, minerals).  ...  Remote sensing acquisitions can be done by both active (synthetic aperture radar, LiDAR) and passive (optical and thermal range, multispectral and hyperspectral) devices.  ...  Change detection Change Detection (CD) refers to the task of analyzing two or more images acquired over the same area at different times (i.e., multitemporal images) in order to detect zones in which the  ... 
doi:10.1109/jproc.2015.2462751 fatcat:cyaxiwfjqbdqzefhjgta5fivee

Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping

Cristina Gómez, David R. Green
2017 Arabian Journal of Geosciences  
Oil and gas transmission pipelines require monitoring for maintenance and safety, to prevent equipment failure and accidents.  ...  UAV systems prototyped to monitor pipelines are reviewed in this paper, and a number of monitoring scenarios are proposed and illustrated.  ...  link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s12517-017-2989-x fatcat:6a4htqomgfaftj5tarltrytxlq

Remote Sensing for the Quantification of Land Surface Dynamics in Large River Delta Regions—A Review

Kuenzer, Heimhuber, Huth, Dech
2019 Remote Sensing  
Over 200 journal papers on remote sensing related studies for large river deltas and estuaries have been analyzed and categorized into thematic fields such as river course morphology, coastline changes  ...  Sustainable management of river deltas therefore requires a holistic assessment of historic and recent ongoing changes and the dynamics in settlement sprawl, land cover and land use change, ecosystem development  ...  A number of studies have highlighted the potential of remote sensing for detecting near-coastal oil spills in aquatic environments, although delta-specific studies are still scarce.  ... 
doi:10.3390/rs11171985 fatcat:i5rq46wtkna2tcswh2vfdacfxi

Remote Sensing and Image Interpretation

John Wright, Thomas M. Lillesand, Ralph W. Kiefer
1980 Geographical Journal  
These changes have been used to monitor the presence and estimate the concentration of algae via remote sensing data.  ...  Minute traces of floating oil, ofiu11 invisible on other types of photography, can be detected in UV photography. (The use of aerial photography to study oil spills is illustrated in Chapter 3.)  ...  Remote ,ensing from space is here to stay. It is changing daily and it is repiete with economic and sociopolitical implications.  ... 
doi:10.2307/634969 fatcat:ma6fplrparhoxkjzgxstrxygmq

Continuous change detection and classification of land cover using all available Landsat data

Zhe Zhu, Curtis E. Woodcock
2014 Remote Sensing of Environment  
Nathan Phillips for sharing with me their expertise on physical remote sensing, physical climatology, and ecological physiology.  ...  Acknowledgements I would like to thank the faculty, staff, and graduate students of the Earth and Environment Department and the Center for Remote Sensing, Boston University for their continuous support  ...  Just by labeling reference pixels of oil spills and clean ocean water at the time when oil spills occurred, it is possible to detect changes happened in ocean and classify them as oil spills or other kinds  ... 
doi:10.1016/j.rse.2014.01.011 fatcat:vmgayx4zf5ftnn5css3yx3plnq

Self-supervised Learning in Remote Sensing: A Review [article]

Yi Wang, Conrad M Albrecht, Nassim Ait Ali Braham, Lichao Mou, Xiao Xiang Zhu
2022 arXiv   pre-print
Further, we provide a preliminary benchmark of modern SSL algorithms on popular remote sensing datasets, verifying the potential of SSL in remote sensing and providing an extended study on data augmentations  ...  In this paper, we provide an introduction to, and a review of the concepts and latest developments in SSL for computer vision in the context of remote sensing.  ...  In 2019 he was a Visiting Researcher with the Cambridge Image Analysis Group (CIA), University of Cambridge, UK.  ... 
arXiv:2206.13188v1 fatcat:ibvp4ug5xbfbjkznrm6r2vycou

Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community

John E. Ball, Derek T. Anderson, Chee Seng Chan
2017 Journal of Applied Remote Sensing  
Whereas remote sensing (RS) possesses a number of unique challenges, primarily related to sensors and applications, inevitably RS draws from many of the same theories as CV; e.g., statistics, fusion, and  ...  machine learning, to name a few.  ...  In oil spill detection, Brekke and Solberg 396 point out that training data are scarce. Oil spills are very rare, which usually means oil spill detection approaches are anomaly detectors.  ... 
doi:10.1117/1.jrs.11.042609 fatcat:tdbssxma3fettcjy5iqgo6afwa

Table of Contents

2021 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS  
MIXUP FOR REMOTE SENSING IMAGES Ziyu Zhang, Zhixi Feng, Shuyuan Yang, Xidian University, China WE3.O-8.6: YOLORS-LITE: A LIGHTWEIGHT CNN FOR REAL-TIME OBJECT DETECTION ..........................  ...  FROM A MAPPING PERSPECTIVE: PIXELWISE ......................  ... 
doi:10.1109/igarss47720.2021.9553380 fatcat:zm7sioez6vgblpj25frkkxtfc4
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