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The Nord Stream pipeline gas leaks released approximately 220,000 tonnes of methane into the atmosphere

Environmental Science and Ecotechnology 2022年第4期12卷 3-7页

作者： Mengwei Jia Fei Li Yuzhong Zhang Mousong Wu Yingsong Li Shuzhuang Feng Hengmao Wang Huilin Chen Weimin Ju Jun Lin Jianwei Cai Yongguang Zhang Fei Jiang Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System ScienceNanjing UniversityNanjingJiangsu Province210023China Key Laboratory of Coastal Environment and Resources of Zhejiang Province School of EngineeringWestlake UniversityHangzhouZhejiang Province310030China Joint International Research Laboratory of Atmospheric and Earth System Sciences School of Atmospheric SciencesNanjing UniversityNanjingJiangsu Province210023China China Centre for Resources Satellite Data and Application Beijing100094China International Joint Carbon Neutrality Laboratory NanjingJiangsu Province210023China Nantong Academy of Intelligent Sensing NantongJiangsu Province226000China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application NanjingJiangsu Province210023China Frontiers Science Center for Critical Earth Material Cycling Nanjing UniversityNanjingJiangsu Province210023China

Sudden mega natural gas leaks of two Nord Stream pipelines in the Baltic Sea(Denmark)occurred from late September to early October 2022,releasing large amounts of methane into the *** inferred the methane emissions of this event based on surface in situ observations using two inversion methods and two meteorological reanalysis datasets,supplemented with satellite-based *** conclude that approximately 220±30 Gg of methane was released from September 26 to October 1,2022.

关键词： methane approximate conclude

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Image-to-image translation with multi-path consistency regularization

arXiv

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arXiv 2019年

作者： Lin, Jianxin Xia, Yingce Wang, Yijun Qin, Tao Chen, Zhibo CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China University of Science and Technology of China Microsoft Research Asia

Image translation across different domains has attracted much attention in both machine learning and computer vision communities. Taking the translation from source domain Ds to target domain Dt as an example, existing algorithms mainly rely on two kinds of loss for training: One is the discrimination loss, which is used to differentiate images generated by the models and natural images;the other is the reconstruction loss, which measures the difference between an original image and the reconstructed version through Ds → Dt → Ds translation. In this work, we introduce a new kind of loss, multi-path consistency loss, which evaluates the differences between direct translation Ds → Dt and indirect translation Ds → Da → Dt with Da as an auxiliary domain, to regularize training. For multi-domain translation (at least, three) which focuses on building translation models between any two domains, at each training iteration, we randomly select three domains, set them respectively as the source, auxiliary and target domains, build the multi-path consistency loss and optimize the network. For two-domain translation, we need to introduce an additional auxiliary domain and construct the multi-path consistency loss. We conduct various experiments to demonstrate the effectiveness of our proposed methods, including face-toface translation, paint-to-photo translation, and deraining/de-noising translation. Copyright © 2019, The Authors. All rights reserved.

关键词： Iterative methods

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SAR Moving Target Segmentation and Removal Based on Deep Learning 8th

SAR Moving Target Segmentation and Removal Based on Deep L...

引用

8th EAI International Conference on Machine Learning and Intelligent Communications, MLICOM 2023

作者： Wu, Yifan Qi, Xiyu Huang, Lijia Zhang, Bingchen Yan, Lili Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100190 China China Centre for Resources Satellite Data and Application Beijing100094 China

ISBN: (纸本)9783031717154

Synthetic Aperture Radar (SAR) stands as an integral part of advanced remote sensing technology. Nevertheless, practical applications experience inevitable disturbances from moving target noise, compromising both image integrity and target detection performance. This paper introduces a pioneering approach reliant on deep learning principles for the elimination of moving target noise within SAR imaging. Firstly, we use the Back-Projection (BP) algorithm to form the foundational images from echo signals. Employing the Unet network, we subsequently acquire a segmentation map of the moving target noise. By subtracting this segmented noise map from the original image, we succeed in the effective erasure of moving targets, yielding a resultant image devoid of moving target noise. Experimental validation demonstrates that our method can effectively remove moving target noise and yield SAR images that solely contain static scenes. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Deep learning

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Topology-based automatic 3D modeling from multiple images

Topology-based automatic 3D modeling from multiple images

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Long Zhang Xuejin Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei P. R. China

3D reconstruction from multiple-view images has drawn a lot of attentions in computer graphics and computer vision communities. Traditional techniques usually end at discrete 3D point clouds computed from feature correspondence. However, geometric structure remains ambiguous in these unstructured point clouds, especially for man-made objects like buildings, indoor scenes. This paper proposes a new method to automatically reconstruct the main geometric structure of the scene composed of planar faces. First, dense 3D point clouds are reconstructed by applying patch-based multi-view stereo (PMVS) algorithm [1]. Then 3D planar primitives are extracted using a RANSAC-based approach [2]. We present a novel method to analyze the adjacency relations of the planar primitives to estimate the 3D intersection lines on the corresponding faces. Junctions and polygonal faces are computed from the 3D intersection lines along with complementary image information to compose the topology structure. Finally, texture for each face is extracted from the image under the best view. Experimental results demonstrate the feasibility of our system by successfully reconstructing the main structure of a wide range of scenes and constructing a texture-mapped piecewise-planar 3D model from images in multiple views.

关键词： Three-dimensional displays Image reconstruction Solid modeling Computational modeling Junctions Topology Surface reconstruction

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GLOBAL PATCH MATCHING

GLOBAL PATCH MATCHING

引用

ISPRS geospatial Week 2017

作者： Huang, X. Hu, K. Ling, X. Zhang, Y. Lu, Z. Zhou, G. Wuhan Engineering Science and Technology Institute Jiangda Road 30 Wuhan China Wuhan Sense Tour Tecnhonogy Company Luoshi South Road 320 Wuhan China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China School of Remote Sensing and Information Engineering Wuhan University China

This paper introduces a novel global patch matching method that focuses on how to remove fronto-parallel bias and obtain continuous smooth surfaces with assuming that the scenes covered by stereos are piecewise continuous. Firstly, simple linear iterative cluster method (SLIC) is used to segment the base image into a series of patches. Then, a global energy function, which consists of a data term and a smoothness term, is built on the patches. The data term is the second-order Taylor expansion of correlation coefficients, and the smoothness term is built by combing connectivity constraints and the coplanarity constraints are combined to construct the smoothness term. Finally, the global energy function can be built by combining the data term and the smoothness term. We rewrite the global energy function in a quadratic matrix function, and use least square methods to obtain the optimal solution. Experiments on Adirondack stereo and Motorcycle stereo of Middlebury benchmark show that the proposed method can remove fronto-parallel bias effectively, and produce continuous smooth surfaces. © Authors 2017.

关键词： 3D Label Algorithm Fronto-parallel Bias Global Optimization Matrix Energy Function Patch Matching

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Layer-wise coordination between encoder and decoder for neural machine translation 18

Layer-wise coordination between encoder and decoder for neur...

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Proceedings of the 32nd International Conference on Neural information Processing systems

作者： Tianyu He Xu Tan Yingce Xia Di He Tao Qin Zhibo Chen Tie-Yan Liu CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Microsoft Research Key Laboratory of Machine Perception MOE School of EECS Peking University

Neural Machine Translation (NMT) has achieved remarkable progress with the quick evolvement of model structures. In this paper, we propose the concept of layer-wise coordination for NMT, which explicitly coordinates the learning of hidden representations of the encoder and decoder together layer by layer, gradually from low level to high level. Specifically, we design a layer-wise attention and mixed attention mechanism, and further share the parameters of each layer between the encoder and decoder to regularize and coordinate the learning. Experiments show that combined with the state-of-the-art Transformer model, layer-wise coordination achieves improvements on three IWSLT and two WMT translation tasks. More specifically, our method achieves 34.43 and 29.01 BLEU score on WMT16 English-Romanian and WMT14 English-German tasks, outperforming the Transformer baseline.

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Disparity-compensated Inter-layer Motion Prediction Using Standardized HEVC Extensions

Disparity-compensated Inter-layer Motion Prediction Using St...

引用

IEEE International Symposium on Circuits and systems

作者： Li Chen Miska M. Hannuksela Houqiang Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei China Nokia Technologies Tampere Finland

ISBN: (纸本)9781479983926

The scalable and multiview extensions of the High Efficiency Video Coding share the same high-level syntax coding structure. For the scalable extension, the motion field of the inter-layer reference picture is modified through Motion Field Mapping before used for motion vector prediction. However, the motion field of the inter-layer reference picture is used without modification in the multiview extension. In this paper, a disparity-compensated inter-layer motion prediction is proposed for multiview video coding to achieve disparity compensation in inter-layer motion prediction using the scaled reference layer offset. The experimental results show that comparing with the multiview extension anchor, the proposed method achieves an average of 1.1% bitrate reduction.

关键词： Video coding motion vector Scalability

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Placement Optimization of Caching UAV-Assisted Mobile Relay Maritime Communication

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China Communications 2020年第8期17卷 209-219页

作者： Jun Zhang Fengzhu Liang Bin Li Zheng Yang Yi Wu Hongbo Zhu Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and TelecommunicationsNanjing 210003China Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing 210003China School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application Fujian Normal UniversityFuzhou 350007China

Recently, due to the deployment flexibility of unmanned aerial vehicles(UAVs), UAV-assisted mobile relay communication system has been widely used in the maritime communication. However, the performance of UAV-assisted mobile relay communication system is limited by the capacity of wireless backhaul link between base station and UAV. In this paper, we consider a caching UAV-assisted decode-and-forward relay communication system in a downlink maritime communication. For the general case with multiple users, the optimal placement of UAV is obtained by solving the average achievable rate maximization problem through the one-dimensional linear search. For a special case with single user, we derive a semi closedform expression of the optimal placement of UAV. Simulation results confirm the accuracy of analytical results and show that the optimal placement of UAV and the average achievable rate significantly depend on the cache capacity at UAV. We also show the difference between the performances of the air-to-ground model and the air-to-sea model.

关键词： UAV caching placement optimization achievable rate maritime communication

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An Azimuth Resample Method For Bistatic SAR Motion Compensation

An Azimuth Resample Method For Bistatic SAR Motion Compensat...

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8th European Conference on Synthetic Aperture Radar

作者： Xiaolan Qiu Bin Han Dadi Meng Donghui Hu Chibiao Ding Key Laboratory of Technology in Geo-spatial Information Processing and Application System IECAS China Institute of Electronics Chinese Academy of Sciences (IECAS) China

Motion compensation is an indispensable step for generating a high quality image in the airborne SAR system. In bistatic SAR, there are two separate platforms and their velocities cannot keep same all the time. So the echoes are transmitted and received at uniform positions, respectively, which deteriorate the imaging results. In this paper, an azimuth resample method for compensating the velocity variance along the flying direction is promoted, and the difference of azimuth resample between monostatic SAR and bistatic SAR is pointed out. Finally, simulated results show the validity of the method.

关键词： Yttrium Transmitters

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Parameterization, sensitivity, and uncertainty of 1-D thermodynamic thin-ice thickness retrieval

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Acta Oceanologica Sinica 2024年第7期43卷 93-111页

作者： Tianyu Zhang Mohammed Shokr Zhida Zhang Fengming Hui Xiao Cheng Zhilun Zhang Jiechen Zhao Chunlei Mi School of Geospatial Engineering and Science Sun Yat-Sen University/Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China Key Laboratory of Comprehensive Observation of Polar Environment(Sun Yat-Sen University) Ministry of EducationZhuhai 519082China State Key Laboratory of Remote Sensing Science College of Global Change and Earth System ScienceBeijing Normal UniversityBeijing 100875China Science and Technology Branch Environment and Climate Change CanadaToronto M3H5T4Canada Qingdao Innovation and Development Base(Centre) Harbin Engineering UniversityQingdao 266500China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China

Retrieval of Thin-Ice Thickness(TIT)using thermodynamic modeling is sensitive to the parameterization of the independent variables(coded in the model)and the uncertainty of the measured input *** article examines the deviation of the classical model’s TIT output when using different parameterization schemes and the sensitivity of the output to the ice ***,it estimates the uncertainty of the output in response to the uncertainties of the input *** parameterized independent variables include atmospheric longwave emissivity,air density,specific heat of air,latent heat of ice,conductivity of ice,snow depth,and snow *** input parameters include air temperature,ice surface temperature,and wind *** the independent variables,the results show that the highest deviation is caused by adjusting the parameterization of snow conductivity and depth,followed ice *** sensitivity of the output TIT to ice thickness is highest when using parameterization of ice conductivity,atmospheric emissivity,and snow conductivity and *** retrieved TIT obtained using each parameterization scheme is validated using in situ measurements and satellite-retrieved *** in situ measurements,the uncertainties of the measured air temperature and surface temperature are found to be *** resulting uncertainties of TIT are evaluated using perturbations of the input data selected based on the probability distribution of the measurement *** results show that the overall uncertainty of TIT to air temperature,surface temperature,and wind speed uncertainty is around 0.09 m,0.049 m,and−0.005 m,respectively.

关键词： Arctic sea ice 1-D thermodynamic ice model thin-ice thickness sea ice parameterization

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