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China's poverty assessment and analysis under the framework of the UN SDGs based on multisource remote sensing data

地球空间信息科学学报（英文版） 2024年第1期27卷 111-131页

作者： Mengjie Wang Yanjun Wang Fei Teng Shaochun Li Yunhao Lin Hengfan Cai Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying Mapping and Remote SensingHunan University of Science and TechnologyXiangtanChina National-Local Joint Engineering Laboratory of Geo-spatial Information Technology Hunan University of Science and TechnologyXiangtanChina School of Earth Sciences and Spatial Information Engineering Hunan University of Science and TechnologyXiangtanChina Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying Mapping and Remote SensingHunan University of Science and TechnologyXiangtanChina National-Local Joint Engineering Laboratory of Geo-spatial Information Technology Hunan University of Science and TechnologyXiangtanChina

Poverty has always been a global concern that has restricted human *** first goal(SDG 1)of the United Nations Sustainable Development Goals(SDGs)is to eliminate all forms of poverty all over the *** establishment of a scientific and effective localized SDG 1 evaluation and monitoring method is the key to achieving SDG *** paper proposes SDG 1 China district and county-level localization evaluation method based on multi-source remote sensing data for the United Nations Sustainable Development *** temporal and spatial distribution characteristics of China's poverty areas and their SDG 1 evaluation values in 2012,2014,2016,and 2018 have been *** on the SDGs global indicator framework,this paper first constructed SDG 1 China's district and county localization indicator system and then extracted multidimensional feature factors from nighttime light images,land cover data,and digital elevation model ***,we establish SDG 1 China's localized partial least squares estimation model and SDG 1 China's localized machine learning estimation ***,we analyze and verify the spatiotemporal distribution characteristics of China's poverty areas and counties and their SDG 1 evaluation *** results show that SDG 1 China's district and county localization indicator system proposed in this study and SDG 1 China's localized partial least squares estimation model can better reflect the poverty level of China's districts and *** estimated model R2 is 0.65,which can identify 72.77%of China's national poverty *** 2012 to 2018,the spatial distribution pattern of SDG evaluation values in China's districts and counties is that the SDG evaluation values gradually increase from western China to eastern *** addition,the average SDG 1 evaluation value of China's districts and counties increased by 23%from 2012 to *** paper is oriented to the United Nations SDGs frame-work,explores the SDG 1 localized evalu

关键词： Multisource remote sensing data Sustainable Development Goals(SDGs) poverty indicator system partial least squares machine learning

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iWavePro: An improved framework for iWave++ 56

iWavePro: An improved framework for iWave++

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56th IEEE International Symposium on Circuits and Systems, ISCAS 2023

作者： Xue, Dongmei Dong, Cunhui Ye, Fan Chen, Hang Kang, Bowei Li, Li Liu, Dong University of Science and Technology of China Cas Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Hefei230027 China

ISBN: (纸本)9781665451093

End-to-end image coding methods based on wavelet-like transform have made great progress in recent years. The most advanced one is iWave++, which adopts multi-level lifting schemes based on convolutional neural networks. However, iWave++ still has many unresolved problems. First, the independent entropy coding of each component makes it impossible to use the correlation between components better. Secondly, additive wavelet transform limits the nonlinear ability of learnable wavelet transform. Moreover, the offline training strategy makes the iWave++ unable to adjust according to the content. In this paper, we propose an improved framework for iWave++ called iWave-Pro. iWavePro is designed with several techniques to overcome the problems mentioned above. These techniques are the joint multi-component Gaussian mixture entropy coding, the affine wavelet-like transform, and the online training. Experimental results show that our method can save 10.73% bit rate compared with iWave++ at the same quality. © 2023 IEEE.

关键词： Convolutional neural networks

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A space-based radar nonlinear tracking method for air targets based on VB-PHD filter 2

A space-based radar nonlinear tracking method for air target...

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2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Fang, Linlin Zhong, Lihua Han, Bing Hu, Yuxin Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798331515669

Space-based radar has better coverage and is not limited by the curvature of the earth. Aircraft target tracking is particularly important in space-based radar system. However, the long observation distance and strong nonlinear observation increases the challenge of target tracking. Therefore, we proposed a space-based radar nonlinear tracking method for air targets based on variational Bayesian probability hypothesis density (VB-PHD) filter. The relationship between state and observation is established. Then, the VB method is adopted to deal with uncertainty of measurement noise variances. Besides, the cubature filter is introduced to deal with the strongly nonlinear models, and the recursion process is completed by using the third-order spherical radial volume rule. Finally, simulation scenarios with different measurement noise parameters were constructed, and the tracking result comparisons show that it effectively solves nonlinear problems, and tracking precision can be significantly improved. © 2024 IEEE.

关键词： Space-based radar

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HPHR-SAR-Net: Hyperpixel High-Resolution SAR Imaging Network Based on Nonlocal Total Variation

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2023年 16卷 8595-8608页

作者： Zhou, Guoru Xu, Zhongqiu Fan, Yizhe Zhang, Zhe Qiu, Xiaolan Zhang, Bingchen Fu, Kun Wu, Yirong Chinese Academy of Sciences Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing100045 China University of Chinese Academy of Sciences Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing100045 China Suzhou Aerospace Information Research Institute Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology Suzhou215009 China

High resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolution SAR imaging algorithms face several challenges. First, these algorithms tend to focus on local information, neglecting nonlocal information between different pixel patches. Second, speckle is more pronounced and difficult to filter out in high-resolution SAR images. Third, the process of high-resolution SAR imaging generally involves high time and computational complexity, making real-time imaging difficult to achieve. To address these issues, we propose a hyperpixel high-resolution SAR imaging network (HPHR-SAR-Net) for rapid despeckling in high-resolution modes. Based on the concept of hyperpixel techniques, we initially combine nonconvex and nonlocal total variation as compound regularization. This approach more effectively despeckles and manages the relationship between pixels while reducing bias effects caused by convex constraints. Subsequently, we solve the compound regularization model using the alternating direction method of multipliers (ADMM) algorithm and unfold it into a deep unfolding network (DUN). The network's parameters are adaptively learned in a data-driven manner, and the learned network significantly increases imaging speed. Additionally, the proposed HPHR-SAR-Net is compatible with high-resolution imaging modes, such as spotlight, staring spotlight, and sliding spotlight. In this article, we demonstrate the superiority of HPHR-SAR-Net through experiments in both simulated and real SAR scenarios. The results indicate that HPHR-SAR-Net can rapidly perform high-resolution SAR imaging from raw echo data, producing accurate imaging results. © 2008-2012 IEEE.

关键词： Radar imaging

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A novel synthetic aperture radar scattering model for sea surface with breaking waves

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Acta Oceanologica Sinica 2022年第4期41卷 138-145页

作者： Xiaochen Wang Yuxin Hu Bing Han Wei Tian Chunhua Zhang Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of SciencesBeijing 100190China The box51111 Beijing 100190China

In this study a novel synthetic aperture radar(SAR)scattering model for sea surface with breaking waves is *** with existing models,the proposed model considers an empirical relationship between wind speed and wave breaking scattering to present the contribution of wave ***,the scattering weight factor p,and wave breaking rate q,are performed to present the contribution of the quasi-specular scattering term,Bragg scattering term,and wave breaking scattering term to the total scattering from the sea *** explore the modeling accuracy of sea-surface scattering,a simulated normalized radar cross-section(NRCS)and measured NRCS are *** proposed model generated the simulated NRCS and a matching GF-3 dataset was used for the measured *** was revealed that the performance of the VV polarization of our model was much better than that of HH polarization,with a correlation of 0.91,bias of-0.14 dB,root mean square error(RMSE)of 1.26 dB,and scattering index(SI)*** addition,the novel model is explored and compared with the geophysical model of CMODs and satellite-measured NRCS from GF-3 SAR wave mode *** an incidence angle 40°–41°,the relationship between the NRCS and wind speed,relative wind direction is *** with the SAR-measured NRCS,the performance of VV polarization was much better than HH polarization,with a correlation of 0.99,bias of-0.25 dB,RMSE of 0.64 dB,and SI of-0.04.

关键词： synthetic aperture radar scattering model sea surface wave breaking

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Remote Sensing Image Matching and Localization Method Based on the MySQL Multi-Feature Control Point Database 9

Remote Sensing Image Matching and Localization Method Based ...

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9th International Conference on Image, Vision and Computing, ICIVC 2024

作者： Zilu, Zhao Feng, Wang Hongjian, You Peifeng, Li Tingtao, Zhang Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350385991

With the increase in the number of remote sensing satellites and imaging modes, the amount of data for acquiring remote sensing images has greatly increased. Effectively and stably performing geometric positioning on remote sensing images is the foundation of remote sensing applications. This paper proposes a remote sensing image matching and positioning method based on a multi-feature control point database in MySQL. Firstly, a feature control point database in MySQL is constructed based on multiple feature methods. Subsequently, the target image is matched from coarse to fine using region features and point features in the feature control point database. Experimental results show that, on three target remote sensing images, the coarse-to-fine matching method based on MySQL multi-feature database can achieve good geometric positioning effects, with a positioning accuracy of around 0.5 pixels. © 2024 IEEE.

关键词： Optical remote sensing

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First assessment of Noise-Equivalent Sigma-Zero in GF3-02 TOPSAR mode with sea surface wind speed retrieval

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Acta Oceanologica Sinica 2023年第10期42卷 84-96页

作者： Junxin Yang Lihua Zhong Xinzhe Yuan Xiaochen Wang Bing Han Yuxin Hu Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Chinese Academy of SciencesBeijing 100190China School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijing 100049China National Satellite Ocean Application Service Beijing 100081China

Gaofen-3-02(GF3-02)is the first C-band synthetic aperture radar(SAR)satellite with terrain observation with progressive scans of SAR(TOPSAR)imaging mode in China,which plays an essential role in marine environment *** the weak scattering characteristics of the ocean,the system thermal noise superimposed on SAR images has significant interference,especially in cross-polarization ***-Equivalent Sigma-Zero(NESZ)is a measure of the sensitivity of the radar to areas of low *** NESZ is defined to be the scattering cross-section coefficient of an area which contributes a mean level in the image equal to the signal-independent additive noise *** TOPSAR,NESZ exhibits the shape of the SAR scanning gain curve in the azimuth and the shape of the antenna pattern in the ***,the accurate measurement of NESZ plays a vital role in the application of spaceborne SAR sea surface cross-polarization *** paper proposes a theoretical calculation method for the NESZ curve in GF3-02 TOPSAR mode based on SAR noise inner calibration data and the imaging algorithm.A method for correcting the error existing in the theoretical curve of NESZ is also proposed according to the relationship between sea surface backscattering and wind speed and the same characteristics of target scattering in the overlapping area of adjacent *** to assessment with wide-swath TOPSAR cross-polarization data,the GF3-02 TOPSAR mode has a very low thermal noise level,which is better than−33 dB at the edge of each beam,and controlled below−38 dB at the center of the *** two-dimensional reference curves of the NESZ of each beam are provided to the GF3-02 TOPSAR *** discussing the relationship between normalized radar cross section(NRCS)and wind speed,we provide a formula for NRCS related to wind speed and radar incidence *** with the NRCS derived from this formula and the NESZ-subtracted NRCS of SAR images,the bias is−0.0048

关键词： GF3-02 TOPSAR Noise-Equivalent Sigma-Zero(NESZ) cross-polarization normalized radar cross section(NRCS) sea surface wind

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The Potential of Multi-Agent Consensus Equilibrium for Synthetic Aperture Radar processing 15

The Potential of Multi-Agent Consensus Equilibrium for Synth...

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15th European Conference on Synthetic Aperture Radar, EUSAR 2024

作者： Fan, Yizhe Li, Jie Wang, Kun Zhang, Bingchen Wu, Yirong Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing101408 China

ISBN: (纸本)9783800762873

Multi-agent consensus equilibrium(MACE) mechanism is a generalization of popular used PnP-ADMM method in computational imaging. We propose a novel SAR processing framework based on MACE mechanism, named by MACE-SAR. The proposed framework offers the possibility to unify various SAR processing agents of both data-driven learned priors and physics-based regularization priors, enabling the integration of diverse functions and enhance the image reconstruction quality. We exemplifies how the MACE-SAR framework can be customized to combine SAR image formation, feature enhancement, image denoising, target detection, etc. The effectiveness of the framework is demonstrated through experiments conducted on simulated and Gaofen-3 satellite real data. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Synthetic aperture radar

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Multi-scale Region-level Graph Convolutional Network for Unsupervised SAR image Change Detection

Multi-scale Region-level Graph Convolutional Network for Uns...

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2024 International Conference on Remote Sensing, Mapping, and Image processing, RSMIP 2024

作者： Zhu, Jingxing Liu, Rui Wang, Feng You, Hongjian Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Chinese Academy of Sciences Beijing China Aerospace Information Research Institute Chinese Academy of Sciences Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781510680012

With the rapid advancement of synthetic aperture radar (SAR) sensors, it has become more important to extract change information between high-resolution SAR images. Considering the efficacy and robustness of segmentation-based strategy in solving fine-resolution images, as well as the excellent performance of deep learning in feature extraction, therefore, in this paper, we propose an unsupervised region-level graph convolutional network (URGCN) for SAR change detection. Firstly, we propose a multi-temporal joint segmentation method to generate multi-level regions. This method can simultaneously segment bi-temporal SAR images and automatically align bi-temporal regions during segmentation process. We then perform pre-classification on difference images generated by neighborhood ratio detector. The high confidence training samples are selected through hierarchical clustering. Thirdly, we encode the segmented regions are as a graph structure and construct GCN model. The graph can capture the spatial and temporal structure information. Finally, the GCN model parameters are optimized by labeled samples and inferring unlabeled regions. Experimental results on two VHR SAR change detection datasets demonstrated that the proposed method can extract complete change information with high accuracy compared to alternative approaches. © 2024 SPIE.

关键词： Change detection

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Retrieval of Significant Wave Height Under Typhoon Conditions from Gaofen-3 SAR Imagery

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Journal of Ocean University of China 2022年第1期21卷 81-90页

作者： WANG Xiaochen HAN Bing ZHONG Lihua YUAN Xinzhe Aerospace Information Research Institute Chinese Academy of ScienceBeijing 100190China Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems Aerospace Information Research InstituteChinese Academy of ScienceBeijing 100190China The National Satellite Ocean Applications Center Beijing 100081China

The objective of this paper is to propose an empirical method to inverse significant wave height(SWH)under typhoon conditions from collected dual-polarization Gaofen(GF)-3 synthetic aperture radar(SAR)*** typhoon scenes were cap-tured from narrow scan(NSC)and wide scan(WSC)images,and collocated with European Center for Medium-Range Weather Fore-casts reanalysis data of(ECMWF).To improve the quality of GF-3 SAR images,the recalibration over rainforest and de-scalloping were carried *** establish the empirical relationship between SAR-derived parameters and collocated SWH,the sensitivity analysis of typical parameters about the normalized radar cross section(Nrcs)and imagery variance(Cvar)were performed to both VV and VH polarized *** scenes from GF-3 SAR imagery under typhoon conditions were used for training the model by the multivari-ate least square regression,and one scene was used for preliminary *** was found that the joint retrieval model based on VV and VH polarized SAR imagery performed better than any single polarized *** results,verified by using ECMWF data,revealed the soundness of this approach,with a correlation of 0.95,bias of 0 m,RMSE of 0.44 and SI of 0.01 when VV polarization and VH polarization data were both used.

关键词： Gaofen-3 SAR typhoon significant wave height

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