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arXiv 2019年

作者： Chen, Joya Liu, Dong Luo, Bin Peng, Xuezheng Xu, Tong Chen, Enhong Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of China CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Tencent TaiQ Team

For a long time, object detectors have suffered from extreme imbalance between foregrounds and backgrounds. While several sampling/reweighting schemes have been explored to alleviate the imbalance, they are usually heuristic and demand laborious hyper-parameters tuning, which is hard to achieve the optimality. In this paper, we first reveal that such the imbalance could be addressed in a learning-based manner. Guided by this illuminating observation, we propose a novel Residual Objectness (ResObj) mechanism that addresses the imbalance by end-to-end optimization, while no further hand-crafted sampling/reweighting is required. Specifically, by applying multiple cascaded objectness-related modules with residual connections, we formulate an elegant consecutive refinement procedure for distinguishing the foregrounds from backgrounds, thereby progressively addressing the imbalance. Extensive experiments present the effectiveness of our method, as well as its compatibility and adaptivity for both region-based and one-stage detectors, namely, the RetinaNet-ResObj, YOLOv3-ResObj and FasterRCNN-ResObj achieve relative 3.6%, 3.9%, 3.2% Average Precision (AP) improvements compared with their vanilla models on COCO, respectively. Copyright © 2019, The Authors. All rights reserved.

关键词： Object detection

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3D reconstruction and error analysis of multi-view space-borne SAR images under different configurations

3D reconstruction and error analysis of multi-view space-bor...

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IET International Radar Conference 2018, IRC 2018

作者： Wang, Chao Qiu, Xiaolan Li, Fangfang Lei, Bin University of the Chinese Academy of Sciences Beijing China Institute of Electrics Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electrics Chinese Academy of Sciences Beijing China

Synthetic aperture radar (SAR) has a good ability to detect the microwave scattering characteristics of the target and has a good capability of slant range Doppler positioning. Using multi-view SAR images in combination with image matching and positioning equations, the 3D position of the target can be obtained. In the past, multi-view 3D reconstruction mainly used side-looking images with parallel trajectories but different incident angles. That method is not universal for different configurations and lacks analysis of the relationship between solution and parameter error. This study aims at the problem of multi-view SAR 3D reconstruction. The authors establish general 3D reconstruction equations that can be used for non-parallel track and non-side-looking and the solution method is deduced. Based on this, an analysis method of error sensitivity is proposed and the dependence relationship between the reconstruction error and configuration, velocity, position, and slant range is analysed. The correctness of this method is verified by simulation experiments, which provides guidance for selection of configuration and sensor accuracy when applying 3D reconstruction. © 2019 Institution of Engineering and technology. All rights reserved.

关键词： Synthetic aperture radar

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The mechanism of farmland marginalization in Chinese mountainous areas:Evidence from cost and return changes

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Journal of Geographical Sciences 2019年第4期29卷 531-548页

作者： LI Shengfa LI Xiubin Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of GeographyGuangzhou 510070China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchCASBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China

Farmland marginalization has become the main trend of land-use change in the mountainous areas of China. Using annual survey data of major agricultural production costs and earnings at national and provincial levels in China, this study aims to analyze the reasons and mechanism behind farmland marginalization in mountainous areas. We find that farmers on plains are able to reduce their per mu labor input effectively through intensive use of agricultural machinery, which has minimized the impact of the increase in labor price. However, it is extremely challenging for farmers in mountainous areas to use the same method owing to the rough terrain. Thus, per laborer farming area in these areas has increased relatively slowly, causing a widening gap in agricultural labor productivity between the two regions. With the rapid rise in labor costs since 2003, the marginalization of cultivated land in mountainous areas is evident. In 2013, the net profit of agricultural production in mountainous China fell below zero. Since 2000, the land-use and land-cover change in these areas was characterized by the reduction of farmland area, reforestation, and the enhancement of the NDVI value. The high correlation between the NDVI change rate and the ratio of change in farmland(r = –0.70) and forest(r = 0.91) in mountainous areas at provincial level further attests to the trend of farmland marginalization there. Finally, we summarize the mechanism of such marginalization against the backdrop of the rapid increase in the opportunity cost of farming and the rapid fall of agricultural labor forces in mountainous areas. This study contributes to a deep understanding of the development process of farmland marginalization and abandonment as well as forest transition in Chinese mountainous areas.

关键词： farmland marginalization farmland abandonment labor costs returns agricultural labor productivity mountainous areas China

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A STUDY ON THE FREQUENCY AND AZIMUTH COHERENCE OF HIGH-RESOLUTION SAR IMAGE

A STUDY ON THE FREQUENCY AND AZIMUTH COHERENCE OF HIGH-RESOL...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Wenji Xing Xiaolan Qiu Chibiao Ding The Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

High-resolution SAR has large transmitting bandwidth and wide synthetic aperture. How to understand and take advantage of the variation characteristics of SAR scattering characteristics with angle and frequency is a topic that worth studying. This article establishes a coherence matrix of sub-band and sub-aperture SAR images, and analyzes its ability to classify scattering mechanism. Experiments are conducted using the TerraSAR-X high-resolution data of different scenarios, and some meaningful results are got, which may provide some support to the analysis and application of high-resolution SAR data.

关键词： Coherence Entropy Azimuth Radar polarimetry Synthetic aperture radar Image resolution

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Investigating the role of aerosol wet scavenging on global horizontal irradiance simulation in the WRF-Chem-solar model

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Applied Energy 2025年 396卷

作者： Su Wang Gang Huang Tie Dai Junji Cao Letu Husi Run Ma Cuina Li State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China State Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China University of Chinese Academy of Sciences Beijing 100049 China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD) Nanjing University of Information Science and Technology Nanjing 210044 China Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China State Key Laboratory of Remote Sensing Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100081 China Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science & Engineering Yibin 644005 China Meteorological Observation Center of China Meteorological Administration Beijing 100081 China

Solar energy emerges as a vital renewable resource with profound implications for future energy consumption. To improve the accuracy of global horizontal irradiance (GHI) simulation, this study integrates the Thompson and Eidhammer aerosol-aware cloud microphysics scheme with the aerosol module Goddard Ozone Chemistry Aerosol Radiation and Transport (GOCART) in the WRF-Solar model. Based on the new coupled aerosol-cloud interaction, a physical parametric aerosol wet scavenging scheme is developed to investigate its effects on aerosol and GHI simulations. Our results demonstrate that the updated wet removal enhances the spatial representation of aerosol optical depth (AOD) across China, particularly in regions influenced by anthropogenic aerosols such as Northern, Central and Eastern China. The average absolute mean bias (BIAS) value for AOD decreases by 20.00 %, leading to a 36.47 % improvement in reducing the overestimation of GHI under clear sky. The most remarkable BIAS reductions occur in Central (104.30 %), Western (45.70 %), and Eastern China (41.42 %) for GHI under clear sky, especially in high surface solar radiation zones (>500 W/m 2 ). Similar improvements are observed for GHI under all-sky conditions, with a national relative improvement of 29.91 %. Central, Eastern, and Western China show the most substantial BIAS reductions, with relative decreases of 57.48 %, 50.62 %, and 32.40 %, respectively. Overall, this study highlights the potential of the enhanced aerosol wet scavenging scheme to improve GHI simulation accuracy, providing valuable insights for advancing renewable energy initiatives.

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A COOPERATIVE MULTITEMPORAL SEGMENTATION METHOD FOR SAR AND OPTICAL IMAGES CHANGE DETECTION

A COOPERATIVE MULTITEMPORAL SEGMENTATION METHOD FOR SAR AND ...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Ling Wan Yuming Xiang Hongjian You Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

This paper proposes an extension version of our previous work MS-CC to achieve optical and SAR images change detection. The proposed method introduces a cooperative multitemporal segmentation, whose merging process considers the heterogeneity of SAR and optical images as parallel information, making sure that the multitemporal information can be fully utilized without interfering with each other. Then, the change detection strategy based on compound classification is carried out on the segmentation results, obtaining the multi-scale change detection maps. Experimental validation is conducted with GoaFen3 and Google Earth data.

关键词： Image segmentation Optical imaging Radar polarimetry Optical sensors Compounds Interference Stacking

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ON THE USE OF CNN FOR AUTOMATED QUALITY ASSESSMENT OF GF-3 POLARIMETRIC DATA

ON THE USE OF CNN FOR AUTOMATED QUALITY ASSESSMENT OF GF-3 P...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Songtao Shangguan Xiaolan Qiu Bin Lei The Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China

With the needs of quality assessment for massive GF-3 polarimetric data, a method based on common distribution targets has been proposed by Sha Jiang. However, it needs manually selection of those woodlands, and cannot be performed automatically. In this paper, an automated GF-3 full-polarization SAR data quality assessment method is conducted using a classic Convolution Neural Network (VGG-16). The network is pre-trained by Radarsat-2 PolSAR data and then trained by selected typical GF-3 scenes. It is supposed to learn the features of the targets, which satisfies the azimuthal symmetry and backscatter reciprocity and fulfills the quality assessment work. Several typical GF-3 strips data are used to test the method. Experiments show that the network can predict the plots of targets from a new scene under the interference of polarimetric distortion and noise. And, the quality assessment results by the network are consistent with the manual assessment results, which shows the effectiveness of the method.

关键词： Quality assessment Distortion Data integrity Strips Manuals Forestry Radar polarimetry

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Stereoscopic omnidirectional image quality assessment based on predictive coding theory

arXiv

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arXiv 2019年

作者： Chen, Zhibo Xu, Jiahua Lin, Chaoyi Zhou, Wei CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui230027 China

Objective quality assessment of stereoscopic omnidirectional images is a challenging problem since it is influenced by multiple aspects such as projection deformation, field of view (FoV) range, binocular vision, visual comfort, etc. Existing studies show that classic 2D or 3D image quality assessment (IQA) metrics are not able to perform well for stereoscopic omnidirectional images. However, very few research works have focused on evaluating the perceptual visual quality of omnidirectional images, especially for stereoscopic omnidirectional images. In this paper, based on the predictive coding theory of the human vision system (HVS), we propose a stereoscopic omnidirectional image quality evaluator (SOIQE) to cope with the characteristics of 3D 360-degree images. Two modules are involved in SOIQE: predictive coding theory based binocular rivalry module and multi-view fusion module. In the binocular rivalry module, we introduce predictive coding theory to simulate the competition between high-level patterns and calculate the similarity and rivalry dominance to obtain the quality scores of viewport images. Moreover, we develop the multi-view fusion module to aggregate the quality scores of viewport images with the help of both content weight and location weight. The proposed SOIQE is a parametric model without necessary of regression learning, which ensures its interpretability and generalization performance. Experimental results on our published stereoscopic omnidirectional image quality assessment database (SOLID) demonstrate that our proposed SOIQE method outperforms state-of-the-art metrics. Furthermore, we also verify the effectiveness of each proposed module on both public stereoscopic image datasets and panoramic image datasets. Copyright © 2019, The Authors. All rights reserved.

关键词： Binocular vision

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Deep learning-based air temperature mapping byfusing remote sensing, station, simulation and socioeconomic data

arXiv

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arXiv 2020年

作者： Shen, Huanfeng Jiang, Yun Li, Tongwen Cheng, Qing Zeng, Chao Zhang, Liangpei School of Resource and Environmental Sciences Wuhan University Wuhan430079 China School of Urban Design Wuhan University Wuhan430079 China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430079 China Collaborative Innovation Center of Geospatial Technology Wuhan430079 China Key Laboratory of Geographic Information System Ministry of Education Wuhan University Wuhan430079 China

Air temperature(Ta)isanessential climatologicalcomponentthatcontrolsand influences variousearth surface *** this study, we makethe first attempttoemploy deep learning for Ta mapping mainly based on space remote sensing and ground station *** that Ta varies greatly in space and time and is sensitive tomany factors, assimilation dataand socioeconomicdata are also included for a multi-source data fusion based ***, a5-layers structured deep belief network(DBN) isemployed to better capturethe complicatedand non-linear relationships between Taand different ***-wise pre-trainingprocess foressentialfeaturesextraction and fine-tuningprocess forweight parametersoptimization ensure the robust prediction of Ta spatio-temporal distribution. The DBN model was implemented for 0.01°daily maximum Ta mapping across China. The ten-fold cross-validation resultsindicate that the DBN model achieves promisingresults with the RMSEof1.996°C, MAEof1.539°C, and Rof 0.986at the national *** with multiple linear regression (MLR), back-propagation neural network (BPNN) and random forest (RF)method, the DBN modelreduces the MAE values by 1.340°C, 0.387°Cand0.222°C,*** analysis on spatialdistribution and temporal tendency of predictionerrors both validate the great potentials of DBN inTa estimation. Copyright © 2020, The Authors. All rights reserved.

关键词： Atmospheric temperature

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The Challenges of LEO based Navigation Augmentation system——Lessons Learned from Luojia-1A satellite

The Challenges of LEO based Navigation Augmentation System—...

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第十届中国卫星导航年会

作者： Lei Wang Ruizhi Chen Beizhen Xu Xinxin Zhang Tao Li Cailun Wu State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Collaborative Innovation Center for Geospatial Technology State Key Laboratory of Satellite Navigation System and Equipment Technology

The Low earth orbiter(LEO) based navigation signal transmitters has advantages in fast-changing geometry and low free space loss, which can be served as a complementary or extension of current MEO/GEO based GNSS. Broadcasting navigation signals from LEO can significantly reduce the convergence time for the long baseline RTK\precise point positioning(PPP) and improve the signal strength. Hence LEO based navigation is considered as one of the key technology of next-generation positioning, navigation and timing(PNT) systems. This study assessed the pseudorange and carrier phase measurements observed from Luojia-1 A satellite with the geometry-free combination method and the zero-baseline method. The assessment results indicate that the pseudorange precision variation subject to elevation angle is also caused by both signal strength variation and multipath effect. The pseudorange measurement precision reaches 0.7 m and 0.8 m respectively for the dual frequency signals and the carrier phase precision is 2.8 mm and 2.6 mm respectively. Based on the data collected from Luojia-1 A satellite, the challenges of LEO navigation augmentation data processing were addressed. The most distinguished features of LEO navigation signals are their large signal strength variation, large Doppler variation and large acceleration variation. All these features have adversary effect on LEO signal processing and data processing, which has not been revealed. These challenges still need to be seriously investigated to further improve the performance of the LEO based navigation augmentation system.

关键词： Navigation Augmentation Signal Augmentation Low Earth Orbiters Luojia-1A

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