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arXiv 2023年

作者： Peng, Dehua Gui, Zhipeng Gui, Jie Wu, Huayi School of Remote Sensing and Information Engineering 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 Wuhan University Wuhan430079 China School of Cyber Science and Engineering Southeast University Nanjing211189 China Engineering Research Center of Blockchain Application Supervision and Management Southeast University Nanjing211189 China Purple Mountain Laboratories Nanjing210000 China

Boundary point detection aims to outline the external contour structure of clusters and enhance the inter-cluster discrimination, thus bolstering the performance of the downstream classification and clustering tasks. However, existing boundary point detectors are sensitive to density heterogeneity or cannot identify boundary points in concave structures and high-dimensional manifolds. In this work, we propose a robust and efficient boundary point detection method based on Local Direction Dispersion (LoDD). The core of boundary point detection lies in measuring the difference between boundary points and internal points. It is a common observation that an internal point is surrounded by its neighbors in all directions, while the neighbors of a boundary point tend to be distributed only in a certain directional range. By considering this observation, we adopt density-independent K-Nearest Neighbors (KNN) method to determine neighboring points and design a centrality metric LoDD using the eigenvalues of the covariance matrix to depict the distribution uniformity of KNN. We also develop a grid-structure assumption of data distribution to determine the parameters adaptively. The effectiveness of LoDD is demonstrated on synthetic datasets, real-world benchmarks, and application of training set split for deep learning model and hole detection on point cloud data. The datasets and toolkit are available at: https://***/ZPGuiGroupWhu/lodd. Copyright © 2023, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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Issues,Progress,and Recommendations in the Construction of Ecological Barrier on the Mongolian Plateau from the Perspective of Big Data

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Journal of Resources and Ecology 2024年第5期15卷 1113-1124页

作者： WANG Juanle LI Kai XU Shuxing SHAO Yating WANG Meng LI Menghan ZHANG Yu LIU Yaping LI Fengjiao Ochir ALTANSUKH Chuluun TOGTOKH State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChineseAcademy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China College of Geoscience and Surveying Engineering China University of Mining&Technology(Beijing)Beijing 100083China College of Geomatics Xi’an University of Science and TechnologyXi’an 710054China Environmental Engineering Laboratory Department of Environment and Forest EngineeringNational University of MongoliaUlaanbaatar 14201Mongolia Institute for Sustainable Development National University of MongoliaUlaanbaatar 14201Mongolia

The Mongolian Plateau(MP),situated in the transitional zone between the Siberian taiga and the arid grasslands of Central Asia,plays a significant role as an Ecological Barrier(EB)with crucial implications for ecological and resource security in Northeast *** is a vast concept and a complex issue related to many aspects such as water,land,air,vegetation,animals,and people,et *** is very difficult to understand the whole of EB without a comprehensive perspective,that traditional diverse studies cannot *** data and artificial intelligence(AI)have enabled a shift in the research *** with these requirements,this study identified issues in the construction of EB on MP from a big data *** includes the issues,progress,and future recommendations for EB construction-related studies using big data and *** issues cover the status of theoretical studies,technical bottlenecks,and insufficient synergistic analyses related to EB *** progress introduces advances in scientific research driven by big data in three key areas of MP:natural resources,the ecological environment,and sustainable *** the future development of EB construction on MP,it is recommended to utilize big data and intelligent computing technologies,integrate extensive regional data resources,develop precise algorithms and automated tools,and construct a big data collaborative innovation plat*** study aims to call for more attention to big data and AI applications in EB studies,thereby supporting the achievement of sustainable development goals in the MP and enhancing the research paradigm transforming in the fields of resources and the environment.

关键词： Mongolian Plateau resources and ecology big data artificial intelligence research paradigm

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Classification of Cognitive Ability of Healthy Elderly Individuals Using Resting-State Functional Connectivity Magnetic Resonance Imaging and An Extreme Learning Machine

Research Square

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Research Square 2021年

作者： Yang, Zekun Ge, Manling Abdelkader, Nasreddine Belkacem Fu, Xiaoxuan Zhang, Qirui Chen, Shenghua Xie, Chong Song, Zibo Chen, Chao State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Hebei Province Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology Tianjin300130 China Department of Computer and Network Engineering College of Information Technology United Arab Emirates University Al Ain15551 United Arab Emirates Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Harvard Medical School CharlestownMA02129 United States Department of Medical Imaging Jinling Hospital Nanjing University School of Medicine General Hospital of Eastern Theater Nanjing210002 China Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin300003 China

Purpose Quantitative determination of the correlation between cognitive ability and functional biomarkers in the elderly brain is essential. To identify biomarkers associated with cognitive performance in the elderly, this study combined an index model specific for resting-state functional connectivity (FC) magnetic resonance imaging (fcMRI) with a supervised machine learning method. Methods Performance scores on conventional cognitive test batteries and MRI data were obtained for 98 healthy elderly individuals and 90 healthy youth from two public databases. Based on the test scores, the elderly cohort was categorized into two groups: excellent and poor. An fcMRI index model was constructed for each elderly individual to determine the relative differences in FC among brain regions compared with that in the youth cohort. Brain areas sensitive to test scores could then be identified using the fcMRI indexes. To confirm the effectiveness of constructed model, the fcMRI indexes of these brain areas were used as feature matrix inputs for training an extreme learning machine. Classification accuracy was then tested in separate groups and confirmed by N-fold cross-validation. Results This learning study could effectively classify the cognitive status of healthy elderly individuals according to frontal lobe, temporal lobe, and parietal lobe FC values with a mean accuracy of 83.5%, which is substantially higher than that achieved using conventional correlation analysis. Conclusion This fcMRI classification study may facilitate early detection of age-related cognitive decline as well as help reveal the underlying pathological mechanisms. © 2021, CC BY.

关键词： Magnetic resonance imaging

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Unveiling the secrets of the mid-infrared Moon

arXiv

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arXiv 2020年

作者： Wu, Yunzhao Jin, Qi Li, Cui Xu, Tianyi Qi, Wenwen Tan, Wei Li, Xiaoman Shi, Zhicheng He, Hongyan Dai, Shuwu Li, Guo Liu, Fengjing Wang, Jingqiao Wang, Xiaoyan Lu, Yu Cai, Wei Wang, Qi Meng, Lingjie Key Laboratory of Planetary Sciences Purple Mountain Observatory Chinese Academy of Sciences Nanjing210034 China Space Science Institute Macau University of Science and Technology Macau China Cas Center for Excellence in Comparative Planetology China Beijing Institute of Space Mechanics and Electricity Beijing China Beijing Institute of Spacecraft System Engineering Beijing China China Centre for Resources Satellite Data and Application Beijing China Jiangsu Ctr. for Collab. Innovation in Geographical Information Resource Development and Application Nanjing210023 China Earth Observation System and Data Center China National Space Administration Beijing China

The Moon's optical characteristics in visible and long-wavelength infrared (LWIR) have long been observed with our eyes or with instruments. What the mid-infrared (MIR) Moon looks like is still a mystery. For the first time we present detailed appearance of the MIR Moon observed by a high-resolution geostationary satellite and reveal the essence behind its appearance. The appearance of the MIR Moon is opposite to its normal visible appearance. In addition the MIR Moon shows limb darkening. Both the absolute and the relative brightness distribution of the MIR lunar disk changes with the solar incidence angle. The signatures of the MIR Moon are controlled by both the reflection and emission of the lunar surface. We also show first-ever brightness temperature maps of the lunar disk without needing a mosaic, which better show the temperature variation across the lunar disk. They reveal that the relationship between brightness temperature and solar incidence angle i is cos1/bi, and the power parameter is smaller than the Lambertian temperature model of cos1/4i observed for lunar orbit-based measurements. The slower decrease of the brightness temperature when moving away from the sub-solar point than the Lambertian model is due to topographic effects. The brightness temperature is dominated by albedo and the solar incidence angle and influenced by the topography. Our results indicate that the Moon in the MIR exhibits many interesting phenomena which were previously unknown, and contains abundant information about lunar reflection and thermal emission for future study. Copyright © 2020, The Authors. All rights reserved.

关键词： Infrared devices

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Nonlinear Association between Urban Heat Vulnerability and Morbidity Risk by Combining Multisource Data

SSRN

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SSRN 2023年

作者： Yang, Jiaming Tong, Zhaomin Xu, Jiwei An, Rui Liu, Yanfang Liu, Yaolin School of Resource and Environmental Sciences Wuhan University 129 Luoyu Road Wuhan430079 China Key Laboratory of Geographic Information System Ministry of Education Wuhan University 129 Luoyu Road Wuhan430079 China Collaborative Innovation Center of Geospatial Technology Wuhan University 129 Luoyu Road Wuhan430079 China Duke Kunshan University No. 8 Duke Avenue Jiangsu Province Kunshan215316 China

Urban heat vulnerability (UHV) caused by anthropogenic activities and climate changes has caused heat health issues in metropolitan areas worldwide. The nonlinear relationship and interactions between main HVIs have not yet been fully explored. Based on vulnerability assessment framework, this paper selected fifteen indicators from built environment, sociodemographic and socioeconomic attributes, resource accessibility and residential thermal comfort, obtained from multisource data. The performances of the ordinary least squares (OLS) and gradient boosting decision trees (GBDT) were compared. Results indicate GBDT outperforms the OLS model and captures the nonlinear relationship more efficiently. When analyzing HVIs’ contributions and interactions with the GBDT model and the SHAP algorithm, nighttime light (NTL), building year (BY), PM2.5, floor area ratio (FAR), number of elderly (≥65 years) (NE) and urban surface roughness (USR) are six major drivers of morbidity of heat-related diseases and they have an evident nonlinear relationship with the threshold effect and spatially heterogeneous contributions for the morbidity variation of heat-related diseases. Our study provides insights into machine learning model for the effect of heat vulnerability on city residential health and mitigation and adaptation strategies for governments and urban planners to develop heat resilience cities. © 2023, The Authors. All rights reserved.

关键词： Decision trees

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Development of a regional carbon assimilation system and its application for estimating fossil fuel carbon emissions in the Yangtze River Delta, China

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Science of the Total Environment 2024年 957卷 177720页

作者： Zhang, Zhengqi Feng, Shuzhuang Chen, Yan Liu, Qiang Ju, Weimin Xiao, Wei Huang, Cheng Wang, Yanyu Wang, Hengmao Jia, Mengwei Wang, Xingyu Jiang, Fei Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System Science Nanjing University Nanjing210023 China Jiangsu Provincial Climate Center Jiangsu Meteorological Bureau Nanjing210018 China Frontiers Science Center for Critical Earth Material Cycling Nanjing University Nanjing210023 China Nanjing CLIMBLUE Technology co. LTD Nanjing211135 China Nanjing University of Information Science and Technology Nanjing210044 China Shanghai Environmental Monitoring Centre Shanghai200235 China State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex Shanghai Academy of Environmental Sciences Shanghai200233 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing210023 China Jintan National Climatic Observatory Jiangsu Meteorological Bureau Jintan213299 China

Urban areas are the largest contributors to global fossil fuel carbon emissions, and controlling urban carbon emissions is critical to addressing climate change and reducing greenhouse gas emissions. However, estimates of urban emissions remain large uncertainties, making it difficult to accurately understand changes in urban carbon emissions and to assess the effectiveness of emission controls. Atmospheric CO2 observations, through data assimilation, can objectively invert changes in urban carbon emissions. In this study, inheriting the inversion method of a global carbon assimilation system of GCASv2, we constructed a regional carbon assimilation system based on a regional 3-D atmospheric chemical transport model WRF-CMAQ, named RegGCAS. We tested the performance of the established assimilation system for winter carbon emissions in the Yangtze River Delta (YRD) by performing a 9 km × 9 km resolution inversion in December 2020, using observations from 6 ground stations and two emission inventories as a priori, respectively. The results show that after assimilating the observations in the YRD region, especially in Suzhou and Hangzhou where there are more observing sites, the two significantly different a priori emissions are effectively converged, with the relative difference being reduced from −45 % and − 36 % of the a priori emissions to −10 % and − 15 % of the a posteriori emissions. Furthermore, the daily changes of the inverted emissions clearly show that weekend emissions are lower than weekday emissions, i.e. the inversion can reveal the weekend effect of emissions changes. This suggests that our system is well established and can be used for estimating fossil fuel carbon emissions during winter. Meanwhile, these results also imply that with our system, when a city has three or more stations, its total emissions can be constrained reliably. © 2024 Elsevier B.V.

关键词： Low emission

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MSight: An Edge-Cloud Infrastructure-based Perception system for Connected Automated Vehicles

arXiv

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arXiv 2023年

作者： Zhang, Rusheng Meng, Depu Shen, Shengyin Zou, Zhengxia Li, Houqiang Liu, Henry X. The Department of Civil and Environmental Engineering University of Michigan Ann ArborMI48109 United States The University of Michigan Transportation Research Institude 2901 Baxer Rd Ann ArborMI48109 United States The Department of Guidance Navigation and Control School of Astronautics Beihang University Beijing100191 China The CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei China Mcity University of Michigan Ann ArborMI48109 United States

As vehicular communication and networking technologies continue to advance, infrastructure-based roadside perception emerges as a pivotal tool for connected automated vehicle (CAV) applications. Due to their elevated positioning, roadside sensors, including cameras and lidars, often enjoy unobstructed views with diminished object occlusion. This provides them a distinct advantage over onboard perception, enabling more robust and accurate detection of road objects. This paper presents MSight, a cutting-edge roadside perception system specifically designed for CAVs. MSight offers real-time vehicle detection, localization, tracking, and short-term trajectory prediction. Evaluations underscore the system’s capability to uphold lane-level accuracy with minimal latency, revealing a range of potential applications to enhance CAV safety and efficiency. Presently, MSight operates 24/7 at a two-lane roundabout in the City of Ann Arbor, Michigan. Copyright © 2023, The Authors. All rights reserved.

关键词： Roadsides

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Video-based point cloud compression artifact removal

arXiv

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arXiv 2021年

作者： Akhtar, Anique Gao, Wen Li, Li Li, Zhu Jia, Wei Liu, Shan Department of Computer Science and Electrical Engineering University of Missouri-Kansas City Kansas CityMO64110 United States Tencent America 661 Bryant St. Palo AltoCA94301 United States Department of Computer Science and Electrical Engineering University of Missouri-Kansas City Kansas CityMO64110 United States CAS Key Laboratory of Technology in Geo-Spatial Information Processing and Application System University of Science and Technology of China Hefei230027 China

—Photo-realistic point cloud capture and transmission are the fundamental enablers for immersive visual communication. The coding process of dynamic point clouds, especially video-based point cloud compression (V-PCC) developed by the MPEG standardization group, is now delivering state-of-the-art performance in compression efficiency. V-PCC is based on the projection of the point cloud patches to 2D planes and encoding the sequence as 2D texture and geometry patch sequences. However, the resulting quantization errors from coding can introduce compression artifacts, which can be very unpleasant for the quality of experience (QoE). In this work, we developed a novel out-of-the-loop point cloud geometry artifact removal solution that can significantly improve reconstruction quality without additional bandwidth cost. Our novel framework consists of a point cloud sampling scheme, an artifact removal network, and an aggregation scheme. The point cloud sampling scheme employs a cube-based neighborhood patch extraction to divide the point cloud into patches. The geometry artifact removal network then processes these patches to obtain artifact-removed patches. The artifact-removed patches are then merged together using an aggregation scheme to obtain the final artifact-removed point cloud. We employ 3D deep convolutional feature learning for geometry artifact removal that jointly recovers both the quantization direction and the quantization noise level by exploiting projection and quantization prior. The simulation results demonstrate that the proposed method is highly effective and can considerably improve the quality of the reconstructed point cloud. Copyright © 2021, The Authors. All rights reserved.

关键词： Geometry

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Spatial Distribution of Rare Earth Elements and Their Impact Factors in an Area with a High Abundance of Regolith-Hosted Deposits

SSRN

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SSRN 2023年

作者： Lin, Zhuoling Zhang, Yaduo Liang, Xiaoliang Huang, Guangqing Fan, Fenglei Yin, Xiaoling Chen, Zhihao Guangzhou Institute of Geochemistry Chinese Academy of Sciences Guangzhou510640 China Guangdong Public Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangdong Academy of Sciences Guangzhou510070 China School of Geography South China Normal University Guangzhou510631 China University of Chinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Laboratory of Mineral Physics and Material Research & Development Guangzhou510640 China College of Natural Resources and Environment South China Agricultural University Guangzhou510642 China

Rare earth elements (REEs) are critical metals for manufacturing numerous high-tech products, but at high concentrations, pose potential hazards owing to their toxicity to animals and human health. Despite the widespread occurrence of regolith-hosted REEs across South China, their spatial distribution characteristics in soils and attendant influencing factors remain largely unknown. This knowledge gap impedes the exploration of regolith-hosted REE deposits and the assessment of the environmental risks associated with REEs. To address this issue, 180 soil samples were collected from Meizhou City, Guangdong Province, a region known for its high abundance of regolith-hosted REEs. Subsequently, the correlations between REE enrichment/fractionation and various factors, i.e., topography, climate conditions, land use, and landform were analysed using the geo-detector method. The results revealed a highly uneven spatial distribution of REEs and their fractionation features with some regions displaying distinct spatial patterns. Elevation was the dominant factor influencing this distribution, and showed strong correlations with the concentrations of REEs, light REEs (LREEs) and heavy REEs (HREEs);the LREE/HREE ratio;and the positive Ce anomaly (δCe). The negative Eu anomaly (δEu) showed a good correlation with rock type. The enrichment and fractionation of REEs indicated a coupling among the abovementioned factors. The crucial scopes of the predominant factors were identified using a risk detector. For REE enrichment, areas with elevations of 137–148 m, precipitation levels of 1553–1574 mm, annual average land surface temperatures of 30.4–30.5 °C, leaf area index values of 22–29 and relief degrees of land surface of 21.4–29.9 m showed the highest average abundance within each type (scope) of the predominant factors. These findings highlight the key factors affecting REE distribution, thereby aiding the efficient utilization of regolith-hosted REE resources and the assessment

关键词： Soils

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The resolution ability and velocity determination the resolution ability and velocity determination in translational variant bistatic SAR

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Yuhang Xuebao/Journal of Astronautics 2009年第4期30卷 1609-1614页

作者： Qiu, Xiao-Lan Hu, Dong-Hui Ding, Chi-Biao Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Institute of Electronics Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100190 China

Ground resolution is very important to SAR images. This paper studied the resolution ability of translational variant bistatic SAR for the designing of proper bistatic configurations. It firstly analyzed the range ground resolution and its relationship with locations using the gradient method. Then it deduced out the azimuth resolution formula and described the calculating method. Finally, simulation results are given and some hints for velocity determination in 'space-air' configuration is also addressed.

关键词： Synthetic aperture radar

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