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Carbon dioxide(CO_(2))emissions from the service industry,traffic,and secondary industry as revealed by the remotely sensed nighttime light data

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International Journal of Digital Earth 2021年第11期14卷 1514-1527页

作者： Kaifang Shi Jingwei Shen Yizhen Wu Shirao Liu Linyi Li School of Geographical Sciences Southwest UniversityChongqingPeople’s Republic of China Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station Southwest UniversityChongqingPeople’s Republic of China Chongqing Engineering Research Center for Remote Sensing Big Data Application School of Geographical SciencesSouthwest UniversityChongqingPeople’s Republic of China School of Remote Sensing and Information Engineering Wuhan UniversityWuhanPeople’s Republic of China

Exploring carbon dioxide(CO2)emissions from human activities is essential for urban energy conservation and resource *** sensed nighttime lights from the Suomi NPP-VIIRS provide spatial consistency in and a low-cost way of revealing CO2 *** many researches have documented the feasibility of the Suomi NPP-VIIRS data for assessing CO2 emissions,few have systematically revealed the ability of nighttime lights for evaluating CO2 emissions from different industries,such as service industry CO2 emissions(SC),traffic CO2 emissions(TC),and secondary industry CO2 emissions(IC).Here,China was selected as the experimental subject,and we comprehensively explored the relationships between the nighttime lights and SC,TC,and IC,and investigated the factors mediating these *** found that without considering other factors,the nighttime lights only revealed up to 51.2%of TC,followed by 41.7%of IC and 22.7%of *** controlling for city characteristic variables,the models showed that there were positive correlations between the Suomi NPP-VIIRS data and SC,IC,and TC,and that nighttime lights have an Inverted-U relationship with *** Suomi NPP-VIIRS data are more suitable for revealing SC,TC,and IC in medium-sized and large-sized cities than in small-sized cities and megacities.

关键词： Nighttime light data Suomi NPP-VIIRS CO2 emissions transmission mechanism China

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Delayed Antarctic melt season reduces albedo feedback

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National Science Review 2023年第9期10卷 236-246页

作者： Lei Liang Huadong Guo Shuang Liang Xichen Li John C.Moore Xinwu Li Xiao Cheng Wenjin Wu Yan Liu Annette Rinke Gensuo Jia Feifei Pan Chen Gong Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences International Research Center of Big Data for Sustainable Development Goals Institute of Atmospheric Physics Chinese Academy of Sciences College of Global Change and Earth System Science Beijing Normal University Arctic Centre University of Lapland CAS Center for Excellence in Tibetan Plateau Earth Sciences School of Geospatial Engineering and Science Sun Yat-sen University Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research Department of Geography University of North Texas

Antarctica' s response to climate change varies greatly both spatially and *** melting impacts mass balance and also lowers surface *** use a 43-year record(from 1978 to 2020) of Antarctic snow melt seasons from space-borne microwave radiometers with a machine-learning algorithm to show that both the onset and the end of the melt season are being ***-causality analysis shows that melt end is delayed due to increased heat flux from the ocean to the atmosphere at minimum sea-ice extent from warming *** onset is Granger-caused primarily by the turbulent heat flux from ocean to atmosphere that is in turn driven by sea-ice *** snowmelt season leads to a net decrease in the absorption of solar irradiance,as a delayed summer means that higher albedo occurs after the period of maximum solar radiation,which changes Antarctica's radiation balance more than sea-ice cover.

关键词： Antarctic ice sheet snowmelt season delay sea ice solar irradiance

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research on Collaborative Service Problem Diagnosis of Urban Multi-mode Passenger Transport System Based on Trip Chain 6th

Research on Collaborative Service Problem Diagnosis of Urban...

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6th International Conference on Intelligent Transportation Engineering, ICITE 2021

作者： Zhao, Lin Liu, Dongmei Zhang, Jinquan Transportation Industry Research and Development Center of Big Data Processing and Application Technologies for Comprehensive Transport Haidian District 8 Xitucheng Road Beijing China Research Institute of Highway MOT 8 Xitucheng Road Haidian District Beijing China

ISBN: (纸本)9789811922589

In order to solve the collaborative service problem existing in urban multi-modes passenger transport system, an evaluation method on level of collaborative service of urban multi-mode integrated passenger transport system based on mass individual trip chains with each evaluation level was proposed. 14 index which could comprehensively reflect the efficiency and convenience during the mass individual trips were selected from three perspectives of hot spots with collaborative service problems, connecting coordination of routes, and supply and demand balance of passenger net. The evaluation index system of level of collaborative service of urban multi-mode integrated passenger transport system was reconstructed aiming at mining problems. Based on nearly 16 million valid individual trip chain on Beijing recognized from the China Unicom mobile phone signaling data, the service hot spots with the problems of shuttle, transfer, and difficulty for taking taxi were recognized, the stability and the influence on the residents travel route choice were mined, and the status of supply and demand balance which is equal or more of the comprehensive passenger transport net in Beijing was preliminary judged. It provides theoretical basis and technical support for the improvement of the integrated coordinated operation efficiency and level of service of the urban passenger transport system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Efficiency

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A dataset of lake level changes in China between 2002 and 2023 using multi-altimeter data

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big Earth data 2024年第1期8卷 166-188页

作者： Shanmu Ma Jingjuan Liao Ruofan Jing Jiaming Chen Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina International Research Center of Big Data for Sustainable Development Goals BeijingChina University of Chinese Academy of Sciences BeijingChina

Lake water levels are an important indicator of water balance and water cycles,and are essential for climate and environmental change studies and water resource ***,lake level measurements are scarce or inconsistent throughout the country,and traditional gauge measurements of many lakes are not feasible,so satellite altimetry is a vital alternative to gauge lake ***,the accuracy and sam-pling frequency of lake level time series are usually low because of time and space coverage limitations;therefore,it is necessary to utilize multialtimeter data to monitor lake levels and obtain lake level changes over long time *** this study,we extracted the water level changes in 988 lakes(>10 km^(2))in China between 2002 and 2023 based on ICESat/-2,Cryosat-2,Jason-1/2/3,and Sentinel-3A/3B altimetry data using waveform retracking,lake level extraction,lake level time series construction,the fusion of multi-altimeter lake level time series,and outlier removal.A total of 55%of the lakes in this dataset have been monitored for more than 10 years,and 34%have more than 12 times the annual average water level *** the same time,in situ data from 21 lakes were used for validation,and the average root mean square error(RMSE)for each of the datasets of ICESat/-2,Cryosat-2,Jason-1/2/3,and Sentinel-3A/3B versus the in situ lake levels are 0.223 m,0.163 m,0.207 m,0.596 m,0.295 m,0.275 m,0.243 m,and 0.317 m,respectively,and the mean RMSE of the fused lake levels reaches 0.332 *** the monitoring period,the water levels in Chinese lakes generally *** overall annual average rate of change at the 20 and 10-year scales was 0.123 m/a and 0.151 m/a,respectively,among which the overall water levels in large lakes increased *** lakes with a faster rate of decline in the water level were primarily *** water storage in each lake region in China shows an upward trend,with the most significant increase in the Tibetan Plateau reg

关键词： Lake level multi-altimeter China spatiotemporal variation

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Advancing urban connectivity measurements for SDG 11.a with SDGSAT-1 nighttime light data in urban agglomerations

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International Journal of Applied Earth Observation and Geoinformation 2025年 140卷

作者： Zhuoran Lv Huadong Guo Lu Zhang Dong Liang Lingxuan Gong Yiming Liu Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing 100049 China Agro-Environmental Protection Institute Ministry of Agriculture and Rural Affairs Tianjin 300191 China School of Earth and Space Sciences Peking University Beijing 100871 China

Urban agglomerations, formed by multiple cities connected through transportation and information networks, play a pivotal role in the sustainable development of human settlements and communities. This study introduces a data-driven approach to analyze urban connectivity using high-precision 10-meter panchromatic nighttime light (NTL) data from SDGSAT-1, integrated with OpenStreetMap (OSM) road data, to support SDG 11.a for sustainable cities and communities. We develop image enhancement and network extraction methods to accurately detect urban road networks and assess connectivity. By incorporating geographical adjustment factors and integrating urban geographic information, we construct a series of indicators to evaluate the resource flow capacities of urban agglomerations using social network models. The study focuses on three major urban agglomerations: the Chengdu-Chongqing Urban Agglomeration (CCUA), the Shandong Peninsula Urban Agglomeration (SPUA), and Liaoning Province (Liaoning). Through these case studies, we extract urban connectivity networks and analyze their resource flow capabilities. This approach provides valuable insights into the intensity and efficiency of urban resource circulation, offering data-driven support for fostering sustainable urban development in alignment with SDG 11.a.

关键词： Urban agglomerations Sustainable development goals Connectivity SDGSAT-1

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Benchmarking ULS-TLS Point Cloud Registration Algorithms in Forest Environments

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IEEE Transactions on Geoscience and Remote Sensing 2025年

作者： Liu, Wangjun Nie, Sheng Xia, Shaobo Wang, Cheng Wang, Jinliang Xi, Xiaohuan Cheng, Feng Chinese Academy of Sciences Key Laboratory of Digital Earth Science Aerospace Information Research Institute Beijing 100094 China International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China University of Chinese Academy of Sciences College of Resources and Environment Beijing 100049 China Changsha University of Science & Technology School of Traffic & Transportation Engineering Changsha 410114 China Yunnan Normal University Faculty of Geography Yunnan Kunming 650500 China

Integrating Unmanned aerial vehicle Laser Scanning (ULS) and Terrestrial Laser Scanning (TLS) data in complex forest environments remains a significant challenge. Despite the availability of numerous registration algorithms, robust comparative studies are limited by the lack of reliable multi-platform benchmark datasets. In this study, we introduce the first multiplatform benchmark dataset for ULS-TLS point cloud registration in forests, encompassing 17 plots from seven diverse regions with about 1.56 billion points. The dataset is categorized into three difficulty levels based on overlap ratio and rigid *** evaluated the performance of five registration algorithms against this benchmark. Chen2022 achieved the highest accuracy with a 100% success rate across all difficulty levels. While Wu2024 demonstrated robust performance in lower difficulties but faced challenges in more complex scenarios. We also found that terrain variations and rigid overlap significantly impacted registration accuracy, particularly for algorithms reliant on individual tree positions such as Hyypp¨a2021 and Feng2024. These findings underscore the need for improved data collection strategy, ground filtering techniques, and feature matching algorithms to enhance performance in challenging environments. We present the first openly accessible multi-platform benchmark dataset for forested regions and anticipate that future research will expand this work to additional areas. The dataset can be downloaded from: datasetDownloadLink. © 1980-2012 IEEE.

关键词： algorithm inter-comparison benchmark data forest ULS-TLS registration

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A data Privacy and Authentication Scheme Based on Internet of Vehicles 7

A Data Privacy and Authentication Scheme Based on Internet o...

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7th IEEE International Conference on big data Security on Cloud, 7th IEEE International Conference on High Performance and Smart Computing, and 6th IEEE International Conference on Intelligent data and Security, bigdataSecurity/HPSC/IDS 2021

作者： Wu, Qiaohong Xiao, Weidong Hu, Xiaoke Zhu, Peiyuan Chen, Xihua Big Data Development and Research Center Guangzhou College of Technology and Business Guangzhou China Xiamen University of Technology School of Software Engineering Xiamen China Shaoyang University School of Food Chemical Engineering Shaoyang China

ISBN: (纸本)9781665439275

Vehicular ad hoc networks (VANETs) enables efficient communication between vehicles or between vehicles and infrastructure, which is a hot research topic in intelligent transportation systems. Due to its open access and dynamic network structure, VANETs are vulnerable to security and privacy issues. data verification and reception scheme based on the Internet of vehicles has proposed in this paper. The computing power and storage capacity of ordinary RSU devices fail to handle a large amount of data received by RSU in a short time, which will lead to a large amount of system time. The data verification receiving scheme proposed in this paper first aggregates the data received by RSU equipment, which will greatly improve the processing efficiency of RSU equipment. This paper analyzes the authentication protocol to achieve security and privacy protections on the Internet of vehicles and puts forward the existing problems and unresolved challenges, which provides a direction for the design of authentication protocol in the future. © 2021 IEEE.

关键词： Authentication

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bigRU-DA: Based on Improved bigRU Multi-Target data Association Method

BiGRU-DA: Based on Improved BiGRU Multi-Target Data Associat...

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International Conference on Computers, Communications, and Systems (ICCCS)

作者： Guangsheng Wu Licai Wang Xun Hu Qibin Luo Dongliang Guo Big data research and development center North China Institute of Computing Technology Beijing China

Trajectory data association algorithm is an important part of multi-target tracking method. Traditional association methods require priori information such as target motion model and clutter density to conduct association, and the association accuracy is low in complex scenes such as trajectory accompaniments and crosses. Based on the sensitivity of bigRU to time series, this paper proposes an improved trajectory data association algorithm of bigRU network: bigRU-DA. In this paper, an output gate structure is added on the basis of the existing bigRU model, which can optimize the output results of the model and extract the influence of trajectory timing sequence on trajectory data association. In order to verify the data association effect of bigRU-DA method, the experiment conducted comparison experiments in four datasets under the condition of clutter interference. Experimental results show that bigRU-DA is superior to other methods in all datasets.

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RIF-Proto: A Few-Shot Relation Extraction for Prototype Networks Based on Relational Information Features

RIF-Proto: A Few-Shot Relation Extraction for Prototype Netw...

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Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Shuai Zhang Licai Wang Yangchen Huang Big data research and development center North China Institute of Computing Technology Beijing China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

Relation extraction stands as a core task within the realm of information extraction, focusing on identifying the target relations between entities in text. While traditional relation extraction has been extensively researched, certain relations lack sufficient labeled data, rendering traditional models ineffective in practical research. Hence, the research focus in this field has shifted towards few-shot learning methods that leverage limited labeled data for training. Significant progress has been made in few-shot relation extraction, with prototype networks garnering attention from scholars for their outstanding performance in few-shot tasks. Prototype networks utilize the clustering idea to achieve relationship classification simply and efficiently, and their training process is mainly divided into three parts: generation of relationship prototypes, relationship classification, and loss calculation. The majority of current research is centered around leveraging external information to enhance the generation of prototypes and loss functions, but due to the difficulty of obtaining external data and the high complexity of data processing, it greatly increases the time cost and the difficulty of implementation. Given the aforementioned challenges, this paper introduces a method for prototype refinement leveraging relationship similarity among existing data. This approach aims to effectively address the issue of significant deviations in relationship prototypes. Initially, extract relationship vectors from the instances in both the support set and query set, followed by computing the relationship similarity between samples based on these vectors, and finally, this paper constructs a prototype correction module, which utilizes the relationship similarity to assign weights to the samples in the support set, to achieve the purpose of prototype correction. In the experiments against the standard dataset FewRel1.0., we observe that the method substantially improves the ex

关键词： Training Seminars Semantics Prototypes Feature extraction Rendering (computer graphics) Vectors

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Legal Event Detection Model Based on ERNIE 3.0-CRF and Ensemble Learning

Legal Event Detection Model Based on ERNIE 3.0-CRF and Ensem...

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Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Siyu Wang Licai Wang Ke Zhang Big data research and development center North China Institute of Computing Technology Beijing China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

Recognizing events is a prerequisite for making judgments, so discovering events in legal documents is important for the analysis of legal case. Legal Event Detection aims to extract legal event trigger words from legal documents and categorize events and is the basis of many judicial AI applications. Oriented to the needs of understanding and analyzing legal events in the judicial trial process, and in response to the low accuracy of event detection caused by the many types of events and little sample data in the legal domain, this paper constructs a pre-training model oriented to event detection in the legal domain, which makes full use of ERNIE 3.0's powerful semantic representation learning capability and CRF's effective modeling capability for sequence annotation tasks. In addition, we further enhance the effectiveness of the model through data augmentation and ensemble learning. The experimental results show that the method works better compared to the baseline model and improves the prediction accuracy of legal event detection.

关键词： Seminars Analytical models Accuracy Law Event detection Predictive models data models

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