2. Shifen Cheng, Feng Lu*, A Two-step method for missing spatio-temporal data reconstruction, ISPRS International Journal of Geo-Information, 2017, 6, 187; doi:10.3390/ijgi6070187
3. 刘康,仇培元,刘希亮,张恒才,王少华,陆锋*,利用词向量模型分析城市道路交通空间相关性,测绘学报,2017, 46(12):2032-2040
4. Feng Lu, Kang Liu, Yingying Duan, Shifen Cheng, Fei Du, Modelling the heterogeneous traffic correlation for city road networks with community detection, Physica A, 2018, doi.org/10.1016/j.physa.2018.02.062
5. Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu, Short-term traffic forecasting: an adaptive ST-KNN model that considers spatial heterogeneity, Computers, Environment and Urban Systems, 2018, 71:186-198
6. Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu, A spatiotemporal multi-view-based learning method for short-term traffic forecasting, ISPRS International Journal of Geo-Information, 2018, 7(6): 218; doi:10.3390/ijgi7060218
7. Kang Liu, Song Gao, Feng Lu*, Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling, Computers, Environment and Urban Systems, 2019, 74: 50-61
8. Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu, Multi-task and multi-view learning based on particle swarm optimization for short-term traffic forecasting, Knowledge-Based Systems, 2019, https://doi.org/10.1016/j.knosys.2019.05.023.
9. Beibei Zhang, Shifen Cheng*, Feng Lu, and Sheng Wu, Spatial characteristics and factor analysis of pollution emission from heavy-duty diesel trucks in the Beijing-Tianjin-Hebei region, China, International Journal of Environmental Research and Public Health, 2019, 16, 4973; DOI:10.3390/ijerph16244973
10.Shifen Cheng, Beibei Zhang, Peng Peng, Zhenzhen Yang, Feng Lu*, Spatiotemporal evolution pattern detection for heavy-duty diesel truck emissions using trajectory mining: a case study of Tianjin, China. Journal of Cleaner Production, 2020, 244:118654. DOI:10.1016/j.jclepro.2019.118654
11.Shifen Cheng, Feng Lu*, Peng Peng, A high-resolution emissions inventory and its spatiotemporal pattern variations for heavy-duty diesel trucks in Beijing, China, Journal of Cleaner Production, 2020, 250:119445.DOI: 10.1016/j.jclepro.2019.119445
12.Kang Liu, Peiyuan Qiu, Song Gao, Feng Lu, Jincheng Jiang, Ling Yin*, Investigating urban metro stations as cognitive places in cities using points of interest. Cities, 2020, 97:102561. DOI: 10.1016/j.cities.2019.102561
13.Kang Liu, Ling Yin*, Feng Lu, Naixia Mou, Visualizing and exploring POI configurations of urban regions on POI-type semantic space. Cities, 2020, 99:102610. DOI: 10.1016/j.cities.2020.102610
14.Shifen Cheng, Peng Peng, Feng Lu*, A lightweight ensemble spatiotemporal interpolation model for geospatial data. International Journal of Geographical Information Science, 2020, 34(9): 1849-1872. DOI: 10.1080/13658816.2020.1725016
15.Shifen Cheng, Feng Lu*, Peng Peng, Short-term traffic forecasting by mining the non-stationarity of spatiotemporal pattern, IEEE Transactions on Intelligent Transportation Systems, 2020, 10.1109/TITS.2020.2991781
16. 程诗奋、彭澎、张恒才、陆锋*,异质稀疏分布时空数据重构与预测方法探讨,武汉大学学报(信息科学版),2020,45(12):1919-1929
移动对象数据库与位置服务:
1. Hengcai Zhang, Feng Lu*, Jianqiu Xu, Modeling and querying moving objects with social relationships, ISPRS International Journal of Geo-Information, 2016, 5, 121, doi:10.3390/ijgi5070121
2. Hengcai Zhang, Feng Lu*, Jie Chen, A line graph-based continuous range query method for moving objects in networks, ISPRS International Journal of Geo-Information, 2016, 5, 246; doi:10.3390/ijgi5120246
3. Hengcai Zhang, Feng Lu*, GSMNet: A hierarchical graph model for moving objects in networks, ISPRS International Journal of Geo-Information, 2017, 6, 71; doi:10.3390/ijgi6030071
4. Mingxiao Li, Feng Lu, Hengcai Zhang*, Jie Chen, Predicting future locations of moving objects with deep fuzzy-LSTM networks, Transportmetrica A: Transport Science, 2018, DOI: 10.1080/23249935.2018.1552334
5. Mingxiao Li, Song Gao, Feng Lu, Hengcai Zhang*, Reconstruction of human movement trajectories from large-scale low-frequency mobile phone data. Computers, Environment and Urban Systems, 2019, 77, https://doi.org/10.1016/j.compenvurbsys.2019.101346
6. Mingxiao Li, Song Gao, Feng Lu, Huan Tong, Hengcai Zhang*, Dynamic estimation of individual exposure levels to air pollution using trajectories reconstructed from mobile phone data. International Journal of Environmental Research and Public Health, 2019, 16, 4522; DOI: 10.3390/ijerph16224522
7. Peixiao Wang, Sheng Wu, Hengcai Zhang*, Feng Lu. Indoor location prediction method for shopping malls based on location sequence similarity. ISPRS International Journal of Geo-Information, 2019, 8, 517; DOI:10.3390/ijgi8110517
8. Peixiao Wang, Hengcai Zhang*, Hongen Wang, Feng Lu, Sheng Wu, A hybrid Markov and LSTM model for indoor location prediction, IEEE Access, 2019, 7(1):185928-185940. DOI:10.1109/ACCESS.2019.2961559
9. 王培晓、吴升、张恒才*、陆锋、王宏恩,一种室内人群时空聚集区域识别方法,武汉大学学报(信息科学版),2020,DOI: 10.13203/j.whugis20190228
10.Yang Xu, Xinyu Li, Shih-Lung Shaw, Feng Lu, Ling Yin, Biyu Chen. Effects of data preprocessing methods on addressing location uncertainty in mobile signaling data. Annals of the American Association of Geographers, 2021, 111(2):515-539. DOI: 10.1080/24694452.2020.1773232
11.Mingxiao Li, Song Gao*, Feng Lu, Kang Liu, Hengcai Zhang, Wei Tu, Fine-scale prediction of human activity intensity using the interactions in physical and social spaces, International Journal of Geographical Information Science, 2021, DOI: 10.1080/13658816.2021.1912347.
自然语言处理与知识图谱:
1. 余丽,陆锋*,刘希亮,开放式地理实体关系抽取的Bootstrapping方法,测绘学报, 2016, 45(5):616-622
2. 余丽、陆锋*、刘希亮、程诗奋、张雪英,稀疏地理实体关系的关键词提取方法,地球信息科学学报, 2016, 18(11):1465-1475
3. 陆锋、余丽、仇培元,论地理知识图谱,地球信息科学学报, 2017,19(6):723-734
4. 仇培元、张恒才、余丽、陆锋*,微博客蕴含交通事件信息抽取的自动标注方法,中文信息学报, 2017, 31(2): 144-153
5. Li Yu, Peiyuan Qiu, Xiliang Liu, Feng Lu*,Bo Wan, A holistic approach to aligning geospatial data with multidimensional similarity measuring, International Journal of Digital Earth, 2017, DOI: 10.1080/17538947.2017.1359688
6. 王姬卜、陆锋、吴升、余丽*,基于自动回标的地理实体关系语料库构建方法,地球信息科学学报, 2018,20(7):871-879
7. Li Yu, Peiyuan Qiu, Jialiang Gao, Feng Lu*, A knowledge-based filtering method for open geo-entity relations, ISPRS International Journal of Geo-Information, 2019, 8, 59; doi:10.3390/ijgi8020059
8. Peiyuan Qiu, Jialiang Gao, Li Yu, Feng Lu*, Knowledge embedding with geospatial distance restriction for geographic graph completion. ISPRS International Journal of Geo-Information, 2019, 8, 254; doi:10.3390/ijgi8060254
9. Peiyuan Qiu, Li Yu, Jialiang Gao & Feng Lu*, Detecting geo-relation phrases from web texts for triplet extraction of geographic knowledge: a context-enhanced method, Big Earth Data, 2019, 3(3):297-314. DOI: 10.1080/20964471.2019.1657719
10. 高嘉良、余丽*、仇培元、陆锋,基于多源知识库的互联网开放文本地理实体关系过滤方法,地球信息科学学报, 2019, 21(9):1392-1401
11.黄宗财、仇培元*、陆锋、吴升,基于联合特征的新闻文本蕴含环境污染事件检测,地球信息科学学报,2019, 21(10): 1510-1517
12.高嘉良、仇培元、余丽、黄宗财、陆锋*,基于旅游知识图谱的可解释景点推荐,中国科学: 信息科学版, 2020, 50(7):1055-1068
海运船舶轨迹数据挖掘:
1. 彭澎、程诗奋、刘希亮、梅强、陆锋*, 全球海洋货运网络健壮性评估, 地理学报, 2017, 72(12):2241-2251
2. Peng Peng, Yu Yang, Feng Lu*, Shifen Cheng, Naixia Mou, Ren Yang, Modelling the competitiveness of the ports along the Maritime Silk Road with big geo-related data, Transportation Research Part A, 2018, 118:852-867
3. Peng Peng, Yu Yang, Shifen Cheng, Feng Lu*, Zimu Yuan, Hub-and-spoke structure: characterizing the global crude oil transport network with mass vessel trajectories, Energy, 2019, 168: 966-974
4. Peng Peng, Jessie P.H. Poon, Yu Yang*, Feng Lu*, Shifen Cheng, Global oil traffic network and diffusion of influence among ports using real time data. Energy, 2019, 10.1016/j.energy.2019.01.118
5. Hongchu Yu, Zhixiang Fang*, Feng Lu, Alan T. Murray, Hengcai Zhang, Peng Peng, Qiang Mei, Jinhai Chen, Impact of oil price fluctuations on tanker maritime network structure and traffic flow changes, Applied Energy, 2019, 237:390-403
6. Hongchu Yu, Zhixiang Fang, Feng Lu, Alan T. Murray, Zhiyuan Zhao, Yang Xu, Xiping Yang, Automatic Identification System Sensor Data-based Multi-layer Linkage Network Dynamics of Maritime Transport, Sensors, 2019, 19, 4197; DOI:10.3390/s19194197
7. 陈闪闪、彭澎*、陆锋、吴升,海上航道通航受阻对集装箱海运网络的影响分析,地理研究,2019, 38(09):2273-2287
8. Peng Peng, Shifen Cheng, Feng Lu*, Characterizing the global liquefied petroleum gas trading community using mass vessel trajectory data,Journal of Cleaner Production,2020, 252: 119883.DOI: 10.1016/j.jclepro.2019.119883
9. 彭澎、程诗奋、陈闪闪、陆锋*,全球液化石油气运输网络贸易社区特征及其演化分析,自然资源学报,2020, 35 (11): 2687-2695
10. 彭澎、程诗奋、杨宇、陆锋*,全球液化天然气运输网络特征及其演化研究,地理研究, 2021, 40(2): 373-386
11. Peng Peng, Feng Lu*, Shifen Cheng, Yu Yang, Mapping the global liquefied natural gas trade network: A perspective of maritime transportation, Journal of Cleaner Production. 2021, 283:124640. DOI: 10.1016/j.jclepro.2020.124640
12. Maohan Liang, Wen Liu*, Shichen Li, Zhe Xiao, Xin Liu, Feng Lu*, An unsupervised learning method with convolutional auto-encoder for vessel trajectory similarity computation, Ocean Engineering, 2021, 225:108803. DOI: 10.1016/j.oceaneng.2021.108803
联系方式
通信地址:100101 北京市朝阳区大屯路甲11号 中国科学院地理资源所
办公电话:010-64888966
电子邮件:luf@lreis.ac.cn; luf@igsnrr.ac.cn
微信公众号:大数据与普适GIS
更新日期:2021年6月18日
陆锋,博士,研究员,博士生导师,中国科学院地理科学与资源研究所学术委员会委员,学位评定委员会委员,期刊中心主任,中国科学院大学岗位教授。社会兼职包括中国地理信息产业协会理论与方法委员会主任、中国卫星导航定位协会室内导航定位委员会副主任、国家空天技术领域中长期科技创新规划专家组成员、“十四五”国家重点研发计划“地球观测与导航”重点专项专家组成员、国家电子政务专家委员会委员、国际空间研究会(COSPAR)中国委员会委员、《地球信息科学学报》常务副主编、船舶助导航国家地方联合工程研究中心学术委员会副主任、数字中国研究院(福建)专家委员会委员、福建省人民政府科技顾问、北京市自动驾驶车辆道路测试专家委员会委员、宁波市制造业高质量发展与智能经济战略咨询委员会委员等。研究兴趣包括移动对象数据库技术、轨迹数据挖掘、文本挖掘与知识图谱、地理空间大数据机器学习模型与算法、复杂网络分析、导航与位置服务技术、交通地理信息系统等。近年来承担国家重点研发计划、国家863计划、国家自然科学重点基金、中国科学院战略性科技先导专项项目、中国科学院重点部署项目等30余项。截至2020年,正式发表学术论文240余篇;获得发明专利授权15项;获得国家科技进步二等奖1项、省部级科技进步一等奖6项、二等奖2项。2020年获得中国智慧城市领军人物奖、中国科学院优秀导师奖。
工作经历
1991年7月-1993年7月,武汉测绘科技大学航测与遥感系/测绘遥感信息工程国家重点实验室 助教
1999年8月-2001年3月,中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室 博士后
2001年4月-2004年6月 中国科学院地理科学与资源研究所副研究员
2004年4月-2004年12月 香港大学高级访问学者
2004年6月- 中国科学院地理科学与资源研究所研究员
2008年9月- 中国科学院地理科学与资源研究所博士生导师
2001年4月- 历任中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室副主任、国家遥感中心地理信息系统部主任、资源与环境信息系统国家重点实验室常务副主任、中国科学院地理科学与资源研究所所长助理、所学术委员会委员、党委委员、学位评定委员会委员、纪委委员
近5年发表主要论文
城市计算与智能交通:
1. Xiliang Liu, Kang Liu, Mingxiao Li, Feng Lu*, A ST-CRF map-matching method for low-frequency floating car data, IEEE Transactions on Intelligent Transportation Systems, 2017, 18(5):1241-1254
2. Shifen Cheng, Feng Lu*, A Two-step method for missing spatio-temporal data reconstruction, ISPRS International Journal of Geo-Information, 2017, 6, 187; doi:10.3390/ijgi6070187
3. 刘康,仇培元,刘希亮,张恒才,王少华,陆锋*,利用词向量模型分析城市道路交通空间相关性,测绘学报,2017, 46(12):2032-2040
4. Feng Lu, Kang Liu, Yingying Duan, Shifen Cheng, Fei Du, Modelling the heterogeneous traffic correlation for city road networks with community detection, Physica A, 2018, doi.org/10.1016/j.physa.2018.02.062
5. Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu, Short-term traffic forecasting: an adaptive ST-KNN model that considers spatial heterogeneity, Computers, Environment and Urban Systems, 2018, 71:186-198
6. Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu, A spatiotemporal multi-view-based learning method for short-term traffic forecasting, ISPRS International Journal of Geo-Information, 2018, 7(6): 218; doi:10.3390/ijgi7060218
7. Kang Liu, Song Gao, Feng Lu*, Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling, Computers, Environment and Urban Systems, 2019, 74: 50-61
8. Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu, Multi-task and multi-view learning based on particle swarm optimization for short-term traffic forecasting, Knowledge-Based Systems, 2019, https://doi.org/10.1016/j.knosys.2019.05.023.
9. Beibei Zhang, Shifen Cheng*, Feng Lu, and Sheng Wu, Spatial characteristics and factor analysis of pollution emission from heavy-duty diesel trucks in the Beijing-Tianjin-Hebei region, China, International Journal of Environmental Research and Public Health, 2019, 16, 4973; DOI:10.3390/ijerph16244973
10.Shifen Cheng, Beibei Zhang, Peng Peng, Zhenzhen Yang, Feng Lu*, Spatiotemporal evolution pattern detection for heavy-duty diesel truck emissions using trajectory mining: a case study of Tianjin, China. Journal of Cleaner Production, 2020, 244:118654. DOI:10.1016/j.jclepro.2019.118654
11.Shifen Cheng, Feng Lu*, Peng Peng, A high-resolution emissions inventory and its spatiotemporal pattern variations for heavy-duty diesel trucks in Beijing, China, Journal of Cleaner Production, 2020, 250:119445.DOI: 10.1016/j.jclepro.2019.119445
12.Kang Liu, Peiyuan Qiu, Song Gao, Feng Lu, Jincheng Jiang, Ling Yin*, Investigating urban metro stations as cognitive places in cities using points of interest. Cities, 2020, 97:102561. DOI: 10.1016/j.cities.2019.102561
13.Kang Liu, Ling Yin*, Feng Lu, Naixia Mou, Visualizing and exploring POI configurations of urban regions on POI-type semantic space. Cities, 2020, 99:102610. DOI: 10.1016/j.cities.2020.102610
14.Shifen Cheng, Peng Peng, Feng Lu*, A lightweight ensemble spatiotemporal interpolation model for geospatial data. International Journal of Geographical Information Science, 2020, 34(9): 1849-1872. DOI: 10.1080/13658816.2020.1725016
15.Shifen Cheng, Feng Lu*, Peng Peng, Short-term traffic forecasting by mining the non-stationarity of spatiotemporal pattern, IEEE Transactions on Intelligent Transportation Systems, 2020, 10.1109/TITS.2020.2991781
16. 程诗奋、彭澎、张恒才、陆锋*,异质稀疏分布时空数据重构与预测方法探讨,武汉大学学报(信息科学版),2020,45(12):1919-1929
移动对象数据库与位置服务:
1. Hengcai Zhang, Feng Lu*, Jianqiu Xu, Modeling and querying moving objects with social relationships, ISPRS International Journal of Geo-Information, 2016, 5, 121, doi:10.3390/ijgi5070121
2. Hengcai Zhang, Feng Lu*, Jie Chen, A line graph-based continuous range query method for moving objects in networks, ISPRS International Journal of Geo-Information, 2016, 5, 246; doi:10.3390/ijgi5120246
3. Hengcai Zhang, Feng Lu*, GSMNet: A hierarchical graph model for moving objects in networks, ISPRS International Journal of Geo-Information, 2017, 6, 71; doi:10.3390/ijgi6030071
4. Mingxiao Li, Feng Lu, Hengcai Zhang*, Jie Chen, Predicting future locations of moving objects with deep fuzzy-LSTM networks, Transportmetrica A: Transport Science, 2018, DOI: 10.1080/23249935.2018.1552334
5. Mingxiao Li, Song Gao, Feng Lu, Hengcai Zhang*, Reconstruction of human movement trajectories from large-scale low-frequency mobile phone data. Computers, Environment and Urban Systems, 2019, 77, https://doi.org/10.1016/j.compenvurbsys.2019.101346
6. Mingxiao Li, Song Gao, Feng Lu, Huan Tong, Hengcai Zhang*, Dynamic estimation of individual exposure levels to air pollution using trajectories reconstructed from mobile phone data. International Journal of Environmental Research and Public Health, 2019, 16, 4522; DOI: 10.3390/ijerph16224522
7. Peixiao Wang, Sheng Wu, Hengcai Zhang*, Feng Lu. Indoor location prediction method for shopping malls based on location sequence similarity. ISPRS International Journal of Geo-Information, 2019, 8, 517; DOI:10.3390/ijgi8110517
8. Peixiao Wang, Hengcai Zhang*, Hongen Wang, Feng Lu, Sheng Wu, A hybrid Markov and LSTM model for indoor location prediction, IEEE Access, 2019, 7(1):185928-185940. DOI:10.1109/ACCESS.2019.2961559
9. 王培晓、吴升、张恒才*、陆锋、王宏恩,一种室内人群时空聚集区域识别方法,武汉大学学报(信息科学版),2020,DOI: 10.13203/j.whugis20190228
10.Yang Xu, Xinyu Li, Shih-Lung Shaw, Feng Lu, Ling Yin, Biyu Chen. Effects of data preprocessing methods on addressing location uncertainty in mobile signaling data. Annals of the American Association of Geographers, 2021, 111(2):515-539. DOI: 10.1080/24694452.2020.1773232
11.Mingxiao Li, Song Gao*, Feng Lu, Kang Liu, Hengcai Zhang, Wei Tu, Fine-scale prediction of human activity intensity using the interactions in physical and social spaces, International Journal of Geographical Information Science, 2021, DOI: 10.1080/13658816.2021.1912347.
自然语言处理与知识图谱:
1. 余丽,陆锋*,刘希亮,开放式地理实体关系抽取的Bootstrapping方法,测绘学报, 2016, 45(5):616-622
2. 余丽、陆锋*、刘希亮、程诗奋、张雪英,稀疏地理实体关系的关键词提取方法,地球信息科学学报, 2016, 18(11):1465-1475
3. 陆锋、余丽、仇培元,论地理知识图谱,地球信息科学学报, 2017,19(6):723-734
4. 仇培元、张恒才、余丽、陆锋*,微博客蕴含交通事件信息抽取的自动标注方法,中文信息学报, 2017, 31(2): 144-153
5. Li Yu, Peiyuan Qiu, Xiliang Liu, Feng Lu*,Bo Wan, A holistic approach to aligning geospatial data with multidimensional similarity measuring, International Journal of Digital Earth, 2017, DOI: 10.1080/17538947.2017.1359688
6. 王姬卜、陆锋、吴升、余丽*,基于自动回标的地理实体关系语料库构建方法,地球信息科学学报, 2018,20(7):871-879
7. Li Yu, Peiyuan Qiu, Jialiang Gao, Feng Lu*, A knowledge-based filtering method for open geo-entity relations, ISPRS International Journal of Geo-Information, 2019, 8, 59; doi:10.3390/ijgi8020059
8. Peiyuan Qiu, Jialiang Gao, Li Yu, Feng Lu*, Knowledge embedding with geospatial distance restriction for geographic graph completion. ISPRS International Journal of Geo-Information, 2019, 8, 254; doi:10.3390/ijgi8060254
9. Peiyuan Qiu, Li Yu, Jialiang Gao & Feng Lu*, Detecting geo-relation phrases from web texts for triplet extraction of geographic knowledge: a context-enhanced method, Big Earth Data, 2019, 3(3):297-314. DOI: 10.1080/20964471.2019.1657719
10. 高嘉良、余丽*、仇培元、陆锋,基于多源知识库的互联网开放文本地理实体关系过滤方法,地球信息科学学报, 2019, 21(9):1392-1401
11.黄宗财、仇培元*、陆锋、吴升,基于联合特征的新闻文本蕴含环境污染事件检测,地球信息科学学报,2019, 21(10): 1510-1517
12.高嘉良、仇培元、余丽、黄宗财、陆锋*,基于旅游知识图谱的可解释景点推荐,中国科学: 信息科学版, 2020, 50(7):1055-1068
海运船舶轨迹数据挖掘:
1. 彭澎、程诗奋、刘希亮、梅强、陆锋*, 全球海洋货运网络健壮性评估, 地理学报, 2017, 72(12):2241-2251
2. Peng Peng, Yu Yang, Feng Lu*, Shifen Cheng, Naixia Mou, Ren Yang, Modelling the competitiveness of the ports along the Maritime Silk Road with big geo-related data, Transportation Research Part A, 2018, 118:852-867
3. Peng Peng, Yu Yang, Shifen Cheng, Feng Lu*, Zimu Yuan, Hub-and-spoke structure: characterizing the global crude oil transport network with mass vessel trajectories, Energy, 2019, 168: 966-974
4. Peng Peng, Jessie P.H. Poon, Yu Yang*, Feng Lu*, Shifen Cheng, Global oil traffic network and diffusion of influence among ports using real time data. Energy, 2019, 10.1016/j.energy.2019.01.118
5. Hongchu Yu, Zhixiang Fang*, Feng Lu, Alan T. Murray, Hengcai Zhang, Peng Peng, Qiang Mei, Jinhai Chen, Impact of oil price fluctuations on tanker maritime network structure and traffic flow changes, Applied Energy, 2019, 237:390-403
6. Hongchu Yu, Zhixiang Fang, Feng Lu, Alan T. Murray, Zhiyuan Zhao, Yang Xu, Xiping Yang, Automatic Identification System Sensor Data-based Multi-layer Linkage Network Dynamics of Maritime Transport, Sensors, 2019, 19, 4197; DOI:10.3390/s19194197
7. 陈闪闪、彭澎*、陆锋、吴升,海上航道通航受阻对集装箱海运网络的影响分析,地理研究,2019, 38(09):2273-2287
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微信公众号:大数据与普适GIS
更新日期:2021年6月18日