众包时空数据驱动的城市地理信息推测综述

阮思捷; 熊可钦; 王树良; 耿晶; 鲍捷; 郑宇

doi:10.12263/DZXB.20230131

您当前的位置：

首页 >

文章列表页 >

众包时空数据驱动的城市地理信息推测综述

综述评论 | 更新时间：2025-12-08

- 众包时空数据驱动的城市地理信息推测综述
- A Survey of Urban Geographic Information Inference Driven by Crowd-Sourced Spatio-Temporal Data
- 电子学报 2023年51卷第8期页码：2238-2259
- 作者机构：
  
  1.北京理工大学计算机学院,北京 100081
  2.京东城市(北京)数字科技有限公司,北京 100176
  3.京东智能城市研究院,北京 100176
- 作者简介：
  
  [ "阮思捷男，1994年12月出生于浙江省杭州市.现为北京理工大学计算机学院特别副研究员.主要研究方向为城市计算与时空数据挖掘.曾获ACM SIGSPATIAL中国分会优博奖.在国内外顶尖期刊和会议上发表学术论文30余篇. E-mail: sjruan@bit.edu.cn" ]
  [ "熊可钦女，2002年4月出生于江西省抚州市.现为北京理工大学本科生.专业为计算机科学与技术.E-mail: keqin0127x@163.com" ]
  [ "王树良（通讯作者）男，1974年7月生，山东梁山人.现为北京理工大学教授、博士生导师，电子政务研究院执行院长，中国制造企业双创发展联盟副理事长，国家重点研发计划项目首席科学家.主要研究方向为空间数据挖掘与社会智能治理.获国家科技进步一等奖等. Email: slwang2011@bit.edu.cn" ]
  [ "耿晶女，1986年2月出生于山东省威海市.现为北京理工大学计算机学院特别副研究员.主要研究方向为地理信息系统、时空数据分析、大数据智能挖掘、电子政务相关理论.E-mail: janegeng@bit.edu.cn" ]
  [ "鲍捷男，1985年5月生，浙江金华人.美国明尼苏达大学计算机系博士.现为京东科技研发总监.主要研究方向为时空大数据管理与挖掘.曾在贵阳、上海以及北京落地多个智慧城市项目，并在世界顶尖期刊和会议上发表学术论文60余篇.E-mail: baojie@jd.com" ]
  [ "郑宇男，1975年10月生，湖南衡阳人.现为京东集团副总裁、京东科技首席数据科学家，上海交通大学讲座教授，南京大学、香港科技大学等多所知名高校的客座教授和博士生导师，国家重点研发计划项目首席科学家.他是城市计算领域的先驱和奠基人，也是大数据和人工智能领域的领军人物和实践者，被评为IEEE Fellow.E-mail: msyuzheng@outlook.com" ]
- 基金信息：
  
  国家自然科学基金(62076027;42201461);北京理工大学青年教师学术启动计划(6120220113)
- DOI：10.12263/DZXB.20230131
  中图分类号： TP391;
- 收稿：2023-02-15，
  
  修回：2023-07-17，
  
  纸质出版：2023-08-25
- 稿件说明：
移动端阅览
阮思捷,熊可钦,王树良等.众包时空数据驱动的城市地理信息推测综述[J].电子学报,2023,51(08):2238-2259.

RUAN Si-jie,XIONG Ke-qin,WANG Shu-liang,et al.A Survey of Urban Geographic Information Inference Driven by Crowd-Sourced Spatio-Temporal Data[J].ACTA ELECTRONICA SINICA,2023,51(08):2238-2259.
阮思捷,熊可钦,王树良等.众包时空数据驱动的城市地理信息推测综述[J].电子学报,2023,51(08):2238-2259. DOI： 10.12263/DZXB.20230131.

RUAN Si-jie,XIONG Ke-qin,WANG Shu-liang,et al.A Survey of Urban Geographic Information Inference Driven by Crowd-Sourced Spatio-Temporal Data[J].ACTA ELECTRONICA SINICA,2023,51(08):2238-2259. DOI： 10.12263/DZXB.20230131.

摘要

对地理信息的准确掌握是城市中各种智能决策得以实现的基础.传统地理信息收集主要靠人工测绘、人工巡检或固定传感器感知，设备、人力成本高昂.近年来，随着移动互联网的发展，泛在的移动群体在城市中产生了海量的时空数据，他们有意或无意间成为城市的传感器，使研究人员有机会利用众包的思路基于此类数据推测城市地理信息.基于众包时空数据推测城市地理信息具有成本低、空间覆盖广、更新及时等优点.但其具有严重的数据质量问题，对城市地理信息推测带来了巨大挑战.本文综述了根据轨迹、基于位置的社交网络、街景等众包时空数据，推测城市中以路段、兴趣点、兴趣面为代表的地理实体的位置和属性的方法.本文给出了众包时空数据和地理实体的定义，详细比较了众包时空数据驱动的推测方法与传统方法的优劣，说明了研究问题和挑战，然后讨论了地图匹配、名称提取、位置发现和统计属性推测四个研究问题的研究进展，最后展望了该领域未来的研究方向.

Abstract

Knowing the accurate geographic information is the basis to achieve the intelligent decisions in cities. Traditional geographic information collecting mainly relies on manual mapping

patrolling or sensing by static geographical sensors

which are expensive given specialized equipment and labors. Recently

with the development of the mobile Internet

the ubiquitous moving objects has generated massive spatio-temporal data in the urban spaces

who act as sensors of the city consciously or unconsciously

and make it possible to infer the geographic information based on those data in a crowd-sourced manner. The geographic information inference based on the crowd-sourced spatio-temporal data enjoys the advantages of low cost

high spatial coverage

and timely updates. However

it also has the data quality issues

which introduce great challenges to the urban geographic information inference. In this paper

we survey the location and attribute inference of geospatial entities

including the road network

point of interest and area of interest

based on crowd-sourced spatio-temporal data

e.g.

trajectories

location-based social network

and street views. We give the definitions of crowd-sourced spatio-temporal data and geospatial entities

compare the pros and cons of utilizing the crowd-sourced spatio-temporal data to infer the geographic information against traditional methods

and elaborate the research problems and challenges. After that

we review four research problems

i.e.

map matching

name extraction

location discovery and statistical attribute inference. Finally

we present the future research directions and conclude the paper.

关键词

Keywords

references

BAO J , HE T F , RUAN S J , et al . Planning bike lanes based on sharing-bikes' trajectories [C ] // Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . New York : ACM , 2017 : 1377 - 1386 .

HE T F , BAO J , RUAN S J , et al . Interactive bike lane planning using sharing bikes' trajectories [J ] . IEEE Transactions on Knowledge and Data Engineering , 2020 , 32 ( 8 ): 1529 - 1542 .

PAN Z Y , ZHANG W T , LIANG Y X , et al . Spatio-temporal meta learning for urban traffic prediction [J ] . IEEE Transactions on Knowledge and Data Engineering , 2022 , 34 ( 3 ): 1462 - 1476 .

ZHANG J B , ZHENG Y , QI D K . Deep spatio-temporal residual networks for citywide crowd flows prediction [J ] . Proceedings of the AAAI Conference on Artificial Intelligence , 2017 , 31 ( 1 ): 1655 - 1661 .

LI Y H , BAO J , LI Y H , et al . Mining the most influential k -location set from massive trajectories [C ] // Proceedings of the 24th ACM SIGSpatial International Conference on Advances in Geographic Information Systems . New York : ACM , 2016 : 1 - 4 .

ZHANG P , BAO Z F , LI Y C , et al . Trajectory-driven influential billboard placement [C ] // Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . New York : ACM , 2018 : 2748 - 2757 .

RUAN S J , BAO J E , LIANG Y X , et al . Dynamic public resource allocation based on human mobility prediction [J ] . Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2020 , 4 ( 1 ): 1 - 22 .

HU Y , RUAN S J , NI Y T , et al . SALON: A universal stay point-based location analysis platform [C ] // Proceedings of the 29th International Conference on Advances in Geographic Information Systems . New York : ACM , 2021 : 407 - 410 .

王家耀 , 魏海平 , 成毅 , 等 . 时空GIS的研究与进展 [J ] . 海洋测绘 , 2004 , 24 ( 5 ): 1 - 4 .

WANG J Y , WEI H P , CHENG Y , et al . The research and development of spatio-temporal GIS [J ] . Hydrographic Surveying and Charting , 2004 , 24 ( 5 ): 1 - 4 . (in Chinese)

李德仁 , 陈小明 , 郭丙轩 , 等 . 车载GPS道路信息采集和更新系统研究 [J ] . 武汉测绘科技大学学报 , 2000 , 25 ( 2 ): 95 - 99 .

LI D R , CHEN X M , GUO B X , et al . Study on car-borne GPS road information collecting and update system [J ] . Journal of Wuhan Technical University of Surveying and Mapping , 2000 , 25 ( 2 ): 95 - 99 . (in Chinese)

王龙波 . 基于GPS与实景影像的POI快速采集技术 [J ] . 中国科技信息 , 2007 ( 12 ): 121 - 122 .

WANG L B . Fast POI collecting technologies based on GPS and real-scane imagery [J ] . China Science and Technology Information , 2007 ( 12 ): 121 - 122 . (in Chinese)

皮晓亮 , 王正 , 韩皓 , 等 . 基于环形线圈检测器采集信息的交通状态分类方法应用研究 [J ] . 公路交通科技 , 2006 , 23 ( 4 ): 115 - 119 .

PI X L , WANG Z , HAN H , et al . Application research of traffic state classification method based on collected information from loop detector [J ] . Journal of Highway and Transportation Research and Development , 2006 , 23 ( 4 ): 115 - 119 . (in Chinese)

童咏昕 , 袁野 , 成雨蓉 , 等 . 时空众包数据管理技术研究综述 [J ] . 软件学报 , 2017 , 28 ( 1 ): 35 - 58 .

TONG Y X , YUAN Y , CHENG Y R , et al . Survey on spatiotemporal crowdsourced data management techniques [J ] . Journal of Software , 2017 , 28 ( 1 ): 35 - 58 . (in Chinese)

CAMPBELL A T , EISENMAN S B , LANE N D , et al . People-centric urban sensing [C ] // Proceedings of the 2nd Annual International Workshop on Wireless Internet . New York : ACM , 2006 : 18-es.

陈荟慧 , 郭斌 , 於志文 . 移动群智感知应用 [J ] . 中兴通讯技术 , 2014 , 20 ( 1 ): 35 - 37 .

CHEN H H , GUO B , YU Z W . Mobile crowd-sensing application [J ] . ZTE Technology Journal , 2014 , 20 ( 1 ): 35 - 37 . (in Chinese)

CAPPONI A , FIANDRINO C , KANTARCI B , et al . A survey on mobile crowdsensing systems: Challenges, solutions, and opportunities [J ] . IEEE Communications Surveys & Tutorials , 2019 , 21 ( 3 ): 2419 - 2465 .

GOODCHILD M F . Citizens as sensors: The world of volunteered geography [J ] . GeoJournal , 2007 , 69 ( 4 ): 211 - 221 .

ZHENG Y , CAPRA L , WOLFSON O , et al . Urban computing: Concepts, methodologies, and applications [J ] . ACM Transactions on Intelligent Systems and Technology , 2014 , 5 ( 3 ): 38 .

ZHAO L S , MAO J L , PU M , et al . Automatic calibration of road intersection topology using trajectories [C ] // 2020 IEEE 36th International Conference on Data Engineering (ICDE) . Piscataway : IEEE , 2020 : 1633 - 1644 .

KRAVI E , KANZA Y , KIMELFELD B , et al . Geosocial location classification: Associating type to places based on geotagged social-media posts [C ] // Proceedings of the 28th International Conference on Advances in Geographic Information Systems . New York : ACM , 2020 : 167 - 170 .

SONG Y T , LI J W , CHEN L Y , et al . A semantic segmentation based POI coordinates generating framework for on-demand food delivery service [C ] // Proceedings of the 29th International Conference on Advances in Geographic Information Systems . New York : ACM , 2021 : 379 - 388 .

XU Q X , RUAN S J , LONG C , et al . Traffic speed imputation with spatio-temporal attentions and cycle-perceptual training [C ] // Proceedings of the 31st ACM International Conference on Information & Knowledge Management . New York : ACM , 2022 : 2280 - 2289 .

ZHAO Y , LI Y , WANG Y , et al . Destination-aware task assignment in spatial crowdsourcing [C ] // Proceedings of the 2017 ACM on Conference on Information and Knowledge Management . New York : ACM , 2017 : 297 - 306 .

JI S G , ZHENG Y , LI T R . Urban sensing based on human mobility [C ] // Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing . New York : ACM , 2016 : 1040 - 1051 .

WU D , XIAO T , LIAO X W , et al . When sharing economy meets IoT [J ] . Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2020 , 4 ( 2 ): 1 - 26 .

CHAO P F , HUA W , MAO R , et al . A survey and quantitative study on map inference algorithms from GPS trajectories [J ] . IEEE Transactions on Knowledge and Data Engineering , 2022 , 34 ( 1 ): 15 - 28 .

SILVA T H , VIANA A C , BENEVENUTO F , et al . Urban computing leveraging location-based social network data [J ] . ACM Computing Surveys , 2020 , 52 ( 1 ): 1 - 39 .

唐炉亮 , 赵紫龙 , 杨雪 , 等 . 大数据环境下道路场景高时空分辨率众包感知方法 [J ] . 测绘学报 , 2022 , 51 ( 6 ): 1070 - 1090 .

TANG L L , ZHAO Z L , YANG X , et al . Road crowd-sensing with high spatio-temporal resolution in big data era [J ] . Acta Geodaetica et Cartographica Sinica , 2022 , 51 ( 6 ): 1070 - 1090 . (in Chinese)

Data West Research Agency . A Practitioner's Guide to GIS Terminology: A Glossary of Geographic Information System Terms [M ] . University Place : Data West Research Agency , 2000 .

刘海 , 郝克刚 . 软件缺陷数据的分析方法及其实现 [J ] . 计算机科学 , 2008 , 35 ( 8 ): 262 - 264 .

LIU H , HAO K G . Method of software defect data analysis and its implementation [J ] . Computer Science , 2008 , 35 ( 8 ): 262 - 264 . (in Chinese)

YI X W , DUAN Z W , LI T , et al . CityTraffic: Modeling citywide traffic via neural memorization and generalization approach [C ] // Proceedings of the 28th ACM International Conference on Information and Knowledge Management . New York : ACM , 2019 : 2665 - 2671 .

HE T F , BAO J , LI R Y , et al . Detecting vehicle illegal parking events using sharing bikes' trajectories [C ] // Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . New York : ACM , 2018 : 340 - 349 .

KWON J , VARAIYA P , SKABARDONIS A . Estimation of truck traffic volume from single loop detectors with lane-to-lane speed correlation [J ] . Transportation Research Record: Journal of the Transportation Research Board , 2003 , 1856 ( 1 ): 106 - 117 .

DEMIR I , KOPERSKI K , LINDENBAUM D , et al . DeepGlobe 2018: A challenge to parse the earth through satellite images [C ] // 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) . Piscataway : IEEE , 2018 : 172 - 17209 .

PAOLA J D , SCHOWENGERDT R A . A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classification [J ] . IEEE Transactions on Geoscience and Remote Sensing , 1995 , 33 ( 4 ): 981 - 996 .

HE S T , BASTANI F , JAGWANI S , et al . RoadTagger: Robust road attribute inference with graph neural networks [J ] . Proceedings of the AAAI Conference on Artificial Intelligence , 2020 , 34 ( 7 ): 10965 - 10972 .

KHALIL M , LI J P , SHARIF A , et al . Traffic congestion detection by use of satellites view [C ] // 2017 14th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) . Piscataway : IEEE , 2018 : 278 - 280 .

STANOJEVIC R , ABBAR S , THIRUMURUGANATHAN S , et al . Road network fusion for incremental map updates [C ] // LBS 2018: 14th International Conference on Location Based Services . Cham : Springer , 2018 : 91 - 109 .

BALSEBRE P , YAO D Z , CONG G , et al . Geospatial entity resolution [C ] // Proceedings of the ACM Web Conference 2022 . New York : ACM , 2022 : 3061 - 3070 .

YUAN J , ZHENG Y , ZHANG C Y , et al . An interactive-voting based map matching algorithm [C ] // 2010 Eleventh International Conference on Mobile Data Management . Piscataway : IEEE , 2010 : 43 - 52 .

RUAN S J , LONG C , MA Z P , et al . Service time prediction for delivery tasks via spatial meta-learning [C ] // Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . New York : ACM , 2022 : 3829 - 3837 .

RUAN S J , LI R Y , BAO J , et al . CloudTP: A cloud-based flexible trajectory preprocessing framework [C ] // 2018 IEEE 34th International Conference on Data Engineering (ICDE) . Piscataway : IEEE , 2018 : 1601 - 1604 .

ZHENG Y . Trajectory data mining: An overview [J ] . ACM Transactions on Intelligent Systems and Technology , 6 ( 3 ): 29 .

ZHENG Y , XIE X , MA W Y . GeoLife: A collaborative social networking service among user, location and trajectory [J ] . IEEE Data Engineering Bulletin , 2010 , 33 : 32 - 39 .

LI Q N , ZHENG Y , XIE X , et al . Mining user similarity based on location history [C ] // Proceedings of the 16th ACM SIGSpatial International Conference on Advances in Geographic Information Systems . New York : ACM , 2008 : 1 - 10 .

YUAN J , ZHENG Y , ZHANG L H , et al . Where to find my next passenger [C ] // Proceedings of the 13th International Conference on Ubiquitous Computing . New York : ACM , 2011 : 109 - 118 .

LEUNG D , NEWSAM S . Exploring Geotagged images for land-use classification [C ] // Proceedings of the ACM Multimedia 2012 Workshop on Geotagging and Its Applications in Multimedia . New York : ACM , 2012 : 3 - 8 .

ALVARES L O , BOGORNY V , KUIJPERS B , et al . A model for enriching trajectories with semantic geographical information [C ] // Proceedings of the 15th Annual ACM International Symposium on Advances in Geographic Information Systems . New York : ACM , 2007 : 1 - 8 .

CHOI D W , PEI J A , HEINIS T . Efficient mining of regional movement patterns in semantic trajectories [J ] . Proceedings of the VLDB Endowment , 2017 , 10 ( 13 ): 2073 - 2084 .

BHATTACHARYA T , KULIK L , BAILEY J . Automatically recognizing places of interest from unreliable GPS data using spatio-temporal density estimation and line intersections [J ] . Pervasive and Mobile Computing , 2015 , 19 : 86 - 107 .

KELES I , SCHUBERT M , KRÖGER P , et al . Extracting visited points of interest from vehicle trajectories [C ] // Proceedings of the 4th International ACM Workshop on Managing and Mining Enriched Geo-Spatial Data . New York : ACM , 2017 : 1 - 6 .

ZHANG F Z , WILKIE D , ZHENG Y , et al . Sensing the pulse of urban refueling behavior [C ] // Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing . New York : ACM , 2013 : 13 - 22 .

ZHANG F Z , YUAN N J , WILKIE D , et al . Sensing the pulse of urban refueling behavior: A perspective from taxi mobility [J ] . ACM Transactions on Intelligent Systems and Technology , 2015 , 6 ( 3 ): 1 - 23 .

WU H , SUN W W , ZHENG B H . Is only one GPS position sufficient to locate You to the road network accurately? [C ] // Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing . New York : ACM , 2016 : 740 - 751 .

NEWSON P , KRUMM J . Hidden Markov map matching through noise and sparseness [C ] // Proceedings of the 17th ACM SIGSpatial International Conference on Advances in Geographic Information Systems . New York : ACM , 2009 : 336 - 343 .

LOU Y , ZHANG C Y , ZHENG Y , et al . Map-matching for low-sampling-rate GPS trajectories [C ] // Proceedings of the 17th ACM SIGSpatial International Conference on Advances in Geographic Information Systems . New York : ACM , 2009 : 352 - 361 .

ZHAO K , FENG J , XU Z , et al . DeepMM: Deep learning based map matching with data augmentation [C ] // Proceedings of the 27th ACM SIGSpatial International Conference on Advances in Geographic Information Systems . New York : ACM , 2019 : 452 - 455 .

REN H M , RUAN S J , LI Y H , et al . MTrajRec: Map-constrained trajectory recovery via Seq2Seq multi-task learning [C ] // Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining . New York : ACM , 2021 : 1410 - 1419 .

YAN Z X , CHAKRABORTY D , PARENT C , et al . SeMiTri: A framework for semantic annotation of heterogeneous trajectories [C ] // Proceedings of the 14th International Conference on Extending Database Technology . New York : ACM , 2011 : 259 - 270 .

NISHIDA K , TODA H , KURASHIMA T , et al . Probabilistic identification of visited point-of-interest for personalized automatic check-in [C ] // Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing . New York : ACM , 2014 : 631 - 642 .

SUZUKI J , SUHARA Y , TODA H , et al . Personalized visited-POI assignment to individual raw GPS trajectories [J ] . ACM Transactions on Spatial Algorithms and Systems , 5 ( 3 ): 16 .

RUAN S J , FU X , LONG C , et al . Filling delivery time automatically based on couriers' trajectories [J ] . IEEE Transactions on Knowledge and Data Engineering , 2023 , 35 ( 2 ): 1528 - 1540 .

JONES C B , PURVES R S , CLOUGH P D , et al . Modelling vague places with knowledge from the Web [J ] . International Journal of Geographical Information Science , 2008 , 22 ( 10 ): 1045 - 1065 .

LI L N , GOODCHILD M F . Constructing places from spatial footprints [C ] // Proceedings of the 1st ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information . New York : ACM , 2012 : 15 - 21 .

HOLLENSTEIN L , PURVES R . Exploring place through user-generated content: Using Flickr tags to describe city cores [J ] . Journal of Spatial Information Science , 2010 ( 1 ): 21 - 48 .

RATTENBURY T , NAAMAN M . Methods for extracting place semantics from Flickr tags [J ] . ACM Transactions on the Web , 2009 , 3 ( 1 ): 1 - 30 .

BAEZA-YATES R , RIBEIRO-NETO B . Modern Information Retrieval [M ] . Austin : Addison-Wesley Longman , 1999 .

LLOYD S . Least squares quantization in PCM [J ] . IEEE Transactions on Information Theory , 1982 , 28 ( 2 ): 129 - 137 .

HUANG Z H , XU W , YU K . Bidirectional LSTM-CRF models for sequence tagging [EB/OL ] . ( 2015-08-09 )[ 2023-02-15 ] . https://arxiv.org/abs/1508.01991 https://arxiv.org/abs/1508.01991 .

ABID N , UL HASAN A , SHAFAIT F . DeepParse: A trainable postal address parser [C ] // 2018 Digital Image Computing: Techniques and Applications (DICTA) . Piscataway : IEEE , 2019 : 1 - 8 .

DEVLIN J , CHANG M W , LEE K , et al . BERT: Pre-training of deep bidirectional transformers for language understanding [EB/OL ] . ( 2018-10-11 )[ 2023-02-15 ] . https://arxiv.org/abs/1810.04805 https://arxiv.org/abs/1810.04805 .

HE T F , CHEN G C , MENG C S , et al . POI alias discovery in delivery addresses using user locations [C ] // Proceedings of the 29th International Conference on Advances in Geographic Information Systems . New York : ACM , 2021 : 225 - 228 .

GAO S , LI L N , LI W W , et al . Constructing gazetteers from volunteered big geo-data based on Hadoop [J ] . Computers, Environment and Urban Systems , 2017 , 61 : 172 - 186 .

INTAGORN S , LERMAN K . Learning boundaries of vague places from noisy annotations [C ] // Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems . New York : ACM , 2011 : 425 - 428 .

KEßLER C , MAUÉ P , HEUER J T , et al . Bottom-up gazetteers: Learning from the implicit semantics of geotags [C ] // International Conference on GeoSpatial Sematics . Berlin : Springer , 2009 : 83 - 102 .

RUAN S J , XIONG Z , LONG C , et al . Doing in one go: Delivery time inference based on couriers' trajectories [C ] // Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . New York : ACM , 2020 : 2813 - 2821 .

SRIVASTAVA V , TEJASWIN P , DHAKAD L , et al . A geocoding framework powered by delivery data [C ] // Proceedings of the 28th International Conference on Advances in Geographic Information Systems . New York : ACM , 2020 : 568 - 577 .

FORMAN G . Getting your package to the right place: Supervised machine learning for geolocation [C ] // Joint European Conference on Machine Learning and Knowledge Discovery in Databases . Cham : Springer , 2021 : 403 - 419 .

RUAN S J , LONG C , YANG X D , et al . Discovering actual delivery locations from mis-annotated couriers' trajectories [C ] // 2022 IEEE 38th International Conference on Data Engineering (ICDE) . Piscataway : IEEE , 2022 : 3241 - 3253 .

VASWANI A , SHAZEER N , PARMAR N , et al . Attention is all you need [C ] // Proceedings of the Advances in Neural Information Processing Systems . Long Beach : Curran Associates Inc. , 2017 : 5998 - 6008 .

DAHIYA M , SAMATIA D , RUSTOGI K . Learning locality maps from noisy geospatial labels [C ] // Proceedings of the 35th Annual ACM Symposium on Applied Computing . New York : ACM , 2020 : 601 - 608 .

FANG Z H , WANG G A , XIE X Y , et al . Urban map inference by pervasive vehicular sensing systems with complementary mobility [J ] . Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies , 2021 , 5 ( 1 ): 1 - 24 .

DING X , FAN H C , GONG J Y . Towards generating network of bikeways from Mapillary data [J ] . Computers, Environment and Urban Systems , 2021 , 88 : 101632 .

BIAGIONI J , ERIKSSON J . Inferring Road maps from global positioning system traces [J ] . Transportation Research Record: Journal of the Transportation Research Board , 2012 , 2291 ( 1 ): 61 - 71 .

EDELKAMP S , SCHRÖDL S . Route planning and map inference with global positioning traces [M ] // Lecture Notes in Computer Science . Berlin : Springer , 2003 : 128 - 151 .

CHEN C , LU C W , HUANG Q X , et al . City-scale map creation and updating using GPS collections [C ] // Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . New York : ACM , 2016 : 1465 - 1474 .

STANOJEVIC R , ABBAR S , THIRUMURUGANATHAN S , et al . Robust road map inference through network alignment of trajectories [C ] // Proceedings of the 2018 SIAM International Conference on Data Mining . Philadelphia : Society for Industrial and Applied Mathematics , 2018 : 135 - 143 .

CAO L L , KRUMM J . From GPS traces to a routable road map [C ] // Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems . New York : ACM , 2009 : 3 - 12 .

NIEHOEFER B , BURDA R , WIETFELD C , et al . GPS community map generation for enhanced routing methods based on trace-collection by mobile phones [C ] // 2009 First International Conference on Advances in Satellite and Space Communications . Piscataway : IEEE , 2009 : 156 - 161 .

BIAGIONI J , ERIKSSON J . Map inference in the face of noise and disparity [C ] // Proceedings of the 20th International Conference on Advances in Geographic Information Systems . New York : ACM , 2012 : 79 - 88 .

WANG S Y , WANG Y S , LI Y J . Efficient map reconstruction and augmentation via topological methods [C ] // Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems . New York : ACM , 2015 : 1 - 10 .

YANG X E , TANG L L , REN C , et al . Pedestrian network generation based on crowdsourced tracking data [J ] . International Journal of Geographical Information Science , 2020 , 34 ( 5 ): 1051 - 1074 .

HE S T , BASTANI F , ABBAR S , et al . RoadRunner: Improving the precision of road network inference from GPS trajectories [C ] // Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems . New York : ACM , 2018 : 3 - 12 .

WU H , ZHANG H Y , ZHANG X Y , et al . Deep Dual Mapper: A gated fusion network for automatic map extraction using aerial images and trajectories [J ] . Proceedings of the AAAI Conference on Artificial Intelligence , 2020 , 34 ( 1 ): 1037 - 1045 .

RUAN S J , LONG C , BAO J E , et al . Learning to generate maps from trajectories [J ] . Proceedings of the AAAI Conference on Artificial Intelligence , 2020 , 34 ( 1 ): 890 - 897 .

YANG J Z , YE X Q , WU B , et al . DuARE: Automatic road extraction with aerial images and trajectory data at Baidu maps [C ] // Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . New York : ACM , 2022 : 4321 - 4331 .

WANG Y , LIU X M , WEI H , et al . CrowdAtlas: Self-updating maps for cloud and personal use [C ] // MobiSys'13: Proceeding of the 11th Annual International Conference on Mobile Systems , Applications, and Services . New York : ACM , 2013 : 469 - 470 .

WU H , TU C C , SUN W W , et al . GLUE: A parameter-tuning-free map updating system [C ] // Proceedings of the 24th ACM International on Conference on Information and Knowledge Management . New York : ACM , 2015 : 683 - 692 .

SHAN Z Q , WU H , SUN W W , et al . COBWEB: A robust map update system using GPS trajectories [C ] // Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing . New York : ACM , 2015 : 927 - 937 .

CAO C , LIU Z D , LI M , et al . Walkway discovery from large scale crowdsensing [C ] // 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) . Piscataway : IEEE , 2018 : 13 - 24 .

SIBSON R . SLINK: An optimally efficient algorithm for the single-link cluster method [J ] . The Computer Journal , 1973 , 16 ( 1 ): 30 - 34 .

KEGL B , KRZYZAK A , LINDER T , et al . Learning and design of principal curves [J ] . IEEE Transactions on Pattern Analysis and Machine Intelligence , 2000 , 22 ( 3 ): 281 - 297 .

WANG T , MAO J L , JIN C Q . HyMU: A hybrid map updating framework [C ] // International Conference on Database Systems for Advanced Applications . Cham : Springer , 2017 : 19 - 33 .

LEE J G , HAN J W , WHANG K Y . Trajectory clustering: A partition-and-group framework [C ] // Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data . New York : ACM , 2007 : 593 - 604 .

CHAO P F , HUA W , ZHOU X F . Trajectories know where map is wrong: An iterative framework for map-trajectory co-optimisation [J ] . World Wide Web , 2020 , 23 ( 1 ): 47 - 73 .

ZHU Z , REN H M , RUAN S J , et al . ICFinder: A ubiquitous approach to detecting illegal hazardous chemical facilities with truck trajectories [C ] // Proceedings of the 29th International Conference on Advances in Geographic Information Systems . New York : ACM , 2021 : 37 - 40 .

ASHBROOK D , STARNER T . Learning significant locations and predicting user movement with GPS [C ] // Proceedings of Sixth International Symposium on Wearable Computers . Piscataway : IEEE , 2003 : 101 - 108 .

ESTER M , KRIEGEL H P , SANDER J , et al . A density-based algorithm for discovering clusters in large spatial databases with noise [C ] // Proceedings of the Second International Conference on Knowledge Discovery and Data Mining . New York : AAAI Press , 1996 : 226 - 231 .

ANKERST M , BREUNIG M M , KRIEGEL H P , et al . Optics: Ordering points to identify the clustering structure [C ] // Proceedings of the 1999 ACM SIGMOD International Conference on Management of Data . New York : ACM , 1999 : 49 - 60 .

ASSAM R , SEIDL T . Context-based location clustering and prediction using conditional random fields [C ] // Proceedings of the 13th International Conference on Mobile and Ubiquitous Multimedia . New York : ACM , 2014 : 1 - 10 .

ZHENG Y , ZHANG L Z , XIE X , et al . Mining interesting locations and travel sequences from GPS trajectories [C ] // Proceedings of the 18th International Conference on World Wide Web . New York : ACM , 2009 : 791 - 800 .

HU Y J , GAO S , JANOWICZ K , et al . Extracting and understanding urban areas of interest using geotagged photos [J ] . Computers, Environment and Urban Systems , 2015 , 54 : 240 - 254 .

DOYTSHER Y , GALON B , KANZA Y . Emotion maps based on geotagged posts in the social media [C ] // Proceedings of the 1st ACM SIGSPATIAL Workshop on Geospatial Humanities . New York : ACM , 2017 : 39 - 46 .

ZHENG V W , ZHENG Y , XIE X , et al . Collaborative location and activity recommendations with GPS history data [C ] // Proceedings of the 19th International Conference on World Wide Web . New York : ACM , 2010 : 1029 - 1038 .

Jr WARD J H . Hierarchical grouping to optimize an objective function [J ] . Journal of the American Statistical Association , 1963 , 58 ( 301 ): 236 - 244 .

RODRIGUES J G P , AGUIAR A . Extracting 3D maps from crowdsourced GNSS skyview data [C ] // MobiCom'19: The 25th Annual International Conference on Mobile Computing and Networking . New York : ACM , 2019 : 1 - 15 .

VAN WINDEN K . Automatically Deriving and Updating Attribute Road Data from Movement Trajectories [D ] . Mekelweg : Technische Universiteit Delft , 2014 .

ZHANG L J , THIEMANN F , SESTER M . Integration of GPS traces with road map [C ] // Proceedings of the Third International Workshop on Computational Transportation Science . New York : ACM , 2010 : 17 - 22 .

CHEN Y H , KRUMM J . Probabilistic modeling of traffic lanes from GPS traces [C ] // Proceedings of the 18th SIGSpatial International Conference on Advances in Geographic Information Systems . New York : ACM , 2010 : 81 - 88 .

DING Y , ZHENG J C , TAN H Y , et al . Inferring Road type in crowdsourced map services [C ] // International Conference on Database Systems for Advanced Applications . Cham : Springer , 2014 : 392 - 406 .

QIN H L , ZHAN X Y , LI Y X , et al . Network-wide traffic states imputation using self-interested coalitional learning [C ] // Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining . New York : ACM , 2021 : 1370 - 1378 .

SHANG J B , ZHENG Y , TONG W Z , et al . Inferring gas consumption and pollution emission of vehicles throughout a city [C ] // Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . New York : ACM , 2014 : 1027 - 1036 .

HE S T , SADEGHI M A , CHAWLA S , et al . Inferring high-resolution traffic accident risk maps based on satellite imagery and GPS trajectories [C ] // 2021 IEEE/CVF International Conference on Computer Vision (ICCV) . Piscataway : IEEE , 2022 : 11957 - 11965 .

WANG J Y , CHEN C , WU J J , et al . No longer sleeping with a bomb: A duet system for protecting urban safety from dangerous goods [C ] // Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . New York : ACM , 2017 : 1673 - 1681 .

PAN G , QI G D , WU Z H , et al . Land-use classification using taxi GPS traces [J ] . IEEE Transactions on Intelligent Transportation Systems , 2013 , 14 ( 1 ): 113 - 123 .

ZHU Y , NEWSAM S . Spatio-temporal sentiment hotspot detection using geotagged photos [C ] // Proceedings of the 24th ACM SIGSpatial International Conference on Advances in Geographic Information Systems . New York : ACM , 2016 : 1 - 4 .

PEDERSEN K F , TORP K . Geolocating traffic signs using crowd-sourced imagery [C ] // Proceedings of the 28th International Conference on Advances in Geographic Information Systems . New York : ACM , 2020 : 199 - 202 .

张国龙 . 高精定位与高精地图众包更新现状、挑战 [EB/OL ] . ( 2021-10-01 ) [ 2022-08-08 ] . https://www.163.com/dy/article/GL7IU5F805278R4J.html https://www.163.com/dy/article/GL7IU5F805278R4J.html .

ZHANG G L . High precision positioning and crowd-sourcing high precision maps updates: Current status and challenges [EB/OL ] . ( 2021-10-01 ) [ 2022-08-08 ] . https://www.163.com/dy/article/GL7IU5F805278R4J.html. https://www.163.com/dy/article/GL7IU5F805278R4J.html. (in Chinese)

李勤 . 中海庭CTO罗跃军谈高精地图: 众包更新是必须,未来 2 - 3 年会落地[EB/OL ] . ( 2021-04-25 ) [ 2022-08-08 ] . https://auto-time.36kr.com/p/1196970721626626 https://auto-time.36kr.com/p/1196970721626626 .

LI Q . CTO of zhonghaiting, talks about high precision map: Crowd-sourcing is a must, which would be in real use in the next 2 - 3 years[EB/OL ] . ( 2021-04-25 ) [ 2022-08-08 ] . https://auto-time.36kr.com/p/1196970721626626. https://auto-time.36kr.com/p/1196970721626626. (in Chinese)

JIANG H B , LI J , ZHAO P , et al . Location privacy-preserving mechanisms in location-based services: A comprehensive survey [J ] . ACM Computing Surveys , 2021 , 54 ( 1 ): 1 - 36 .

WANG H Z , WANG E , YANG Y J , et al . Privacy-preserving online task assignment in spatial crowdsourcing: A graph-based approach [C ] // IEEE INFOCOM 2022 - IEEE Conference on Computer Communications . Piscataway : IEEE , 2022 : 570 - 579 .

CHEN X , WU X P , LI X Y , et al . Privacy-preserving high-quality map generation with participatory sensing [C ] // IEEE INFOCOM 2014 - IEEE Conference on Computer Communications . Piscataway : IEEE , 2014 : 2310 - 2318 .

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据