Geospatial data combined with multi-source data such as mobile phone signaling data to depict the travel characteristics of city residents

doi:10.13474/j.cnki.11-2246.2022.0159

Abstract

Abstract: The paper proposes ways to depict the travel characteristics of city residents combined with multi-source data such as mobile phone signaling and POI.Firstly,binds signaling data to geographical information blocks and identifies the basic job, housing and entertainment information of residents according to time characteristics and social attributes of geographical data. Then,mix POI people's livelihood interest, travel characteristics development keywords such as multiple source data, uses weekday commuting analysis model and holiday travel characteristics extraction model to identify the user's commuting distance, commuting, daily commuting frequency, weekly working hours, holiday travel scene, travel frequency, residence time, and form entertainment information travel characteristics label set. Taking Chengdu as an example, collects a month of mobile phone signaling data and POI data in the same period to verify the feasibility of the method. The results reflect the actual urban population size and spatial distribution characteristics of urban population map of big data products and provide support for government departments, commercial enterprise users to carry out relevant analysis business.

Key words: geographical data, mobile phone signaling data, travel characteristics of city residents, commuting analysis

CLC Number:

P208

WANG Meihong, HOU Xiaoyu, SI Lianfa, HE Feng. Geospatial data combined with multi-source data such as mobile phone signaling data to depict the travel characteristics of city residents[J]. Bulletin of Surveying and Mapping, 2022, 0(5): 162-165.

References

[1] 代维秀,陈占龙,谢鹏.居民出行与轨迹行为交互模式挖掘与关联技术[J].测绘学报, 2021, 50(4):532-543.
[2] 晋泽倩,陈艳艳,李臣.城市企事业人群出行链提取及出行特征分析[J].科学技术与工程, 2022, 22(6):2531-2538.
[3] 孙铁山,王兰兰,李国平.北京都市区人口-就业分布与空间结构演化[J].地理学报, 2012, 67(6):829-840.
[4] 胡明伟.居民出行调查数据的统计分析方法[J].统计与决策, 2009(6):170-171.
[5] 李吉墉,周春山,杨高.珠海外来人口分布的时空演变特征研究[J].城市学刊, 2018, 39(4):38-42.
[6] 龚丽丽,蔡忠亮,李伯钊,等.街道尺度下城市居民出行特征分析[J/OL].测绘地理信息.[2022-03-24].DOI:10.14188/j.2095-6045.2021062.
[7] 屈树学,董琪,秦嘉徽,等.基于社交媒体数据的北京市游客与居民签到差异研究[J].地理与地理信息科学, 2022, 38(1):37-44.
[8] 刘丽敏,虞虎,靳海涛.基于公交刷卡数据的北京城市居民周末户外休闲行为特征研究[J].地域研究与开发, 2018, 37(6):52-57.
[9] 李祖芬,于雷,高永,等.基于手机信令定位数据的居民出行时空分布特征提取方法[J].交通运输研究, 2016, 2(1):51-57.
[10] 钮心毅,丁亮,宋小冬.基于手机数据识别上海中心城的城市空间结构[J].城市规划学刊, 2014(6):61-67.
[11] 海晓东,刘云舒,赵鹏军,等.基于手机信令数据的特大城市人口时空分布及其社会经济属性估测:以北京市为例[J].北京大学学报(自然科学版), 2020, 56(3):518-530.
[12] 杨振山,苏锦华,杨航,等.基于多源数据的城市功能区精细化研究:以北京为例[J].地理研究, 2021, 40(2):477-494.
[13] 苏跃江,温惠英,韦清波,等.多源数据融合驱动的居民出行特征分析方法[J].交通运输系统工程与信息, 2020, 20(5):56-63.
[14] 侯笑宇,司连法,王梅红,等.结合手机信令数据和地理空间数据的居民职住信息识别[J].测绘通报, 2019(5):139-142.