摘要
浮动车轨迹数据可用于居民出行热点研究,本文利用海口市“滴滴出行”轨迹数据,基于核密度估计法识别居民出行热点,结合复杂网络理论建立热点区域空间交互网络,挖掘居民出行潜在规律。研究发现:核心区域存在持续型热点,与休息日相比,工作日热点分散分布且热度值更高;工作日热点交互强度明显大于休息日,且强度较高的热点存在局部抱团现象。上述结论可为改善城市居民出行体验和城市交通拥堵状况等提供参考。
Floating car trajectory data can be used to study the hotspots of residents’travel.This article uses the trajectory data of“Didi Travel”in Haikou City to identify residents’travel hotspots based on the kernel density estimation method.Combined with complex network theory,a spatial interactive network of hotspot areas is established to explore the potential laws of residents’travel.It is found that there are persistent hotspots in the core area.Compared with rest days,hotspots on weekdays are scattered and have higher heat values;hotspot interaction intensity on weekdays is significantly greater than that on rest days,and there is a local clustering phenomenon in hotspots with higher intensity.The above conclusions can provide reference for improving the travel experience of urban residents and urban traffic congestion.
作者
彭定永
兰小机
温振威
PENG Dingyong;LAN Xiaoji;WEN Zhenwei(School of Civil and Surveying and Mapping Engineering,Jiangxi University of Science and Technology,Ganzhou 341000,China)
出处
《江西测绘》
2022年第1期41-44,共4页
JIANGXI CEHUI
基金
国家自然科学基金项目(41561085,40971234)
关键词
轨迹数据
核密度估计
居民出行热点
复杂网络
空间交互网络
Trajectory Data
Kernel Density Estimation
Resident Travel Hotspots
Complex Network
Spatial Interaction Network
