Research on Population Spatiotemporal Aggregation Characteristics of a Small City: A Case Study on Shehong County Based on Baidu Heat Maps

被引:28
作者
Feng, Deyi [1 ,2 ]
Tu, Lingli [1 ]
Sun, Zhongwei [1 ]
机构
[1] Chongqing Univ, Sch Architecture & Urban Planning, Dept Urban Planning, Chongqing 400030, Peoples R China
[2] Guiyang Urban Planning & Design Inst, Inst Architecture & Planning, Guiyang 550001, Guizhou, Peoples R China
基金
国家重点研发计划;
关键词
spatiotemporal behavior; Baidu heat map; Getis-Ord general G; correlation analysis; small city; LAND-USE; CITIES; PATTERNS;
D O I
10.3390/su11226276
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Baidu heat maps can be used to explore the pattern of individual citizens conducting their activities and their agglomeration effects at the city scale. To investigate the spatiotemporal pattern of population aggregation and its relationship with land parcel attributes in small cities, we collected Baidu heat map data for a weekday and a weekend day in Shehong County and used Getis-Ord general G and the raster overlay methods to analyze population aggregation spatiotemporal characteristics. Chi-squared and Pearson correlation tests were used to analyze the correlation between population aggregation and land parcel attributes against three types of land parcel divisions: land use parcels, road network blocks, and grids. The results showed that, (1) for most hours of the workday, the degree of population aggregation was greater than on the weekend, and the fluctuation magnitude on the workday was higher as well. (2) On the weekday, people clustered and dispersed faster than on the weekend. (3) On the weekday and weekend, the spatial position of people aggregation was highly overlapping. (4) The correlation between the degree of population aggregation and the type of parcel was not significant. (5) Regarding different parcel unit sizes, the correlations between population aggregation degree and point of interest (POI) density, floor area ratio, and building density were significant and positively correlated, and the correlation coefficients increased as the grid size increased.
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页数:19
相关论文
共 49 条
[1]   Seasonal tourism spaces in Estonia:: Case study with mobile positioning data [J].
Ahas, Rein ;
Aasa, Anto ;
Mark, Ular ;
Pae, Taavi ;
Kull, Ain .
TOURISM MANAGEMENT, 2007, 28 (03) :898-910
[2]   Daily rhythms of suburban commuters' movements in the Tallinn metropolitan area: Case study with mobile positioning data [J].
Ahas, Rein ;
Aasa, Anto ;
Silm, Siiri ;
Tiru, Margus .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2010, 18 (01) :45-54
[3]   Development and Urban Sustainability: An Analysis of Efficiency Using Data Envelopment Analysis [J].
Alfonso Pina, William H. ;
Pardo Martinez, Clara Ines .
SUSTAINABILITY, 2016, 8 (02)
[4]  
[Anonymous], TECHNOMETRICS
[5]  
[Anonymous], 2018, SUSTAINABILITY BASEL, DOI DOI 10.3390/SU10124732
[6]   THE USE OF CATEGORICAL VARIABLES IN DATA ENVELOPMENT ANALYSIS [J].
BANKER, RD ;
MOREY, RC .
MANAGEMENT SCIENCE, 1986, 32 (12) :1613-1627
[7]   Understanding individual mobility patterns from urban sensing data: A mobile phone trace example [J].
Calabrese, Francesco ;
Diao, Mi ;
Di Lorenzo, Giusy ;
Ferreira, Joseph, Jr. ;
Ratti, Carlo .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2013, 26 :301-313
[8]   Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome [J].
Calabrese, Francesco ;
Colonna, Massimo ;
Lovisolo, Piero ;
Parata, Dario ;
Ratti, Carlo .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2011, 12 (01) :141-151
[9]   Pedestrian Density Analysis in Public Scenes With Spatiotemporal Tensor Features [J].
Chen, Ke ;
Kamarainen, Joni-Kristian .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 17 (07) :1968-1977
[10]  
Deu-Pons Jordi, 2014, Bioinformatics, V30, P1757, DOI 10.1093/bioinformatics/btu094