scholarly journals Spatial Autoregressive Model for Estimation of Visitors’ Dynamic Agglomeration Patterns Near Event Location

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4577
Author(s):  
Takumi Ban ◽  
Tomotaka Usui ◽  
Toshiyuki Yamamoto
Keyword(s):  
Goodness Of Fit ◽  
Rapid Development ◽  
Population Data ◽  
Location Data ◽  
Endogenous Variables ◽  
Event Location ◽  
Spatial Autoregressive ◽  
Spatial Autoregressive Models ◽  
Dynamic Population ◽  
Crowd Formation

The rapid development of ubiquitous mobile computing has enabled the collection of new types of massive traffic data to understand collective movement patterns in social spaces. Contributing to the understanding of crowd formation and dispersal in populated areas, we developed a model of visitors’ dynamic agglomeration patterns at a particular event using dynamic population data. This information, a type of big data, comprised aggregate Global Positioning System (GPS) location data automatically collected from mobile phones without users’ intervention over a grid with a spatial resolution of 250 m. Herein, spatial autoregressive models with two-step adjacency matrices are proposed to represent visitors’ movement between grids around the event site. We confirmed that the proposed models had a higher goodness-of-fit than those without spatial or temporal autocorrelations. The results also show a significant reduction in accuracy when applied to prediction with estimated values of the endogenous variables of prior time periods.

scholarly journals Exploring Impact of Surrounding Service Facilities on Urban Vibrancy Using Tencent Location-Aware Data: A Case of Guangzhou

2021 ◽  
Vol 13 (2) ◽  
pp. 444
Author(s):  
Xucai Zhang ◽  
Yeran Sun ◽  
Ting On Chan ◽  
Ying Huang ◽  
Anyao Zheng ◽  
...  
Keyword(s):  
Rapid Development ◽  
Ordinary Least Squares ◽  
Information And Communications Technology ◽  
Time Data ◽  
Location Data ◽  
Point Of Interest ◽  
Quality Life ◽  
City Construction ◽  
The Impact ◽  
The City

Urban vibrancy contributes towards a successful city and high-quality life for people as one of its vital elements. Therefore, the association between service facilities and vibrancy is crucial for urban managers to understand and improve city construction. Moreover, the rapid development of information and communications technology (ICT) allows researchers to easily and quickly collect a large volume of real-time data generated by people in daily life. In this study, against the background of emerging multi-source big data, we utilized Tencent location data as a proxy for 24-h vibrancy and adopted point-of-interest (POI) data to represent service facilities. An analysis framework integrated with ordinary least squares (OLS) and geographically and temporally weighted regression (GTWR) models is proposed to explore the spatiotemporal relationships between urban vibrancy and POI-based variables. Empirical results show that (1) spatiotemporal variations exist in the impact of service facilities on urban vibrancy across Guangzhou, China; and (2) GTWR models exhibit a higher degree of explanatory capacity on vibrancy than the OLS models. In addition, our results can assist urban planners to understand spatiotemporal patterns of urban vibrancy in a refined resolution, and to optimize the resource allocation and functional configuration of the city.

scholarly journals Variable Selection for the Spatial Autoregressive Model with Autoregressive Disturbances

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1448
Author(s):  
Xuan Liu ◽  
Jianbao Chen
Keyword(s):  
Variable Selection ◽  
Autoregressive Model ◽  
Rapid Development ◽  
Heterogeneous Data ◽  
Spatial Effect ◽  
Spatial Effects ◽  
Spatial Autoregressive Model ◽  
Monte Carlo Studies ◽  
Spatial Autoregressive ◽  
Theoretical Results

Along with the rapid development of the geographic information system, high-dimensional spatial heterogeneous data has emerged bringing theoretical and computational challenges to statistical modeling and analysis. As a result, effective dimensionality reduction and spatial effect recognition has become very important. This paper focuses on variable selection in the spatial autoregressive model with autoregressive disturbances (SARAR) which contains a more comprehensive spatial effect. The variable selection procedure is presented by using the so-called penalized quasi-likelihood approach. Under suitable regular conditions, we obtain the rate of convergence and the asymptotic normality of the estimators. The theoretical results ensure that the proposed method can effectively identify spatial effects of dependent variables, find spatial heterogeneity in error terms, reduce the dimension, and estimate unknown parameters simultaneously. Based on step-by-step transformation, a feasible iterative algorithm is developed to realize spatial effect identification, variable selection, and parameter estimation. In the setting of finite samples, Monte Carlo studies and real data analysis demonstrate that the proposed penalized method performs well and is consistent with the theoretical results.

Examining the Association Between Massage Parlors and Neighborhood Crime

2018 ◽  
Vol 65 (11) ◽  
pp. 1537-1569 ◽  
Author(s):  
Jessica Huff ◽  
Danielle Wallace ◽  
Courtney Riggs ◽  
Charles M. Katz ◽  
David Choate
Keyword(s):  
Management System ◽  
Autoregressive Models ◽  
Physical Disorder ◽  
Record Management ◽  
Social Disorder ◽  
Neighborhood Crime ◽  
Spatial Autoregressive ◽  
Spatial Autoregressive Models ◽  
The Impact ◽  
User Review

Although massage parlors have been associated with illicit activities including prostitution, less is known about their association with neighborhood crime. Employing the Computer Automated Dispatch/Record Management System (CAD/RMS), online user review, licensing, Census, and zoning data, we examine the impact of massage parlors on crime in their surrounding neighborhoods. Using spatial autoregressive models, our results indicate the total number of massage parlors was associated with increased social disorder. The presence of illicit massage parlors in adjacent neighborhoods was associated with crime and physical disorder in the focal neighborhoods. This study has consequences for how police address crime associated with massage parlors. Specifically, the use of online user review forums could be an effective way to identify illicit massage parlors. Recommendations for policing and code enforcement are discussed.

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