scholarly journals Developing Non-Negative Spatial Autoregressive Models for Better Exploring Relation Between Nighttime Light Images and Land Use Types

2020 ◽  
Vol 12 (5) ◽  
pp. 798
Author(s):  
Honghan Zheng ◽  
Zhipeng Gui ◽  
Huayi Wu ◽  
Aihong Song
Keyword(s):  
Land Use ◽  
Spatial Autocorrelation ◽  
Autoregressive Models ◽  
Spatial Error ◽  
Land Use Types ◽  
Central Pixel ◽  
Nighttime Light ◽  
Spatial Autoregressive ◽  
Spatial Autoregressive Models ◽  
The Relationship

Exploring the relationship between nighttime light and land use is of great significance to understanding human nighttime activities and studying socioeconomic phenomena. Models have been studied to explain the relationships, but the existing studies seldom consider the spatial autocorrelation of night light data, which leads to large regression residuals and an inaccurate regression correlation between night light and land use. In this paper, two non-negative spatial autoregressive models are proposed for the spatial lag model and spatial error model, respectively, which use a spatial adjacency matrix to calculate the spatial autocorrelation effect of light in adjacent pixels on the central pixel. The application scenarios of the two models were analyzed, and the contribution of various land use types to nighttime light in different study areas are further discussed. Experiments in Berlin, Massachusetts and Shenzhen showed that the proposed methods have better correlations with the reference data compared with the non-negative least-squares method, better reflecting the luminous situation of different land use types at night. Furthermore, the proposed model and the obtained relationship between nighttime light and land use types can be utilized for other applications of nighttime light images in the population, GDP and carbon emissions for better exploring the relationship between nighttime remote sensing brightness and socioeconomic activities.

Measuring pedestrian volume by land use mix: Presenting a new entropy-based index by weighting walking generation units

2019 ◽  
Vol 47 (7) ◽  
pp. 1219-1236 ◽  
Author(s):  
Ha Na Im ◽  
Chang Gyu Choi
Keyword(s):  
Land Use ◽  
Urban Studies ◽  
Negative Impact ◽  
Explanatory Power ◽  
Built Environments ◽  
Estimation Model ◽  
Land Use Types ◽  
Land Use Mix ◽  
The Relationship ◽  
The Empirical Analysis

This study proposes an alternative to the conventional entropy-based land use mix index, which is generally used to measure the diversity of land use. Pedestrian volume was selected as the dependent variable as it represents the vitality of districts, which many recent urban studies now consider important. The study investigates an entropy-based weighted land use mix index, which is weighted by different land use types. For the index, different areas are needed to generate a unit of pedestrian volume, whose measure is m2/person/day. The study demonstrates that this alternative is more effective than the existing conventionally used entropy-based land use mix index for explaining pedestrian volume. The research confirms that the conventionally used entropy-based land use mix index can have a positive or negative impact depending on the land use characteristics of the survey points because the conventionally used entropy-based land use mix index has a non-linear relationship with pedestrian volume. By analysing 9727 surveyed locations of pedestrian volume in Seoul, Korea, the study demonstrates that the weighted land use mix index, rather than the conventionally used entropy-based land use mix index, can improve the explanatory power of the estimation model for the relationship between pedestrian volume and built environments, showing consistent results throughout the empirical analysis. In future built-environment studies, the utility of the weighted land use mix index is expected to improve if studies include how to find the accurate weighting of the land use in estimating the pedestrian volume.

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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