scholarly journals Examining Hotspots of Traffic Collisions and their Spatial Relationships with Land Use: A GIS-Based Geographically Weighted Regression Approach for Dammam, Saudi Arabia

2020 ◽  
Vol 9 (9) ◽  
pp. 540 ◽  
Author(s):  
Muhammad Tauhidur Rahman ◽  
Arshad Jamal ◽  
Hassan M. Al-Ahmadi
Keyword(s):  
Land Use ◽  
Saudi Arabia ◽  
Traffic Safety ◽  
Geographically Weighted Regression ◽  
Significant Proportion ◽  
Urban Land Use ◽  
Weighted Regression ◽  
Spatial Relationships ◽  
Population Densities ◽  
Crash Types

Examining the relationships between vehicle crash patterns and urban land use is fundamental to improving crash predictions, creating guidance, and comprehensive policy recommendations to avoid crash occurrences and mitigate their severities. In the existing literature, statistical models are frequently used to quantify the association between crash outcomes and available explanatory variables. However, they are unable to capture the latent spatial heterogeneity accurately. Further, the vast majority of previous studies have focused on detailed spatial analysis of crashes from an aggregated viewpoint without considering the attributes of the built environment and land use. This study first uses geographic information systems (GIS) to examine crash hotspots based on two severity groups, seven prevailing crash causes, and three predominant crash types in the City of Dammam, Kingdom of Saudi Arabia (KSA). GIS-based geographically weighted regression (GWR) analysis technique was then utilized to uncover the spatial relationships of traffic collisions with population densities and relate it to the land use of each neighborhood. Results showed that Fatal and Injury (FI) crashes were mostly located in residential neighborhoods and near public facilities having low to medium population densities on highways with relatively higher speed limits. Distribution of hotspots and GWR-based analysis for crash causes showed that crashes due to “sudden lane deviation” accounted for the highest proportion of crashes that were concentrated mainly in the Central Business District (CBD) of the study area. Similarly, hotspots and GWR analysis for crash types revealed that “collisions between motor vehicles” constitute a significant proportion of the total crashes, with epicenters mostly stationed in high-density residential neighborhoods. The outcomes of this study could provide analysts and practitioners with crucial insights to understand the complex inter-relationships between traffic safety and land use. It can provide useful guidance to policymakers for better planning and effective management strategies to enhance safety at zonal levels.

scholarly journals Determination of the Peak Hour Ridership of Metro Stations in Xi’an, China Using Geographically-Weighted Regression

2020 ◽  
Vol 12 (6) ◽  
pp. 2255 ◽  
Author(s):  
Lijie Yu ◽  
Yarong Cong ◽  
Kuanmin Chen
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Geographically Weighted Regression ◽  
Urban Land Use ◽  
Weighted Regression ◽  
Metro Station ◽  
Geographically Weighted Regression Model ◽  
Extra Peak ◽  
Deviation Coefficient

The ridership of a metro station during a city’s peak hour is not always the same as that during the station’s own peak hour. To investigate this inconsistency, this study introduces the peak deviation coefficient to describe this phenomenon. Data from 88 metro stations in Xi’an, China, are used to analyze the peak deviation coefficient based on the geographically weighted regression model. The results demonstrate that when the land around a metro station is mainly land for work, primary and middle schools, and residences, its station’s peak hour is consistent with the city’s peak hour. Additionally, the station’s peak hour is more likely to deviate from the city’s peak hour for suburban stations. There are two ridership options when designing stations, namely the extra peak hour ridership during a city’s peak hour and that during a station’s peak hour, and the larger of the two is used to design metro stations. The mixed land use ratio must be considered in urban land use planning, because although non-commuting land can mitigate the traffic pressure of a city’s peak hour, it may cause the deviation of the station’s peak hours from that of the city.

scholarly journals Understanding City-Wide Ride-Sourcing Travel Flow: A Geographically Weighted Regression Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Chuqiao Chen ◽  
Simon Hu ◽  
Washington Y. Ochieng ◽  
Na Xie ◽  
Xiqun (Michael) Chen
Keyword(s):  
Land Use ◽  
Geographically Weighted Regression ◽  
Transportation Planning ◽  
Goodness Of Fit ◽  
Urban Land ◽  
Residential Area ◽  
Urban Land Use ◽  
Weighted Regression ◽  
Bus Station ◽  
The Impact

The emerging ride-sourcing service has become an important element of urban mobility. A challenging question underlying the provision of such service is how and to what extent the built environment affects origin-destination (OD) travel flows. This paper employs the geographically weighted regression (GWR) model to analyze the OD-based ride-sourcing travel flow. It makes a comparison with the existing ordinary least square (OLS) model and spatial autocorrelation model (SAM). We have collected ride-sourcing order data in Hangzhou, China, to provide an accurate source for acquiring ride-sourcing travel flow. We investigate the effects of the residential area, points of interest (POIs), and transit stations on ride-sourcing travel flow among traffic analysis zones (TAZs). The results show the following: (a) GWR has better goodness-of-fit than SAM and OLS. (b) Residential area, enterprise, and bus stations have positive correlations with ride-sourcing OD flows, but education and subway stations have negative correlations. We have further investigated the issue and found that it is not a causal relationship between the bus station and OD flow, due to collinearity between the two variables. The bus station builds on locations with high demand, but its capacity is not large enough to reduce the ride-sourcing flow to a low level, which results in a positive coefficient. (c) Based on the estimated coefficients, the prediction of ride-sourcing flows is feasible, supporting the impact analysis for urban land use and transportation planning. This paper contributes to understanding OD-based ride-sourcing travel flow distributions and provides a framework of long-term OD flow prediction for urban land use and transportation planning.

scholarly journals Eastern Grey Kangaroo (Macropus giganteus) Vigilance Behaviour Varies between Human-Modified and Natural Environments

Animals ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 494
Author(s):  
Georgina Hume ◽  
Elizabeth Brunton ◽  
Scott Burnett
Keyword(s):  
Land Use ◽  
Human Population ◽  
Urban Environments ◽  
Urban Land Use ◽  
Urban Landscapes ◽  
Large Mammals ◽  
Population Densities ◽  
Vigilance Behaviour ◽  
Landscape Level ◽  
Behavioural Adaptations

Rapid increases in urban land use extent across the globe are creating challenges for many wildlife species. Urban landscapes present a novel environment for many species, yet our understanding of wildlife behavioural adaptations to urban environments is still poor. This study compared the vigilance behaviour of a large mammal in response to urbanisation at a landscape level. Here, we investigate urban (n = 12) and non-urban (n = 12) populations of kangaroos in two regions of Australia, and the relationship between kangaroo vigilance and urbanisation. We used a linear modelling approach to determine whether anti-predator vigilance and the number of vigilant acts performed were influenced by land use type (i.e., urban or non-urban), human population densities, kangaroo demographics, and environmental factors. Kangaroo behaviour differed between the two study regions; kangaroo vigilance was higher in urban than non-urban sites in the southern region, which also had the highest human population densities, however no effect of land use was found in the northern region. Season and sex influenced the vigilance levels across both regions, with higher levels seen in winter and female kangaroos. This study is the first to compare urban and non-urban vigilance of large mammals at a landscape level and provide novel insights into behavioural adaptations of large mammals to urban environments.

scholarly journals Exploring the Spatial Variation of the Relationship between Land Use and Water Quality in a Drainage Basin Using Geographically Weighted Regression

2020 ◽  
Vol 12 (2) ◽  
pp. 147-168
Author(s):  
Samuel Azua ◽  
Taiye Oluwafemi Adewuyi ◽  
Lazarus Mustapha Ojigi ◽  
Omafuvwe Joseph Mudiare
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Geographically Weighted Regression ◽  
Drainage Basin ◽  
Water Quality Management ◽  
Mixed Forest ◽  
Weighted Regression ◽  
Landsat 8 ◽  
Sample Points ◽  
The Relationship

The focus of this study is to determine the relationship between land use and water quality in the River Mu drainage basin for effective water quality management. Various land uses in the study area were identified and mapped using Landsat 8 OLI of 2016. Water samples were also collected from 112 sample sites using Stratified Random Sampling methods. The samples were analysed in terms of physicochemical parameters using standard methods. The results of land use and water quality parameters were regressed using Geographically Weighted Regression (GWR) to determine whether there exist spatially varying relationships. The results revealed that the local R2 values varied between 0.0 and 0.5, indicating a weak relationship between land use and water pollution, except for mixed forest and pH which recorded local R2 values of 0.7 towards the western region of the study area. This shows that the relationship between the two variables varied spatially across the drainage basin. The one-sample Kolmogorov Smirmov test-p<0.05 revealed that there were significant differences in pH (0.00), EC (0.00), turbidity (0.001), TDS (0.048), DO (0.003), NH4+ (0.002), Ca2+ (0.00), Cl- (0.036), Fe3+ (0.00) and Cr2+ (0.039) across the different sample points, whereas K+ (0.134), PO43- (0.715) and NO3- (0.501) were not significantly different across the different sample points. The study recommended that the procedure for water management be localized to sub-catchment and basin levels, to provide adequate attention to each sub-catchment depending on the level and nature of pollution identified.

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