Volume 26, Issue 1 (2022)
MJSP 2022, 26(1): 63-88 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Aghayari Hir M, Zaheri M, Rahimzadeh N. Spatial Modeling of Rural Travel Flow and Analysis of Factors Affecting Travel Demand Case Study: (Villages of Tabriz County). MJSP 2022; 26 (1) :63-88
URL: http://hsmsp.modares.ac.ir/article-21-56687-en.html
URL: http://hsmsp.modares.ac.ir/article-21-56687-en.html
1- Faculty Member of the Department of Geography and Rural Planning, University of Tabriz , aghayarihir@gmail.com
2- Associate Professor of Geography and Rural Planning, Faculty of Geography and Environmental Planning, University of Tabriz
3- Ph. D. student in Geography and Rural Planning, University of Tabriz
2- Associate Professor of Geography and Rural Planning, Faculty of Geography and Environmental Planning, University of Tabriz
3- Ph. D. student in Geography and Rural Planning, University of Tabriz
Abstract: (2122 Views)
Introduction
Lack of essential services increases the need for mobility and relocation in rural areas and makes people travel to meet their needs. The need for mobility along with the absence of public transportation services, while prolonging travels, has affected travel demand and flow, so that people use several vehicles in a travel chain (origin-destination) (Stfen and Hunt, 2006: 104). Various spatial factors affect the flow, destination and volume of trips, which can be shown by spatial analysis and modeling as one typical method to do this. Spatial statistics tools include a set of techniques and methods for describing and modeling spatial data. Use of spatial statistics helps us to increase the accuracy of results and observations in cases where the distribution or dispersion of data in space is complicated. In this paper, geographically-weighted regression and spatial modeling have been used to show the volume and travel flow in villages, and also the factors affecting them to determine, besides the origin and destination of rural travels, travel volume and their spatial distribution. The question is what factors are influential in the destination of these trips and their volume, and to what extent is the impact of each of these factors on the frequency of rural travel demands.
Methodology
The present article is a descriptive-analytical method with a practical purpose and the data is collected both in the field and from the existing documents. In the documentary section, some data were collected from 1390 and 1395 censuses and some other using questionnaires. The statistical population of the study were all rural households in Tabriz County, where a researcher-made questionnaire was used to obtain travel information. Since the number of households amounted to 33379 families, using the Cochran formula 320 sample sizes were selected and questionnaires were randomly distributed between rural households. Given that the primary purpose of this study is to model the spatial pattern of passenger flow in space and time, so that the spatio-temporal mobility of passengers in the road network can be seen, three components including the extraction of passenger travel pattern (Origin-destination), determination of the travel routes, and the factors affecting these trips were identified. In the first step, the data obtained from the questionnaire were processed to model and plot the travel pattern (origin-destination of trips). For this purpose, it was necessary to identify the villages with and without bus stations and public transportation servicesas well as the travel routes of passengers. The next step is modeling the travel patterns and flow of passengers. In this study, ArcGIS software was used to show the flow of travel. This mapshows the direction of movement and the volume of the flow adjusted by line widths. Using the simulated travel routes, a flow matrix was obtained from the travel volume among all villages, small towns, and Tabriz city. Then, to investigate the dominant pattern of the travel demand, spatial autocorrelation analysis (local Moran pattern) and hot spots were used to determine the pattern of space travel distribution. Finally, in order to reveal the most influential factor affecting travel demand as the independent variable, a geographically-weighted regression model was formed and the relationship between travel and such indicators as demographic, economic, and social factors were analyzed and modeled.
Results and discussion
Initially, the data collected from the villages were entered into the ArcGIS software to obtain the origins and destinations of the passengers, their travel directions, and the way their travels were distributed. Then, using Spatial analyst tools, the direction and spatial distribution of trips were obtained by a straight line as an Origion-Destination matrix for short-term trips to Tabriz city. The results showed that many trips were made outside the countryside to the city of Tabriz, and some of these trips were made to large villages and small towns. According to the data extracted from the questionnaire, many of these trips are made by car or taxi because many of these villages are on the roads where public transport does not pass through.
Hot spot analysis has been used to identify villages with high travel rates. The results obtained from the analysis of hot spots indicate that the main places of travels are mostly in the villages of Maidan Chai and Aji-Chay, which seems to be due to the access to public transportation services and the existence of villages with buses to Tabriz city in these rural areas. In the next step, in order to model and explain the effect of research variables on travel demand, GWR was used in GIS. According to the results of the analysis, the parameters of R2 and adjusted R2 are 0.8 and 0.75, respectively. This means that based on a geographically-weighted regression, the indicators considered at the 0.95 confidence level explain 0.80 of the trips and have acceptable accuracy in modeling the spatial relationships of the factors affecting the travel demands of individuals. In addition, the AICc value indicates a lower number, indicating a better fit of the observed data. Due to the different nature of the indicators, the effect of each of the indicators and factors on the amount of travels was investigated separately. The results show that the highest amount of R2 with a value of 0.72 is related to the access to the public transport, followed by the number of workers outside the village with a value of 0.70. Among these, the least influential factor is the total travel time to reach the destination with a value of 0.21, which indicates that people travel to access services and meet their needs regardless of the total time to reach their destinations.
Conclusion
The results of the study showed that several factors have affected the heterogeneity of travel demands in rural areas, which, according to the study, access to the public transport and people working outside the village have the most impact. In addition, most of daily trips to the city of Tabriz are done for business and by personal cars. These trips are based on hot spot analysis in Maidan Chai and Ajichay villages, where most of the villages near the city of Tabriz have access to the public transport (bus) and taxi. The short distance between these villages and the city of Tabriz, the existence of public transportation services in them, and consequently lower costs and ease of movement have caused the accommodation of the overflow of Tabriz in these villages and have increased the demand for travel in these villages, in such a way that during the day, the movement of travelers in these villages is the same as daily trips in the city of Tabriz, and educational, recreational, shopping, health, etc. trips are made from these villages to the city of Tabriz. In addition, the presence of several industrial towns and factories near the villages of Ajichai and Maidanchai has increased the number of business trips in these villages.
Lack of essential services increases the need for mobility and relocation in rural areas and makes people travel to meet their needs. The need for mobility along with the absence of public transportation services, while prolonging travels, has affected travel demand and flow, so that people use several vehicles in a travel chain (origin-destination) (Stfen and Hunt, 2006: 104). Various spatial factors affect the flow, destination and volume of trips, which can be shown by spatial analysis and modeling as one typical method to do this. Spatial statistics tools include a set of techniques and methods for describing and modeling spatial data. Use of spatial statistics helps us to increase the accuracy of results and observations in cases where the distribution or dispersion of data in space is complicated. In this paper, geographically-weighted regression and spatial modeling have been used to show the volume and travel flow in villages, and also the factors affecting them to determine, besides the origin and destination of rural travels, travel volume and their spatial distribution. The question is what factors are influential in the destination of these trips and their volume, and to what extent is the impact of each of these factors on the frequency of rural travel demands.
Methodology
The present article is a descriptive-analytical method with a practical purpose and the data is collected both in the field and from the existing documents. In the documentary section, some data were collected from 1390 and 1395 censuses and some other using questionnaires. The statistical population of the study were all rural households in Tabriz County, where a researcher-made questionnaire was used to obtain travel information. Since the number of households amounted to 33379 families, using the Cochran formula 320 sample sizes were selected and questionnaires were randomly distributed between rural households. Given that the primary purpose of this study is to model the spatial pattern of passenger flow in space and time, so that the spatio-temporal mobility of passengers in the road network can be seen, three components including the extraction of passenger travel pattern (Origin-destination), determination of the travel routes, and the factors affecting these trips were identified. In the first step, the data obtained from the questionnaire were processed to model and plot the travel pattern (origin-destination of trips). For this purpose, it was necessary to identify the villages with and without bus stations and public transportation servicesas well as the travel routes of passengers. The next step is modeling the travel patterns and flow of passengers. In this study, ArcGIS software was used to show the flow of travel. This mapshows the direction of movement and the volume of the flow adjusted by line widths. Using the simulated travel routes, a flow matrix was obtained from the travel volume among all villages, small towns, and Tabriz city. Then, to investigate the dominant pattern of the travel demand, spatial autocorrelation analysis (local Moran pattern) and hot spots were used to determine the pattern of space travel distribution. Finally, in order to reveal the most influential factor affecting travel demand as the independent variable, a geographically-weighted regression model was formed and the relationship between travel and such indicators as demographic, economic, and social factors were analyzed and modeled.
Results and discussion
Initially, the data collected from the villages were entered into the ArcGIS software to obtain the origins and destinations of the passengers, their travel directions, and the way their travels were distributed. Then, using Spatial analyst tools, the direction and spatial distribution of trips were obtained by a straight line as an Origion-Destination matrix for short-term trips to Tabriz city. The results showed that many trips were made outside the countryside to the city of Tabriz, and some of these trips were made to large villages and small towns. According to the data extracted from the questionnaire, many of these trips are made by car or taxi because many of these villages are on the roads where public transport does not pass through.
Hot spot analysis has been used to identify villages with high travel rates. The results obtained from the analysis of hot spots indicate that the main places of travels are mostly in the villages of Maidan Chai and Aji-Chay, which seems to be due to the access to public transportation services and the existence of villages with buses to Tabriz city in these rural areas. In the next step, in order to model and explain the effect of research variables on travel demand, GWR was used in GIS. According to the results of the analysis, the parameters of R2 and adjusted R2 are 0.8 and 0.75, respectively. This means that based on a geographically-weighted regression, the indicators considered at the 0.95 confidence level explain 0.80 of the trips and have acceptable accuracy in modeling the spatial relationships of the factors affecting the travel demands of individuals. In addition, the AICc value indicates a lower number, indicating a better fit of the observed data. Due to the different nature of the indicators, the effect of each of the indicators and factors on the amount of travels was investigated separately. The results show that the highest amount of R2 with a value of 0.72 is related to the access to the public transport, followed by the number of workers outside the village with a value of 0.70. Among these, the least influential factor is the total travel time to reach the destination with a value of 0.21, which indicates that people travel to access services and meet their needs regardless of the total time to reach their destinations.
Conclusion
The results of the study showed that several factors have affected the heterogeneity of travel demands in rural areas, which, according to the study, access to the public transport and people working outside the village have the most impact. In addition, most of daily trips to the city of Tabriz are done for business and by personal cars. These trips are based on hot spot analysis in Maidan Chai and Ajichay villages, where most of the villages near the city of Tabriz have access to the public transport (bus) and taxi. The short distance between these villages and the city of Tabriz, the existence of public transportation services in them, and consequently lower costs and ease of movement have caused the accommodation of the overflow of Tabriz in these villages and have increased the demand for travel in these villages, in such a way that during the day, the movement of travelers in these villages is the same as daily trips in the city of Tabriz, and educational, recreational, shopping, health, etc. trips are made from these villages to the city of Tabriz. In addition, the presence of several industrial towns and factories near the villages of Ajichai and Maidanchai has increased the number of business trips in these villages.
Article Type: Original Research |
Subject:
rural and tribal planning
Received: 2021/10/26 | Accepted: 2022/04/11 | Published: 2022/05/31
Received: 2021/10/26 | Accepted: 2022/04/11 | Published: 2022/05/31
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |