Exploring the distribution of accessibility by public transport using spatial analysis : a case study for retail concentrations and public hospitals in Athens
(2019) In Master Thesis in Geographical Information Science GISM01 20182Dept of Physical Geography and Ecosystem Science
- Abstract
- This thesis studies the distribution of accessibility by public transport to retail concentrations and public hospitals in Athens, using spatial autocorrelation analysis based on Local Indicators of Spatial Autocorrelation (LISA) method and Geographically Weighted Regression (GWR).
For this reason, the study area was divided in a 300x300 meter square grid of points representing the location points of the study. For each point, the travel time to each of the retail concentration and public hospital location was estimated using Google Directions API. The accessibility of each point was then calculated as the percentage of reachable destinations for each land use group within 45 minutes. The results where then aggregated to zip code level,... (More) - This thesis studies the distribution of accessibility by public transport to retail concentrations and public hospitals in Athens, using spatial autocorrelation analysis based on Local Indicators of Spatial Autocorrelation (LISA) method and Geographically Weighted Regression (GWR).
For this reason, the study area was divided in a 300x300 meter square grid of points representing the location points of the study. For each point, the travel time to each of the retail concentration and public hospital location was estimated using Google Directions API. The accessibility of each point was then calculated as the percentage of reachable destinations for each land use group within 45 minutes. The results where then aggregated to zip code level, where along with data regarding the average annual zip code income, population density and destination from Athens’ central business district formed the final dataset.
The analysis that followed suggests that there is a cluster of high accessibility in the city center and a cluster of low accessibility in the outer suburbs. In addition, a middle zone of insignificant clustering is located between the two clusters. The chosen urban structure and socioeconomic variables that were used for the geographically weighted regression have significant effects except for the case of population density on public transport accessibility. More specifically, distance from the central business district (CBD) is found to be negatively correlated with accessibility to both retail concentrations and hospitals. On the other hand, annual average income seems to be positively correlated with accessibility to both destinations. Finally, population density has a positive correlation with only retail concentrations. In addition, the analysis indicated that there may be more unknown factors affecting accessibility to retail concentrations in the city center than the periphery. (Less) - Popular Abstract
- Public transportation is a mode which allows nearly all individuals regardless of age, income or disabilities to carry out their daily activities. Therefore it is very important that public transport enables individuals to access as many as possible alternative destinations. This thesis studies the distribution of accessibility by public transport to retail markets and public hospitals in Athens. In order to achieve this it uses two spatial analysis techniques: Local Indicators of Spatial Autocorrelation (LISA) and Geographically Weighted Regression (GWR).
In order to achieve this, the accessibility to retail markets and public hospital was calculated for each zip code of Athens using Google Maps Directions. Additionally, average annual... (More) - Public transportation is a mode which allows nearly all individuals regardless of age, income or disabilities to carry out their daily activities. Therefore it is very important that public transport enables individuals to access as many as possible alternative destinations. This thesis studies the distribution of accessibility by public transport to retail markets and public hospitals in Athens. In order to achieve this it uses two spatial analysis techniques: Local Indicators of Spatial Autocorrelation (LISA) and Geographically Weighted Regression (GWR).
In order to achieve this, the accessibility to retail markets and public hospital was calculated for each zip code of Athens using Google Maps Directions. Additionally, average annual income, population density and distance from Athens’ center were calculated for each zip code. The application of the first technique (LISA) allowed us to identify areas where accessibility tends to be high or low. The application of the second technique (GWR) gave us insight regarding the relation of accessibility to the other added parameters, which play an important social and urban planning role.
The LISA analysis suggests that there is a cluster of high accessibility in the city center and a cluster of low accessibility in the outer suburbs. In between, there is a zone where accessibility seems to be random. The results of GWR suggest that there is a negative relation between accessibility and distance from Athens’ center for both retail markets and public hospitals. On the other hand, annual average income seems to be positively related with accessibility to both destinations. Finally, population density has a positive relation with only retail markets. In addition, the analysis indicated that there may be more unknown factors affecting accessibility to retail markets in the city center than the periphery. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8975012
- author
- Vafeiadis, Evangelos LU
- supervisor
- organization
- course
- GISM01 20182
- year
- 2019
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- geography, GIS, spatial analysis, geographic weighted regression, spatial clustering, local indicators of spatial association, public transport, accessibility
- publication/series
- Master Thesis in Geographical Information Science
- report number
- 101
- language
- English
- id
- 8975012
- date added to LUP
- 2019-05-09 16:22:38
- date last changed
- 2019-05-09 16:22:38
@misc{8975012,
abstract = {{This thesis studies the distribution of accessibility by public transport to retail concentrations and public hospitals in Athens, using spatial autocorrelation analysis based on Local Indicators of Spatial Autocorrelation (LISA) method and Geographically Weighted Regression (GWR).
For this reason, the study area was divided in a 300x300 meter square grid of points representing the location points of the study. For each point, the travel time to each of the retail concentration and public hospital location was estimated using Google Directions API. The accessibility of each point was then calculated as the percentage of reachable destinations for each land use group within 45 minutes. The results where then aggregated to zip code level, where along with data regarding the average annual zip code income, population density and destination from Athens’ central business district formed the final dataset.
The analysis that followed suggests that there is a cluster of high accessibility in the city center and a cluster of low accessibility in the outer suburbs. In addition, a middle zone of insignificant clustering is located between the two clusters. The chosen urban structure and socioeconomic variables that were used for the geographically weighted regression have significant effects except for the case of population density on public transport accessibility. More specifically, distance from the central business district (CBD) is found to be negatively correlated with accessibility to both retail concentrations and hospitals. On the other hand, annual average income seems to be positively correlated with accessibility to both destinations. Finally, population density has a positive correlation with only retail concentrations. In addition, the analysis indicated that there may be more unknown factors affecting accessibility to retail concentrations in the city center than the periphery.}},
author = {{Vafeiadis, Evangelos}},
language = {{eng}},
note = {{Student Paper}},
series = {{Master Thesis in Geographical Information Science}},
title = {{Exploring the distribution of accessibility by public transport using spatial analysis : a case study for retail concentrations and public hospitals in Athens}},
year = {{2019}},
}