Analyzing sustainability effects of road pavement : case study: Lappeenranta City
Cedillo, Valeria (2019)
Diplomityö
Cedillo, Valeria
2019
School of Engineering Science, Tietotekniikka
Kaikki oikeudet pidätetään.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2019090326571
https://urn.fi/URN:NBN:fi-fe2019090326571
Tiivistelmä
Transport sector plays a key role for the overall sustainability development, sustainability indicators and sustainability evaluation are well-known terms that have acquired substantial importance. The concept of sustainability implies interaction of the three pillars: economic, environmental and social. In order to apply these aspects to transportation is necessarily to create an interactive link of transportation with the concepts mentioned before.
The approach of this study was to assess the current state of the roads pavement in Lappeenranta city based on given dataset and evaluate the influence of the road network towards transportation’s sustainability. The raw data extraction and process was made using Python libraries, data storing and filtering in MongoDB and for roads visualization QGIS software was utilized.
According to the data provided, three variables were selected, these variables are related to each sustainability aspect.
The outcome of the calculations is represented in graphics, and each variable is firstly evaluated individually. The results demonstrate that the more kilometres a road has the higher the value of the variables will be, but there is no direct relationship between the mentioned attributes, however we can conclude that a more extended sample data set is required, as well as more methods and tools in order to build a framework that can define and compare sustainable goals against the results obtained.
The approach of this study was to assess the current state of the roads pavement in Lappeenranta city based on given dataset and evaluate the influence of the road network towards transportation’s sustainability. The raw data extraction and process was made using Python libraries, data storing and filtering in MongoDB and for roads visualization QGIS software was utilized.
According to the data provided, three variables were selected, these variables are related to each sustainability aspect.
The outcome of the calculations is represented in graphics, and each variable is firstly evaluated individually. The results demonstrate that the more kilometres a road has the higher the value of the variables will be, but there is no direct relationship between the mentioned attributes, however we can conclude that a more extended sample data set is required, as well as more methods and tools in order to build a framework that can define and compare sustainable goals against the results obtained.