Lisbon´s Real Estate Analysis based on Proximity Calculations

Bibliographic Details
Main Author: Valério, Maria Madalena Jorge do Nascimento
Publication Date: 2023
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/152094
Summary: Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
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spelling Lisbon´s Real Estate Analysis based on Proximity CalculationsLisbonSmart CityReal EstateAccessibilityMobilitySDG 11 - Sustainable cities and communitiesProject Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsThe real estate market is always changing and evolving and with sustainability becoming an increasingly important topic, the way the price of a property is determined, and the factors taken in consideration, should evolve as well. Inspired by the popular concept of Smart Cities, more specifically the 15-minute city approach, which is a concept highly focused on accessibility and walkability in cities, different variables were calculated to assess each property’s accessibility and diversity of amenities. Both these factors are different for each property, depending on their location. This work presents an analysis of the real estate market in Lisbon where, aside from the physical attributes of a habitation, the diversity and accessibility to difference services in each location will be evaluated and integrated in the machine learning process. The goal is to know the impact of each calculated measure when predicting the price per meter value of each house, in order to help understand why similar houses across Lisbon have such distinctive prices. Both the Euclidean Distance and the Network Distance were used in the calculations. The distance to Tejo River and the number of commercial establishments within a 15-minute walk radius were two of the most important features in the predictive models tested. Three different methods were tested and improved, electing the Random Forest Regressor as the best the one and the one to be used in the final model. The final model had half of the variance in the target explained by the all the calculated features, which makes this analysis a potential good tool to help fill the gap of a predictive model that only factors in the physical characteristics of a house.Neto, Miguel de Castro Simões FerreiraJardim, João Bruno Morais de SousaRUNValério, Maria Madalena Jorge do Nascimento2023-04-24T13:49:12Z2023-04-102023-04-10T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/152094TID:203268385enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T18:11:03Zoai:run.unl.pt:10362/152094Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:41:21.253725Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Lisbon´s Real Estate Analysis based on Proximity Calculations
title Lisbon´s Real Estate Analysis based on Proximity Calculations
spellingShingle Lisbon´s Real Estate Analysis based on Proximity Calculations
Valério, Maria Madalena Jorge do Nascimento
Lisbon
Smart City
Real Estate
Accessibility
Mobility
SDG 11 - Sustainable cities and communities
title_short Lisbon´s Real Estate Analysis based on Proximity Calculations
title_full Lisbon´s Real Estate Analysis based on Proximity Calculations
title_fullStr Lisbon´s Real Estate Analysis based on Proximity Calculations
title_full_unstemmed Lisbon´s Real Estate Analysis based on Proximity Calculations
title_sort Lisbon´s Real Estate Analysis based on Proximity Calculations
author Valério, Maria Madalena Jorge do Nascimento
author_facet Valério, Maria Madalena Jorge do Nascimento
author_role author
dc.contributor.none.fl_str_mv Neto, Miguel de Castro Simões Ferreira
Jardim, João Bruno Morais de Sousa
RUN
dc.contributor.author.fl_str_mv Valério, Maria Madalena Jorge do Nascimento
dc.subject.por.fl_str_mv Lisbon
Smart City
Real Estate
Accessibility
Mobility
SDG 11 - Sustainable cities and communities
topic Lisbon
Smart City
Real Estate
Accessibility
Mobility
SDG 11 - Sustainable cities and communities
description Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
publishDate 2023
dc.date.none.fl_str_mv 2023-04-24T13:49:12Z
2023-04-10
2023-04-10T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/152094
TID:203268385
url http://hdl.handle.net/10362/152094
identifier_str_mv TID:203268385
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833596895561252864

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