Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlements

Detalhes bibliográficos
Autor(a) principal: Ayo, Brenda
Data de Publicação: 2020
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/93641
Resumo: Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
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spelling Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlementsInformal SettlementsRemote SensingUrbanizationMachine Learning (ML)Random Forest (RF)Convolutional Neural Networks (CNN)Sentinel-2 satellite imageryDissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesThe identification and monitoring of informal settlements in urban areas is an important step in developing and implementing pro-poor urban policies. Understanding when, where and who lives inside informal settlements is critical to efforts to improve their resilience. This study aims at integrating OSM data and sentinel-2 imagery for classifying and monitoring the growth of informal settlements methods to map informal areas in Kampala (Uganda) and Dar es Salaam (Tanzania) and to monitor their growth in Kampala. Three building feature characteristics of size, shape and Distance to nearest Neighbour were derived and used to cluster and classify informal areas using Hotspot Cluster analysis and ML approach on OSM buildings data. The resultant informal regions in Kampala were used with Sentinel-2 image tiles to investigate the spatiotemporal changes in informal areas using Convolutional Neural Networks (CNNs). Results from Optimized Hot Spot Analysis and Random Forest Classification show that Informal regions can be mapped based on building outline characteristics. An accuracy of 90.3% was achieved when an optimally trained CNN was executed on a test set of 2019 satellite image tiles. Predictions of informality from new datasets for the years 2016 and 2017 provided promising results on combining different open source geospatial datasets to identify, classify and monitor informal settlements.Silva, Joel Dinis Baptista Ferreira daMeyer, HannaGuerrero, IgnacioRUNAyo, Brenda2020-03-02T17:14:07Z2020-02-272020-02-27T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/93641TID:202456870enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:41:56Zoai:run.unl.pt:10362/93641Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:37:48.087208Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlements
title Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlements
spellingShingle Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlements
Ayo, Brenda
Informal Settlements
Remote Sensing
Urbanization
Machine Learning (ML)
Random Forest (RF)
Convolutional Neural Networks (CNN)
Sentinel-2 satellite imagery
title_short Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlements
title_full Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlements
title_fullStr Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlements
title_full_unstemmed Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlements
title_sort Integrating openstreetmap data and sentinel-2 Imagery for classifying and monitoring informal settlements
author Ayo, Brenda
author_facet Ayo, Brenda
author_role author
dc.contributor.none.fl_str_mv Silva, Joel Dinis Baptista Ferreira da
Meyer, Hanna
Guerrero, Ignacio
RUN
dc.contributor.author.fl_str_mv Ayo, Brenda
dc.subject.por.fl_str_mv Informal Settlements
Remote Sensing
Urbanization
Machine Learning (ML)
Random Forest (RF)
Convolutional Neural Networks (CNN)
Sentinel-2 satellite imagery
topic Informal Settlements
Remote Sensing
Urbanization
Machine Learning (ML)
Random Forest (RF)
Convolutional Neural Networks (CNN)
Sentinel-2 satellite imagery
description Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
publishDate 2020
dc.date.none.fl_str_mv 2020-03-02T17:14:07Z
2020-02-27
2020-02-27T00:00:00Z
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/10362/93641
TID:202456870
url http://hdl.handle.net/10362/93641
identifier_str_mv TID:202456870
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:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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