Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data

Detalhes bibliográficos
Autor(a) principal: Machado, Daniel Carlos dos Santos
Data de Publicação: 2015
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/14556
Resumo: Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.
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spelling Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary dataObject-based time-seriesGoogle Earth EngineRefugee camps monitoringRetrospective analysisCrisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.Prinz, TorstenKnoth, ChristianPla Bañón, FilibertoRUNMachado, Daniel Carlos dos Santos2015-03-26T10:57:51Z2015-01-302015-01-30T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/14556TID:201394022porinfo: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:RCAAP2024-03-11T03:49:47Zoai:run.unl.pt:10362/14556Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:21:56.324625Repositório 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 Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data
title Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data
spellingShingle Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data
Machado, Daniel Carlos dos Santos
Object-based time-series
Google Earth Engine
Refugee camps monitoring
Retrospective analysis
title_short Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data
title_full Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data
title_fullStr Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data
title_full_unstemmed Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data
title_sort Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data
author Machado, Daniel Carlos dos Santos
author_facet Machado, Daniel Carlos dos Santos
author_role author
dc.contributor.none.fl_str_mv Prinz, Torsten
Knoth, Christian
Pla Bañón, Filiberto
RUN
dc.contributor.author.fl_str_mv Machado, Daniel Carlos dos Santos
dc.subject.por.fl_str_mv Object-based time-series
Google Earth Engine
Refugee camps monitoring
Retrospective analysis
topic Object-based time-series
Google Earth Engine
Refugee camps monitoring
Retrospective analysis
description Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.
publishDate 2015
dc.date.none.fl_str_mv 2015-03-26T10:57:51Z
2015-01-30
2015-01-30T00:00:00Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/14556
TID:201394022
url http://hdl.handle.net/10362/14556
identifier_str_mv TID:201394022
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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
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