Unmanned aerial systems in remotely sensed biomass estimates : how they improve the quality of existing satellite based approaches

Detalhes bibliográficos
Autor(a) principal: Feng, Leon Gaw Yan
Data de Publicação: 2018
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/33792
Resumo: Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
id RCAP_1acdec173165f1bf3be8ce430cb8092c
oai_identifier_str oai:run.unl.pt:10362/33792
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Unmanned aerial systems in remotely sensed biomass estimates : how they improve the quality of existing satellite based approachesBiomassDronesModellingSentinel 2UASVegetation indicesWorld View 3Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesForests of the world provide an important ecosystem service in the fight against climate change by sequestering carbon from the atmosphere and storing them as biomass. However, cloud cover and terrain inaccessibility hamper studies of forest biomass using satellites, especially in the dense jungles of the tropics. This study investigated the use of UAS to complement existing satellite based approaches by exploring what information can be derived from UAS sensors and how their biomass estimates can be applied to satellite sensors to improve their accuracies. A biomass estimation model was built using on the ground measurements while GIS was used to generate biomass maps. The results from the model show that NDVI and tree heights were statistically significant explanatory variables for biomass in the Mixed Oak Forests of Davert, Germany. Estimates from UAS were the most accurate in terms of R2, compared to other sensor estimates from Sentinel 2, World View 3 and Orthophotos. Hence, two adjustment factors were proposed to improve the accuracy of World View 3 and Sentinel 2 estimates. UAS are thus a versatile sensor platform for biomass studies that complements satellite sensors to improve studies of global biomass of forests.Prinz, TorstenLehmann, Jan Rudolf KarlGuerrero, IgnacioRUNFeng, Leon Gaw Yan2018-04-04T15:03:01Z2018-02-022018-02-02T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/33792TID:201893843enginfo: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:RCAAP2024-03-11T04:18:33Zoai:run.unl.pt:10362/33792Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:30:04.718907Repositório 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 Unmanned aerial systems in remotely sensed biomass estimates : how they improve the quality of existing satellite based approaches
title Unmanned aerial systems in remotely sensed biomass estimates : how they improve the quality of existing satellite based approaches
spellingShingle Unmanned aerial systems in remotely sensed biomass estimates : how they improve the quality of existing satellite based approaches
Feng, Leon Gaw Yan
Biomass
Drones
Modelling
Sentinel 2
UAS
Vegetation indices
World View 3
title_short Unmanned aerial systems in remotely sensed biomass estimates : how they improve the quality of existing satellite based approaches
title_full Unmanned aerial systems in remotely sensed biomass estimates : how they improve the quality of existing satellite based approaches
title_fullStr Unmanned aerial systems in remotely sensed biomass estimates : how they improve the quality of existing satellite based approaches
title_full_unstemmed Unmanned aerial systems in remotely sensed biomass estimates : how they improve the quality of existing satellite based approaches
title_sort Unmanned aerial systems in remotely sensed biomass estimates : how they improve the quality of existing satellite based approaches
author Feng, Leon Gaw Yan
author_facet Feng, Leon Gaw Yan
author_role author
dc.contributor.none.fl_str_mv Prinz, Torsten
Lehmann, Jan Rudolf Karl
Guerrero, Ignacio
RUN
dc.contributor.author.fl_str_mv Feng, Leon Gaw Yan
dc.subject.por.fl_str_mv Biomass
Drones
Modelling
Sentinel 2
UAS
Vegetation indices
World View 3
topic Biomass
Drones
Modelling
Sentinel 2
UAS
Vegetation indices
World View 3
description Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial Technologies
publishDate 2018
dc.date.none.fl_str_mv 2018-04-04T15:03:01Z
2018-02-02
2018-02-02T00:00:00Z
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/10362/33792
TID:201893843
url http://hdl.handle.net/10362/33792
identifier_str_mv TID:201893843
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
_version_ 1799137925202444288

Registros relacionados