High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/134627 |
Resumo: | Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies |
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High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, PortugalDissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesTimely, reliable, and cost-efficient information about soil moisture is important for supporting agricultural practitioners in monitoring the impact of alternative agricultural practices. Regenerative agriculture is increasingly gaining traction; however, farmers lack easy access to information on key agricultural parameters such as soil moisture. Therefore, this study seeks to explore the feasibility of soil moisture estimation at high-resolution (around 10 m) using Sentinel-1 remote sensing radar data. A machine learning model was developed using a random forest regression algorithm with a combination of SAR-based, topography and Seninel-2 optical-based data as inputs. Through a k-fold cross-validation of the model, an average r-squared (R²) of 0.17, a root mean squared error (RMSE) of 3.51 (% VMC), and an mean absolute percentage error (MAPE) of 83.34, was achieved.Torres-Sospedra, JoaquínKuntz, SteffenMeyer, HannaRUNPetersen, Syver Jahren2022-03-16T16:00:16Z2022-03-022022-03-02T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/134627TID:202966194enginfo: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:RCAAP2024-03-11T05:13:04Zoai:run.unl.pt:10362/134627Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:48:10.964098Repositório 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 |
High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal |
title |
High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal |
spellingShingle |
High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal Petersen, Syver Jahren |
title_short |
High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal |
title_full |
High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal |
title_fullStr |
High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal |
title_full_unstemmed |
High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal |
title_sort |
High-resolution Soil Moisture Retrieval Using Sentinel-1 Data for Evaluating Regenerative Agriculture: A feasibility study from Alentejo, Portugal |
author |
Petersen, Syver Jahren |
author_facet |
Petersen, Syver Jahren |
author_role |
author |
dc.contributor.none.fl_str_mv |
Torres-Sospedra, Joaquín Kuntz, Steffen Meyer, Hanna RUN |
dc.contributor.author.fl_str_mv |
Petersen, Syver Jahren |
description |
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-03-16T16:00:16Z 2022-03-02 2022-03-02T00:00:00Z |
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/10362/134627 TID:202966194 |
url |
http://hdl.handle.net/10362/134627 |
identifier_str_mv |
TID:202966194 |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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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 |
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