Publicação
Processamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COS
| Resumo: | The use of LiDAR (Light Detection and Ranging) data to generate geographic datasets for the production and updating of the Land Use and Land Cover Map (COS) has become indispensable. The three-dimensional information offered by the data makes enables overcoming the limitations of traditional orthophoto photointerpretation methodologies, allowing the identification of territorial changes more quickly and accurately. The main objective of this work consisted of developing a LiDAR data processing workflow that automatically detects key landscape elements, such as forest patches, permanent crops, and buildings, and integrates them as auxiliary layers in the preparation of the COS. To this end, products derived from the LiDAR point cloud, including digital terrain and height models (Canopy Height Model), to which tree and canopy segmentation algorithms were applied, and spatial analyses aimed at identifying the desired features were performed. The results were then cross-referenced with multispectral orthophotography for thematic validation. The approach demonstrated high effectiveness, in distinguishing forest patches in agroforestry mosaics, identifying orchards, vineyards, and olive groves by their regular geometric pattern, and detecting buildings with greater detail and up-to-dateness than existing cartography. Comparison with the COS2023 revealed that more than 94% of the built-up area identified from the LiDAR data coincides with the already mapped urban fabric, while simultaneously evidencing new constructions and urban expansions. The work proves the advantages of integrating LiDAR data into cartographic updating. The three-dimensional information accelerates the COS reviewing cycles, improves the thematic and spatial accuracy of the product, and supports decision-making with the most up-to-data. This contribution paves the way for a geographic alert system capable of signalling significant changes in land occupation, strengthening the capacity of the Direção-Geral do Território (DGT) to monitor the territory more efficiently. |
|---|---|
| Autores principais: | Domingues,Miguel Miranda Barreira |
| Assunto: | LiDAR Land Use and Land Cover Map Remote Sensing Land Cover Classification Thematic Mapping |
| Ano: | 2026 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | português |
| Origem: | Repositório da Universidade de Lisboa |
| _version_ | 1869345837652377600 |
|---|---|
| author | Domingues,Miguel Miranda Barreira |
| author_facet | Domingues,Miguel Miranda Barreira |
| author_role | author |
| contributor_name_str_mv | Ferreira,Ana Cristina Navarro Benevides,Pedro José Santos da Costa Faculdade de Ciências Repositório Científico de Acesso Aberto da ULisboa |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Domingues,Miguel Miranda Barreira\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Ferreira,Ana Cristina Navarro Benevides,Pedro José Santos da Costa Faculdade de Ciências Repositório Científico de Acesso Aberto da ULisboa |
| datacite.creators.creator.creatorName.fl_str_mv | Domingues,Miguel Miranda Barreira |
| datacite.date.Accepted.fl_str_mv | 2026-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2026-03-10T11:40:02Z |
| datacite.date.embargoed.fl_str_mv | 2026-03-10T11:40:02Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | LiDAR Land Use and Land Cover Map Remote Sensing Land Cover Classification Thematic Mapping |
| datacite.titles.title.fl_str_mv | Processamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COS |
| dc.contributor.none.fl_str_mv | Ferreira,Ana Cristina Navarro Benevides,Pedro José Santos da Costa Faculdade de Ciências Repositório Científico de Acesso Aberto da ULisboa |
| dc.creator.none.fl_str_mv | Domingues,Miguel Miranda Barreira |
| dc.date.Accepted.fl_str_mv | 2026-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2026-03-10T11:40:02Z |
| dc.date.embargoed.fl_str_mv | 2026-03-10T11:40:02Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.5/117469 |
| dc.language.none.fl_str_mv | por |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | LiDAR Land Use and Land Cover Map Remote Sensing Land Cover Classification Thematic Mapping |
| dc.title.fl_str_mv | Processamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COS |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | The use of LiDAR (Light Detection and Ranging) data to generate geographic datasets for the production and updating of the Land Use and Land Cover Map (COS) has become indispensable. The three-dimensional information offered by the data makes enables overcoming the limitations of traditional orthophoto photointerpretation methodologies, allowing the identification of territorial changes more quickly and accurately. The main objective of this work consisted of developing a LiDAR data processing workflow that automatically detects key landscape elements, such as forest patches, permanent crops, and buildings, and integrates them as auxiliary layers in the preparation of the COS. To this end, products derived from the LiDAR point cloud, including digital terrain and height models (Canopy Height Model), to which tree and canopy segmentation algorithms were applied, and spatial analyses aimed at identifying the desired features were performed. The results were then cross-referenced with multispectral orthophotography for thematic validation. The approach demonstrated high effectiveness, in distinguishing forest patches in agroforestry mosaics, identifying orchards, vineyards, and olive groves by their regular geometric pattern, and detecting buildings with greater detail and up-to-dateness than existing cartography. Comparison with the COS2023 revealed that more than 94% of the built-up area identified from the LiDAR data coincides with the already mapped urban fabric, while simultaneously evidencing new constructions and urban expansions. The work proves the advantages of integrating LiDAR data into cartographic updating. The three-dimensional information accelerates the COS reviewing cycles, improves the thematic and spatial accuracy of the product, and supports decision-making with the most up-to-data. This contribution paves the way for a geographic alert system capable of signalling significant changes in land occupation, strengthening the capacity of the Direção-Geral do Território (DGT) to monitor the territory more efficiently. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| fulltext.url.fl_str_mv | https://repositorio.ulisboa.pt/bitstreams/18f89ce2-922a-40fa-837c-1be7610c14f9/download |
| id | ul_feb34ec7f04fb64d63b495c4959b3bbf |
| identifier.url.fl_str_mv | http://hdl.handle.net/10400.5/117469 |
| inst_facet_str | urn:organizationAcronym:ul{{{_:::_}}}Universidade de Lisboa |
| instacron_str | ul |
| institution | Universidade de Lisboa |
| instname_str | Universidade de Lisboa |
| language | por |
| network_acronym_str | ul |
| network_name_str | Repositório da Universidade de Lisboa |
| oai_identifier_str | oai:repositorio.ulisboa.pt:10400.5/117469 |
| organization_str_mv | urn:organizationAcronym:ul |
| person_str_mv | Domingues,Miguel Miranda Barreira |
| publishDate | 2026 |
| repo_facet_str | urn:repositoryAcronym:ul{{{_:::_}}}Repositório da Universidade de Lisboa |
| reponame_str | Repositório da Universidade de Lisboa |
| repository_id_str | urn:repositoryAcronym:ul |
| service_str_mv | urn:repositoryAcronym:ul |
| spelling | porenThe use of LiDAR (Light Detection and Ranging) data to generate geographic datasets for the production and updating of the Land Use and Land Cover Map (COS) has become indispensable. The three-dimensional information offered by the data makes enables overcoming the limitations of traditional orthophoto photointerpretation methodologies, allowing the identification of territorial changes more quickly and accurately. The main objective of this work consisted of developing a LiDAR data processing workflow that automatically detects key landscape elements, such as forest patches, permanent crops, and buildings, and integrates them as auxiliary layers in the preparation of the COS. To this end, products derived from the LiDAR point cloud, including digital terrain and height models (Canopy Height Model), to which tree and canopy segmentation algorithms were applied, and spatial analyses aimed at identifying the desired features were performed. The results were then cross-referenced with multispectral orthophotography for thematic validation. The approach demonstrated high effectiveness, in distinguishing forest patches in agroforestry mosaics, identifying orchards, vineyards, and olive groves by their regular geometric pattern, and detecting buildings with greater detail and up-to-dateness than existing cartography. Comparison with the COS2023 revealed that more than 94% of the built-up area identified from the LiDAR data coincides with the already mapped urban fabric, while simultaneously evidencing new constructions and urban expansions. The work proves the advantages of integrating LiDAR data into cartographic updating. The three-dimensional information accelerates the COS reviewing cycles, improves the thematic and spatial accuracy of the product, and supports decision-making with the most up-to-data. This contribution paves the way for a geographic alert system capable of signalling significant changes in land occupation, strengthening the capacity of the Direção-Geral do Território (DGT) to monitor the territory more efficiently.application/pdfptProcessamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COSDomingues,Miguel Miranda BarreiraFerreira,Ana Cristina NavarroBenevides,Pedro José Santos da CostaFaculdade de CiênciasHostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@ulisboa.ptrepositorio@ulisboa.pt2026-03-10T11:40:02Z20262026-01-01T00:00:00ZHandlehttp://hdl.handle.net/10400.5/117469http://purl.org/coar/access_right/c_abf2open accessLiDARLand Use and Land Cover MapRemote SensingLand Cover ClassificationThematic Mapping7239866 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/18f89ce2-922a-40fa-837c-1be7610c14f9/download |
| spellingShingle | Processamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COS Domingues,Miguel Miranda Barreira LiDAR Land Use and Land Cover Map Remote Sensing Land Cover Classification Thematic Mapping |
| status | SINGLETON |
| subject.fl_str_mv | LiDAR Land Use and Land Cover Map Remote Sensing Land Cover Classification Thematic Mapping |
| title | Processamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COS |
| title_full | Processamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COS |
| title_fullStr | Processamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COS |
| title_full_unstemmed | Processamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COS |
| title_short | Processamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COS |
| title_sort | Processamento de Dados LiDAR para gerar Conjuntos de Dados Geográficos para apoio à Produção da COS |
| topic | LiDAR Land Use and Land Cover Map Remote Sensing Land Cover Classification Thematic Mapping |
| topic_facet | LiDAR Land Use and Land Cover Map Remote Sensing Land Cover Classification Thematic Mapping |
| url | http://hdl.handle.net/10400.5/117469 |
| visible | 1 |