Overview and Benchmark on Multi-Modal Lidar Point Cloud Registration for Forest Applications

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorNational Land Survey of Finland-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorCampos, Mariana Batista-
Autor(es): dc.creatorCastanheiro, Leticia Ferrari-
Autor(es): dc.creatorShah, Dipal-
Autor(es): dc.creatorWang, Yunsheng-
Autor(es): dc.creatorKukko, Antero-
Autor(es): dc.creatorPuttonen, Eetu-
Data de aceite: dc.date.accessioned2025-08-21T20:24:18Z-
Data de disponibilização: dc.date.available2025-08-21T20:24:18Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-05-11-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.5194/isprs-archives-XLVIII-1-2024-43-2024-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/306828-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/306828-
Descrição: dc.descriptionLight Detection and Ranging (LIDAR) is widely acknowledged as a robust tool for monitoring forest structure, dynamics, and changes. To achieve a high-complete forest structural model, LiDAR data acquisition from both aerial (above-canopy) and terrestrial (below-canopy) platforms is commonplace. Consequently, in such multi-modal LiDAR cases, robust data registration is required for accurate forest analysis, such as biomass and canopy growth. Yet, multi-modal LiDAR registration remains a significant challenge due to differences in observation perspectives, deficient data overlap, and often inhomogeneity in point distributions and densities. The challenge increases in complex forest environments due to the abundance of unstable features (e.g., leaves) and occlusions. Thus, the dynamic nature of forest scenes needs to be considered when applying registration methods on forest point clouds. In this paper, we overview the latest advancements in registering forest point clouds from multi-modal data acquisitions, aiming to discuss the strengths and weaknesses of the most used LiDAR registration methods for forest applications. To support our investigations, we benchmark two multi-modal registration methods especially designed for forest mapping against traditional global and feature-based approaches. Experiment assessments were conducted using two point clouds acquired from a permanent laser scanning and airborne laser scanning systems at a boreal forest plot.-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionDepartment of Remote Sensing and Photogrammetry Finnish Geospatial Research Institute National Land Survey of Finland-
Descrição: dc.descriptionDepartment of Cartography São Paulo State University (UNESP), São Paulo-
Descrição: dc.descriptionDepartment of Cartography São Paulo State University (UNESP), São Paulo-
Descrição: dc.descriptionCNPq: 141550/2020-1-
Descrição: dc.descriptionCAPES: 88887.695922/2022-00-
Formato: dc.format43-50-
Idioma: dc.languageen-
Relação: dc.relationInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectALS-TLS-
Palavras-chave: dc.subjectcoarse registration-
Palavras-chave: dc.subjectcross-platform LiDAR-
Palavras-chave: dc.subjectfeature-based methods-
Palavras-chave: dc.subjectstem matching-
Título: dc.titleOverview and Benchmark on Multi-Modal Lidar Point Cloud Registration for Forest Applications-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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