AUTOMATIC BUILDING CHANGE DETECTION USING MULTI-TEMPORAL AIRBORNE LiDAR DATA

Autor(es)

dos Santos, R. C. ; Galo, M. ; Carrilho, A. C. ; Pessoa, G. G. ; de Oliveira, R. A. R. ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: 2020 IEEE LATIN AMERICAN GRSS & ISPRS REMOTE SENSING CONFERENCE (LAGIRS); v. N/A, p. 6-pg., 2020-01-01.

Resumo

The automatic detection of building changes is an essential process for urban area monitoring, urban planning, and database update. In this context, 3D information derived from multi-temporal airborne LiDAR scanning is one effective alternative. Despite several works in the literature, the separation of change areas in building and non-building remains a challenge. In this sense, it is proposed a new method for building change detection, having as the main contribution the use of height entropy concept to identify the building change areas. The experiments were performed considering multi-temporal airborne LiDAR data from 2012 and 2014, both with average density around 5 points/m(2). Qualitative and quantitative analyses indicate that the proposed method is robust in building change detection, having the potential to identify small changes (larger than 20 m(2)). In general, the change detection method presented average completeness and correctness around 97% and 71%, respectively. (AU)

• Processo FAPESP: 19/05268-8 - REGULARIZAÇÃO DE CONTORNOS DE TELHADOS DE EDIFICAÇÕES A PARTIR DA INTEGRAÇÃO DE DADOS LiDAR E IMAGENS AÉREAS UTILIZANDO O CONCEITO CD-SPLINE
• Beneficiário: Renato César dos Santos
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado