Coastal land cover mapping using UAV imaging on the southeast coast of Brazil

Autor(es)

Bispo dos Santos, Gabriel Almeida ; Conti, Luis Americo

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF COASTAL CONSERVATION; v. 26, n. 5, p. 10-pg., 2022-10-01.

Resumo

The use of Object Based Analysis (OBIA) from drone images (Unmanned Aerial vehicles - UAVs) has been increasingly employed in land use mapping, specifically in coastal areas, regions of high dynamics and complexity. Such approaches can be very useful as they allow the elaboration of high spatial resolution maps and multitemporal analysis. However, few studies have been conducted in order to evaluate different classification methods and establish best practices for the use of these applications with a standardized and comparable way. In this work four supervised classification methods were analysed (Logistic Regression, Decision Forest, Decision Jungle and Neural Networks); in addition, we have analysed the role of different parameters (such as texture and shape indices) in the classification. The results may significantly contribute to the dissemination of the use of UAVs for coastal areas mapping, specifically for monitoring and management as well as in the detection of areas vulnerable to erosion and in the delimitation of regions sensitive to environmental changes. (AU)

• Processo FAPESP: 19/22028-0 - Multihab - imageamento multiespectral através de vants (veículos aéreos não tripulados) no mapeamento e monitoramento de ecossistemas costeiros
• Beneficiário: Luis Americo Conti
• Modalidade de apoio: Auxílio à Pesquisa - Programa de Pesquisa sobre Mudanças Climáticas Globais - Regular