Analyzing Spatio-temporal Land Cover Dynamics in an Atlantic Forest Portion Using Unsupervised Change Detection Techniques

Autor(es)

Sapucci, Gabriela Ribeiro ^[1] ; Negri, Rogerio Galante ^[1] ; Casaca, Wallace ^[1] ; Massi, Klecia Gili ^[2]

Afiliação do(s) autor(es)

^[1] Sao Paulo State Univ UNESP, Inst Sci & Technol, Sao Jose Dos Campos, SP - Brazil

^[2] Sao Paulo State Univ UNESP, Dept Energy Engn, Rosana, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: ENVIRONMENTAL MODELING & ASSESSMENT; v. 26, n. 4, p. 581-590, AUG 2021.
• Citações Web of Science: 0

Resumo

Over the past decades, the Southeast Atlantic Forest in Paraiba do Sul River Valley has suffered intense deforestation and human disturbances. Due to the Atlantic Forest biodiversity and the economic relevance of such a region in Brazil, spatial-temporal analyses are of crucial importance to protect the forest, as well as to support economic decision-making of public and private agents. In this context, the use of change detection techniques applied to remote sensing imagery arises as a powerful tool to track and map the Earth's surface transformations. Therefore, this work investigates the effectiveness and practical feasibility of distinct unsupervised change detection approaches when they are applied to reveal the spatial-temporal dynamics in Paraiba do Sul River Valley across the last four decades. Different change detection approaches such as Change Vector Analysis (CVA), a K-Means and Principal Component Analysis (PCA-KM) framework, and a Alternating Sequential Filtering (ASF) based process were taken and properly tuned to cope with Landsat image series. The analysis of the results revealed a permanent land cover change rate over the last decades. Moreover, these changes do not necessary occur in the same locations, as it was confirmed the existence of successive modifications in original coverage of the study area. Another observed aspect is that the simplest technique for detecting changes, CVA, turned out to be the best approach to map the changes in the examined region. (AU)

• Processo FAPESP: 18/01033-3 - Investigação e Desenvolvimento de Algoritmos para Detecção de Mudança em Imagens de Sensoriamento Remoto
• Beneficiário: Rogério Galante Negri
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 17/14614-1 - Estudo multitemporal sobre os efeitos da silvicultura no uso e cobertura do solo nas regiões do Vale do Paraíba e Serra da Mantiqueira
• Beneficiário: Gabriela Ribeiro Sapucci
• Modalidade de apoio: Bolsas no Brasil - Iniciação Científica