Análise de uso e cobertura da terra na região do tapajós, Amazônia central, a partir de dado polarimétrico PALSAR/ALOS-1 e coerência interferométrica TanDEM-X (Land use and forest cover analysis in central Amazon, from PALSAR/ALOS polarimetric data and TANDEM-X interferometric coherence)

Évelyn Márcia Pôssa, Fábio Furlan Gama, João Roberto dos Santos, José Cláudio Mura, Polyanna da Conceição Bispo

Resumo


O objetivo do presente trabalho é verificar o potencial de atributos polarimétricos extraídos de imagens-radar PALSAR/ALOS conjugados ao atributo de coerência interferométrica dos dados TanDEM-X/TerraSAR-X para o mapeamento de uso e cobertura da terra na Amazônia brasileira. Na análise dessas imagens-radar uma série de atributos polarimétricos foi extraída a partir da informação de fase utilizando teoremas de decomposições de alvos formulados por Cloude-Pottier, Touzi, Freeman-Durden e Yamaguchi. Esse procedimento resultou em quatro grupos de atributos, os quais foram classificados individualmente e/ou associados à coerência interferométrica, através do algoritmo MAXVER-ICM. Empregando informações de campo, a validação temática foi realizada por matrizes de confusão, índice Kappa e exatidão global. No cenário investigado nove classes temáticas (floresta primária; solo em pousio ou solo preparado; sucessões secundárias avançada, intermediária e inicial; área cultivada; pasto sujo; pasto limpo; e corpo d’água) foram identificadas no processo de mapeamento deste ambiente tropical. Atributos polarimétricos derivados do teorema de decomposição de Cloude-Pottier (H/α/A) associados ao atributo de coerência interferométrica (γ) mostraram melhor desempenho classificatório (Kappa = 0,72 e exatidão global = 78,79%) comparado aos demais.

 

 

 

A B S T R A C T

The aim of this study is to verify the potential of polarimetric attributes extracted from PALSAR/ALOS-1 radar images combined to the interferometric coherence from TanDEM-X/TerraSAR-X data for land use and land cover mapping in the Brazilian Amazon. From the phase informationIn of these radar images, polarimetric attributes were extracted by target decomposition theorems formulated by Cloude-Pottier, Touzi, Freeman-Durden and Yamaguchi. This procedure resulted in four groups of attributes, which were classified individually and/or associated with interferometric coherence descriptors through the MAXVER-ICM algorithm. Using field information the method was validated based on the confusion matrix, Kappa and overall accuracy. A total of nine thematic classes were identified in the mapping process of this tropical environment: primary forest; advanced, intermediate and initial secondary succession; bare soil; agricultural area; two classes of pasture and water body.  Derived attributes from Cloude-Pottier decomposition theorem (H/α/A) associated with interferometric coherence attribute (γ) showed the best classification performance (Kappa = 0.72 and an overall accuracy = 78.79%) compared to the other methods.

Keywords: land use and land cover; Amazon. Remote Sensing; SAR; Target decomposition; interferometric coherence


Palavras-chave


uso e cobertura da Terra; Amazônia; Sensoriamento Remoto; radar; decomposição de alvos; coerência interferométrica

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DOI: https://doi.org/10.26848/rbgf.v11.6.p2094-2108

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Revista Brasileira de Geografia Física - ISSN: 1984-2295

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Esta obra está licenciada com uma Licença Creative Commons Attribution-NonCommercial 4.0 International License