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)

Abstract

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 TThe 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

Discriminating Forest Successional Stages, Forest Degradation, and Land Use in Central Amazon Using ALOS/PALSAR-2 Full-Polarimetric Data

“…For each sample, representative field photos and geographic coordinates (latitude and longitude), using a Global Positioning System (GPS) receiver (Garmin eTrex10 model), were gathered. The sites were selected based on specific research interests and on previous field campaigns carried out in 2012, 2014, and 2016 [35,48,52,53]. These previous authors have also defined site-specific land cover classes of interest, based on widely used criterion to differentiate succession processes in the Brazilian Amazon as presented by Vieira et al [54] and Uhl et al [55], as well as land use adequate to local landscape, presented by Pôssa et al [35].…”

“…The sites were selected based on specific research interests and on previous field campaigns carried out in 2012, 2014, and 2016 [35,48,52,53]. These previous authors have also defined site-specific land cover classes of interest, based on widely used criterion to differentiate succession processes in the Brazilian Amazon as presented by Vieira et al [54] and Uhl et al [55], as well as land use adequate to local landscape, presented by Pôssa et al [35]. The dominant LULC typology for each site was defined as: Primary Forest (PF); Advanced Secondary Succession (SS3); Intermediate Secondary Succession (SS2); Initial Secondary Succession (SS1); Degraded Forest (DG); Poorly Managed Pasture (PP); Well Managed Pasture (WP); Cropland (CR); and Bare Soil and Fallow (BS) ( Table 1).…”

“…To reduce the speckle effect, the matrices were smoothed with the Refined Lee filter [56] ( Figure 2). The filter was selected based on the results from previous studies developed in the same study area using ALOS/PALSAR-1 images [35,38,47]. In this study, the following window sizes were tested: 3 × 3, 5 × 5, 7 × 7, and 9 × 9 pixels.…”

“…The use of ALOS/PALSAR data to monitor forest disturbances and LULC classes has increased in the past years. Pôssa et al [35] evaluated the potential of full polarimetric ALOS/PALSAR-1 scenes to map LULC in the TNF and surroundings by analyzing interferometric coherence and polarimetric attributes. An association of attributes derived by the Cloude-Pottier decomposition and interferometric coherence showed the best classification results, with an overall accuracy (OA) of 78.8% and Kappa index of 0.72.…”

Dinâmica Da Paisagem Da Bacia Hidrográfica Do Rio Itapecuru - Ma

“…Com o propósito de alcançar os objetivos da pesquisa, estrutura-se uma abordagem sistêmica 1 . Os procedimentos técnicos se estruturaram a partir da adaptação das metodologias consolidadas por Mcgarigal e Marks (1995); Rossi et al (2008); Walz (2011); Batista (2014); Meyer (2015) e Pôssa et al (2018). Dessa forma analisa-se a dinâmica da paisagem da BH do rio Itapecuru através de três características fundamentais: composição, estrutura e função 2 .…”