Abstract
Widespread in the coastal zones of (sub)tropical regions, mangroves are an essential habitat for many animal species and provide subsistence resources for many human coastal communities. Among remote sensing techniques, synthetic aperture radar is a particularly advantageous method to monitor mangroves: images are not dependent on cloud cover and can provide information from forest understory. This article mapped mangrove forests in the southern coast of São Paulo State (Brazil) using frequency-based contextual classification of incoherent attributes derived from a multi-polarized Phased Array L-Band Synthetic Aperture Radar (PALSAR) image. The use of 10 incoherent attributes and only 3 Synthetic Aperture Radar (SAR) vegetation indices as input for digital classification showed the best accuracies with kappa index values of 0.739 and 0.734, respectively. HH polarization and SAR vegetation indices were the attributes that contributed most to the mangrove mapping procedure. The use of L-Band SAR data was effective for mapping mangrove areas, and therefore it is recommended as a tool for coastal management.
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