Seasonal variations in the backscatter of RADARSAT-1 images in tropical coastal environments

Abstract

Understanding the variability in synthetic aperture radar (SAR) backscatter as a function of the phenological variability of vegetation and tropical environmental conditions is still a challenge. Through quantitative and qualitative analyses, this study addresses how both environmental and precipitation conditions, tidal range, and vegetation density affect the backscatter coefficients of coastal environments based on the analysis of four C-band, HH-Polarization, RADARSAT-1 Wide 1 images, in descending orbit, acquired in the wet and dry seasons. The canopy structural variations were analyzed using the enhanced vegetation index (EVI), and correlated with the backscatter values of SAR images, in order to define the predominant backscatter mechanisms, making it possible to distinguish the mangroves from the brackish marshes in the easternmost Amazon coastal plain (Caranguejos Island). The C-band, HH-Polarization RADARSAT-1 backscatter shows the highest correlation with average EVI values in the dry season. The results show that mangroves and brackish marshes can be distinguished in images acquired under low precipitation, especially in the dry season. Variations in the tidal conditions have no effect on the backscatter values of RADARSAT-1 images. We conclude, therefore, that multitemporal RADARSAT-1 images are adequate for monitoring and discriminating wetland environments in a humid tropical climate.

KEYWORDS:
synthetic aperture radar; backscatter coefficient; enhanced vegetation index; automatic classification; coastal environments