Effectiveness of SRTM and ALOS-PALSAR data for identifying morphostructural lineaments in northeastern Brazil

Abstract

This work provides a comparison between ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) and DEM (Digital Elevation Model) SRTM (Shuttle Radar Topography Mission) data aiming to evaluate their efficiency to detect morphostructural lineaments. An area in Northeastern Brazil was selected to perform this investigation because of its unambiguous evidence of tectonic fault activity from the Precambrian to the Quaternary. DEM enhanced by shading schemes and palettes was integrated with images representative of morphometric variables as aspect and horizontal curvature in order to enable the recognition of linear features. Images derived from HIS transformation and arithmetic operations of fine beam dual (HH+HV) polarization PALSAR images were processed to provide RGB compositions. Comparisons among lineament maps based on these two remote-sensing products attest to the highest efficacy of SRTM data in detecting geologically meaningful lineaments in the study area. These indicate a main E–W trend and secondary, NE–SW and NW–SE trends, which conform to dominant directions of tectonic fault zones previously mapped in northeastern Brazil. Geomorphological and geological field investigations carried out in the course of the current research further contributed to showing the best performance of this product for unravelling details of three expressive tectonic structures in the study area. This study shows that lineament attenuation in PALSAR images augments proportionally with increased land use. Other important interferences that either rule out or significantly attenuate linear structures are imposed by natural characteristics of the L-band PALSAR sensor, including layover and high-look azimuth in equatorial latitude. The latter might have particularly attenuated detection of lineaments parallel to illumination azimuth. Taking into account these interferences in PALSAR images, integration of DEM-SRTM data used herein offers a much more robust tool to help carry out morphostructural studies in terrains displaying characteristics similar to the ones in the study area.