Mapping iron-mineralized laterite environments based on textural attributes from MAPSAR image simulation - SAR-R99B (SIVAM/SIPAM) in the Amazon region

Abstract

The use of remote sensing is a valuable method for geological mapping as it provides synoptic coverage at relatively low cost. In the Amazon region, radar imagery has a potential for geological applications due the enhanced sensitivity to topography (macrotopography), surface roughness (microtopography), and dielectric properties of materials, independent of weather, sun angle, and illumination conditions. As the roughness is highlighted, SAR textural attributes can be used for mapping iron-ore mineralized laterites in N1 deposit, located in the Carajás Province. For mapping the lateritic cover, the airborne SAR was used from Surveillance of the Amazon System (SIVAM/SIPAM, L-hh, L-hv, L-vv) to simulate orbital Multi-Application Purpose SAR (MAPSAR). The images were analyzed through textural classifications derived from second-order measure (GLCM) with the objective of mapping the mineralized laterites for iron ore. Differences are highlighted when comparing the classified maps and the ground information. Not all classes were separated, but a high performance for textural attributes was presented by the hematite class. This class was sensitive to the sensor and target parameters, especially macrotopography and physics characteristics. The results showed that for mineral exploration, the radar images at L-band can be used as a practical tool for a preliminary mapping, and as a guide for field-based verification. © 2011 Sociedade Brasileira de Geofísica.