LAUSR

Abstract Airborne gamma-ray spectrometry and altimetric data have been used to recognize lateritic surfaces in southwestern Amazonia, Brazil. Three altimetric surfaces, marked by three main types of lateritic duricrust, comprise the landscape of the studied area. Surface 1 (SP1 ≤ 134 m a.s.l.) is dominated by a deep dissecting U-shaped valley, lowlands, steep slopes, and hills gathering Mn to Mn-Al-Fe duricrusts. Surface 2 (SP2–134 to 186 m a.s.l.) has rounded hills supported by Fe and Fe Al duricrusts. Surface 3 (SP3–186 to 290 m a.s.l.) consists of strongly dissected plateaus to rounded hills sustained by bauxites, massive Fe duricrust, rare Mn-Al-Fe duricrusts, and Mn colluviums. Specifically, all lateritic duricrusts are associated with high values of eTh, and these data were employed in conjunction with SRTM data for generating favorability maps for lateritic surfaces using Boolean and fuzzy techniques. Altimetric data is an important input data in the boolean and fuzzy models since the boolean model overestimated the lateritic surfaces in surface 1, while not considering regional stratigraphic stacking when gathering ironstones as lateritic duricrust (lateritic duricrusts are older than ironstones). Both boolean and fuzzy models successfully recognized the lateritic duricrusts in surfaces 2 and 3 (134–290 m a.s.l.), even though the fuzzy product overestimated the lateritic surfaces above 134 m a.s.l. A lateritic index (LI = (eTh/eU) x K + (eTh x eU)) was also applied as complementary method in relation to the fuzzy and boolean models. LI divided the studied area into three main domains according to weathering intensity (lowest LI, low to intermediate LI, and high to extremely high LI associated with duricrust). Although the LI does not consider the altitude, the obtained model describes areas favorable for lateritic surface occurrences, being a useful and rapid method for preliminary large-scale mapping of lateritic surfaces. Mn duricrusts with K-bearing minerals were also identified by the intersection between F-factor (F K x (eU/eTh)) and eTh fuzzy membership maps. Nevertheless, geological control is important, since protolith influences the F-factor responses. The combination among the eTh fuzzy membership map, ternary map of K, eTh and eU on the RGB channels, the geological and soil map database and some chemical analysis allowed improving future research on supergene deposits as bauxite and manganese duricrusts, phosphorous and gold+sulphides.