| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4572999 | Geoderma | 2016 | 12 Pages |
•Airborne spectrometric, and relief data was integrated to identify lateritic crust.•Boolean and fuzzy techniques were compared and used to classify favorable areas.•Both models showed good correlation with soil and geologic maps.•The index overlay method showed 8 classes of laterite favorability with kappa 0.87.•Fuzzy model using fuzzy gamma operator 0.7 showed the best kappa value of 0.91.
Airborne gamma-ray spectrometry is relatively well understood when associated with rocks, but the response and radioelement distribution in weathered materials is less known. This work used airborne gamma-ray spectrometry and altimetry to identify domains with higher probability of occurrence of lateritic crust and dismantling products in an area located in the west of the Brazilian Amazon. Map algebra was used through the Boolean and fuzzy techniques to create predictability digital models highlighting favorable areas for the occurrence of lateritic crusts. The Index Overlay Method was used in the Boolean technique. The fuzzy technique used the fuzzy algebraic product operator, fuzzy algebraic sum operator, and fuzzy gamma operator. Both models showed good correlation between the favorability predicted and the presence of crusts in the field, however, the fuzzy model showed higher correlation and highlighted areas not identified by the Boolean model. In contrast, the Boolean model allowed the visualization of the areas related to the influence of each variable or its possible combinations individually on the final map. Thus, the identification of lateritic crusts based on mathematic models applied to altimetric and airborne gamma-ray spectrometric data is a new tool that will contribute significantly to geological mapping and to the understanding related to the response and radioelement distribution in weathered materials.
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