Effectiveness of proximal and remote sensing to trace soils spatial variability: A study case in a Brazilian Cerrado coffee farm

Abstract

ABSTRACT Brazil has made notable advances in soil mapping compared to other Latin American countries, driven by collaborative efforts from federal agencies, research institutions, and universities. However, detailed soil maps remain limited, particularly at local scales. This study explored soil spatial variability in a coffee plantation located in the Brazilian Cerrado, assessing the effectiveness of integrating proximal and remote sensing data to create detailed soil maps that support precision agriculture. Soil samples were collected from multiple depths across the study area and analyzed for texture, fertility, and elemental composition using portable X-ray fluorescence (pXRF). Additionally, terrain attributes derived from a digital elevation model were examined to understand their relationship with soil properties. Our results demonstrated that elements associated with parent material, such as Fe, Si, Ti, Al, and Ca, were more reliable indicators for distinguishing soil classes than topographic features. The dominance of Cambissolos Háplicos (CX), which have lower clay content and contain gravel, suggested a reduced need for soil amendments compared to Latossolos Vermelhos (LV), leading to potential cost savings for producers. These findings underscore the utility of pXRF in detecting soil variability and emphasize that combining proximal and remote sensing data can enhance the efficiency and sustainability of agricultural management.

Keywords

• Terrain attributes
• portable X-ray fluorescence spectroscopy
• parent material