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Título

ASSESSING SOIL POTENTIAL PRODUCTIVITY IN AREAS WITH PASTURELANDS THROUGH EARTH OBSERVATION TECHNIQUES

Resumo

Pasture areas occupy an extensive part of the Brazilian territory, generating discussion about whether they can be converted to agriculture. However, debaters usually do not include relevant topics like soil potential to support agriculture in the discussion. Therefore, we aimed to quantify soil potential productivity (SOILPP) in Brazilian pasturelands from 1990 to 2020 using geotechnologies. For that, we crossed a SOILPP (source GeoCis) with the pasture area (source MapBiomas) and the pasture quality map (source LAPIG/UFG) to support our argumentation. It is noteworthy to mention that SOILPP starts from the premise that soil name, texture, fertility, water-holding capacity, depth, and climate are pillars of soil productivity that determine the local productive potential. Such pillars generate classes from A, for the best, to G, for the worst productivity potential. Thus we could assess the land use suitability by overlapping information through the Brazilian biomes according to their characteristics. The pasturelands concentrated in the Cerrado, comprising environments from D to F, amounting to about 20%, in 1990, which increased the SOILPP D class in 2020 and decreased in E and F environments. On the one hand, the areas with pasture increased (8%) in productive regions of the Amazon biome, on the other they decreased in weaker soils (8%). The Pampas biome presented an increase in suitable environments by 18%. Even though the pasture areas occupy the better SOILPP classes, they are at an intermediate or severe degradation degree. This fact is harmful because fragile environments (E, F, and G) can worsen soil health, reducing the capacity to sustain this culture or becoming unproductive. In addition, part of the pasture areas under environments from A to D could be changed to crops, increasing Brazilian food production capacity and avoiding the deforestation of new cultivation areas.

Palavras-chave

Remote Sensing; Soil Potential Production; Pasture Quality; Biome; Soil Health.

Instituição financiadora

This paper was granted by The State of São Paulo Research Foundation (FAPESP) (2022/11034-2; 2021/05129-8)

Agradecimentos

The authors thanks to GeoCis Research Group for sampling and analyses