Assessing soil degradation in Brazilian agriculture by a remote sensing approach to monitor bare soil frequency: impact on soil carbon

Abstract

In countries with extensive agricultural practices, there is a significant risk of soil degradation, making it essential to develop techniques for understanding and detecting these changes. In this study, we used an earth observation system to identify the temporal bare soil frequency and thus, relate it with soil tillage and its impact on soil carbon degradation. The work was performed in two important agricultural states of Brazil, São Paulo and Paraná. For that, historical field and Remote Sensing (RS) data were analyzed to identify the relation between bare soil areas and their degradation. The frequency of bare soil was detected by Landsat images, in the last 36 years using the Geospatial Soil Sensing System (GEOS3). Historical soil surface temperature data was produced using the same images. In addition, legacy pedological and crops (i.e., soil cover) maps were used. Finally, soil texture information was spatialized based on a synthetic soil image (SISY). A total of 28,000 sites with topsoil organic carbon (SOC) were used as the reference for degradation. The soils of the state of Paraná presented significantly lower bare soil areas when compared to the state of São Paulo, mainly due to the wide use of the No-Tillage system. The advancement of sugarcane harvesting technologies together with the "boom" of the commodities after 2000s was responsible for the considerable increases in soil cover conservation. It was noticed that the more exposed the soil remains, the less carbon it has, having a negative correlation (r≈ −0.5). Sandy soils in both states proved to be the ones that were subject to the highest exposure rates and thus, more degraded. This fact is of concern, given that sandy soils are more susceptible to degradation factors, such as erosion. We observed important historical public policies related to the temporal tillage systems adopted by agro-community, which had a significant impact on carbon dynamics. The remote technique was able to infer how the soil has been managed. This information is crucial as it provides a solid basis for developing future public policies aimed at sustainable production.