Remote sensing imagery detects hydromorphic soils hidden under agriculture system

Abstract

The pressure for food production has expanded agriculture frontiers worldwide, posing a threat to water resources. For instance, placing crop systems over hydromorphic soils (HS), have a direct impact on groundwater and influence the recharge of riverine ecosystems. Environmental regulations improved over the past decades, but it is difficult to detect and protect these soils. To overcome this issue, we applied a temporal remote sensing strategy to generate a synthetic soil image (SYSI) associated with random forest (RF) to map HS in an 735,953.8 km2 area in Brazil. HS presented different spectral patterns from other soils, allowing the detection by satellite sensors. Slope and SYSI contributed the most for the prediction model using RF with cross validation (accuracy of 0.92). The assessments showed that 14.5% of the study area represented HS, mostly located inside agricultural areas. Soybean and pasture areas had up to 14.9% while sugar cane had just 3%. Here we present an advanced remote sensing technique that may improve the identification of HS under agriculture and assist public policies for their conservation.

Fine scale mapping of phosphorus stocks in brazilian soils by geotechnologies: implications for a sustainable agriculture

“…GEOS3 is fed with the entire historical series of Landsat images and outputs a synthetic soil image (SYSI) composed of pixels that represent the soil reflectance at a time when it was uncovered. The SYSI represents a direct measure of the soil and has a high correlation with various soil properties , being used as a proxy for DSM in several studies (Gómez et al, 2023;Mello et al, 2023;Rosin et al, 2023;. Furthermore, due to the correlation between various soil properties, they can also be used as environmental covariates .…”