The global demand for food production has led to the expansion of agricultural frontiers, posing a significant threat to water resources. One such threat is the impact of crop systems on hydromorphic soils (HS), which directly affect groundwater and influence the recharge of riverine ecosystems. Despite improvements in environmental regulations, detecting and protecting these soils remains a challenge. A recent Mello et al. (2023) study presents a novel solution using advanced remote sensing techniques.
The researchers applied a temporal remote sensing strategy to generate a synthetic soil image (SYSI), which was then used with a random forest (RF) model to map HS across a vast area of 735,953.8 km2 in Brazil. The study found that HS exhibited different spectral patterns from other soils, making them detectable by satellite sensors. The slope and SYSI were the most significant contributors to the RF prediction model, which achieved an accuracy 0.92 through cross-validation.
The study revealed that 14.5% of the area represented HS, with the majority located within agricultural areas. Soybean and pasture areas contained up to 14.9% HS, while sugarcane areas contained just 3%.
The findings of this study are significant as they present an advanced remote sensing technique that can improve the identification of HS under agriculture. This could assist in developing public policies aimed at conserving these vital soils. The study underscores the importance of using advanced technologies in addressing environmental challenges and ensuring sustainable agricultural practices.
