Geostatistics in Soil Science: A Comprehensive Review on Past, Present and Future Perspectives

Soil science, a crucial discipline at the intersection of complex terrestrial processes, is critical to address global challenges like food security and environmental sustainability. Geostatistics has emerged as a powerful tool, providing insights into soil property spatial variability for informed decision-making in agriculture, land management, and environmental stewardship. This review thoroughly examines the evolution, status and future prospects of geostatistics in soil science. The paper starts by tracing geostatistics’ roots in soil science, originating in the 1980s, and underscores its role in characterizing soil property spatial distributions. Foundational principles like semivariogram and kriging provide context for the evolution of geostatistical applications. The paper then delves into contemporary applications from precision agriculture to digital soil mapping, soil health monitoring and risk assessment, offering spatially explicit data essential for optimizing land resource utilization. Despite its transformative impact, challenges persist, including the proliferation of interpolation techniques and the search for the optimal approach. While hybrid techniques like kriging with an external drift and regression kriging enhance accuracy, a universally superior method remains elusive. The paper concludes with a resounding call to action, advocating for the ongoing development, comparative assessment and flexible use of geostatistical methods and models, in synergy with emerging machine learning techniques. This collective effort aims to illuminate the most suitable techniques for diverse scenarios, ensuring precision in predicting complex soil properties and variables. Geostatistics emerges as the cornerstone for unraveling soil spatial variabilities, indispensable for the future of agriculture and environmental stewardship in an age where soil science meets cutting-edge technology.