Filling the soil data gap

Abstract:

Today's data-driven agriculture demands access to high-resolution spatial and temporal data streams. Soil scientists in the United States and globally have been struggling to meet this demand. While advances in remote sensing have enabled fundamental advances in understanding agronomic performance and production constraints, measurement of the soil still largely relies on shovels and benchtop analytical methods. Diffuse reflectance spectroscopy can help fill the soil data gap by providing a rapid and low-cost alternative to traditional laboratory analysis. National and international initiatives both in the public and private sectors have now built large spectral libraries that can be utilized to make routine estimates of a range of soil properties. At the same time, advances in data science have made it easier to fully exploit the information contained in diffuse reflectance spectra resulting in better estimates of a larger range of soil properties. In this presentation, we provide an overview of the potential and current limitations of diffuse reflectance mid infrared spectroscopy for estimating a range of soil properties and discuss how this information can be applied for improved decision making. Matching information on soils with the spatial and temporal density of remote sensing data is a challenge but if successful, the pairing of crop and soil data would usher in a new era of Smart Farming.