Estimation of Soil Organic Matter from Red and Near‐Infrared Remotely Sensed Data Using a Soil Line Euclidean Distance Technique

Abstract

The soil line is a well‐known linear relationship between the near‐infrared and red reflectance or image intensity of bare soil images. Remotely sensed estimations of soil surface properties can lead to improved representation of spatial heterogeneity. The objectives of this research are to develop an approach based on image soil lines that incorporates image intensity in the red and near‐infrared bands for mapping surface organic matter (OM) and to provide guidance for soil sampling. The soil line concept is used to develop predictive relationships between the amount of OM within the surface horizon of the soil profile and intensity in the red and near‐infrared bands. The soil line Euclidean distance (SLED) technique is based on relating a pixel's Euclidean distance of the red and near‐infrared intensity value to the red and near‐infrared intensity value for the bottom‐most point on the soil line. The technique is evaluated for two fields in the U.S. Midwest. The technique performs as well as or better than a recently proposed technique, while at the same time relating to the parent material (i.e., soil series) within the field. A technique for significantly reducing the number of soil samples required in grid sampling is also introduced and evaluated. This technique utilizes pixels at various percentile locations along the soil line to characterize the predictive relationship between percentage surface OM and image intensity.