Soil surface roughness using cumulated gaussian curvature

Abstract

Optimal use of farming machinery is important for efficiency and sustainability. Continuous automated control of the machine settings throughout the tillage operation requires sensory feedback estimating the seedbed quality. In this paper we use a laser range scanner to capture high resolution maps of soil aggregates in a laboratory setting as well as full soil surface maps in a field test. Gaussian curvature is used to estimate the size of single aggregates under controlled circumstances. Additionally, a method is proposed, which cumulates the Gaussian curvature of full soil surface maps to estimate the degree of tillage.