Automatic clod detection and boundary estimation from Digital Elevation Model images using different approaches

Soil micro-topography characterization is an important issue for both soil science and remote sensing data interpretation. The objective of present study is to propose and discuss some methods dedicated to the automatic localization of clods (or big aggregates) on Digital Elevation Model images of soil. Two new image processing methods are introduced. The first one deals with the clod detection and the rough estimation of their boundaries. It is based on the adaptation of a famous segmentation algorithm applied to a modified surface enhancing the main features characterizing the clods. The second proposed method deals with the accurate estimation of clod boundaries. Clod boundaries are moved based on dynamic programming. Both proposed methods are validated on laboratory-built surfaces and on an actual surface recorded in an agricultural field. Results show that the proposed methods outperformed previously published methods. The proposed processing of DEM images allows the detection of the aggregates and clods deposited on the soil surface and the accurate estimation of their boundaries. The practice is facilitated by the proposition of default values for the parameters. The implications are the automatic analysis of DEM images that is a step towards micro-topography statistical characterization.