INTERACTIVE DIGITAL TERRAIN MODEL ANALYSIS IN ATTRIBUTE SPACE
Keywords: Pattern Spectra, LiDAR, DTM, mathematical morphology
Abstract. The use of high-resolution digital terrain model derived from airborne LiDAR system becomes more and more prevalent. Effective multi-scale structure characterization is of crucial importance for various domains such as geosciences, archaeology and Earth observation. This paper deals with structure detection in large datasets with little or no prior knowledge. In a recent work, we have demonstrated the relevance of hierarchical representations to enhance the description of digital elevation models (Guiotte et al., 2019). In this paper, we proceed further and use the pattern spectrum, a multi-scale tool originating from mathematical morphology, further enhanced by hierarchical representations. The pattern spectra allow to globally and efficiently compute the distribution of size and shapes of the objects contained in a digital elevation model. The tree-based pattern spectra used in this paper allowed us to analyse and extract features of interest. We report experiments in a natural environment with two use cases, related to gold panning and dikes respectively. The process is fast enough to allow interactive analysis.