Methods for separating orchards from forest using airborne LiDAR

Abstract

• Key message: The aim of the study was to distinguish orchards from other lands with forest vegetation based on the data from airborne laser scanning. The methods based on granulometry provided better results than the pattern analysis. The analysis based on the Forest Data Bank/Cadastre polygons provided better results than the analysis based on the segmentation polygons. Classification of orchards and other areas with forest vegetation is important in the context of reporting forest area to international organizations, forest management, and mitigating effects of climate change. • Context: Agricultural lands with forest vegetation, e.g., orchards, do not constitute forests according to the forest definition formulated by the national and international definitions, but contrary to the one formulated in the Kyoto Protocol. It is a reason for the inconsistency in the forest area reported by individual countries. • Aims: The aim of the study was to distinguish orchards from other lands with forest vegetation based on the data from airborne laser scanning. • Methods: The study analyzed the usefulness of various laser scanning products and the various features of pattern and granulometric analysis in the Milicz forest district in Poland. • Results: The methods based on granulometry provided better results than the pattern analysis. The analysis based on the Forest Data Bank/Cadastre polygons provided better results than the analysis based on the segmentation polygons. • Conclusion: Granulometric analysis has proved to be a useful tool in the classification of orchards and other areas with forest vegetation. It is important in the context of reporting forest area to international organizations, forest management, and mitigating effects of climate change.