Comparison of six individual tree crown detection algorithms evaluated under varying forest conditions

Abstract

In this article, six individual tree crown (ITC) detection/delineation algorithms are evaluated, using an image data set containing six diverse forest types at different geographical locations in three European countries. The algorithms use fundamentally different techniques, including local maxima detection, valley following (VF), region-growing (RG), template matching (TM), scale-space (SS) theory and techniques based on stochastic frameworks. The structurally complexity of the forests in the aerial images used ranges from a homogeneous plantation and an area with isolated tree crowns to an extremely dense deciduous forest type. None of the algorithms alone could successfully analyse all different cases. The study shows that it is important to partition the imagery into homogeneous forest stands prior to the application of individual tree detection algorithms. It furthermore suggests a need for a common, publicly available suite of test images and common test procedures for evaluation of individual tree detection/delineation algorithms. Finally, it highlights that, for complex forest types, monoscopic images are insufficient for consistent tree crown detection, even by human interpreters.

Acknowledgements

This work was partially funded by ARC MODE de VIE collaborative project at INRIA.

The authors would like to thank the French Forest Inventory (IFN), the Centre for Image Analysis (CBA) in Uppsala (Sweden), and the department of Basic Sciences and Environment at the Faculty of Life Sciences at the University of Copenhagen (Denmark) for providing the images.

The authors are grateful for the interpretation of images provided by Péter Horváth at ARIANA, INRIA Sophia Antipolis, France (four images), Malin Enberg at Dianthus AB, Boden, Sweden (one image) and Michael Gottlieb at the Faculty of Life Sciences of the University of Copenhagen, Denmark (one image). Other interpretations (14 total) were done by the authors.

Ground reference data for the image Offnadir was provided by Ib Holmgård Sørensen, Danish Forest and Landscape Research Institute, Vejle, Denmark.