Detection of forest canopy gaps from very high resolution aerial images

Abstract

In Europe, assessment of the ecological function of forests is increasingly important as evidenced by Natura 2000, which has seen the establishment of protected sites that are of ecological importance. The presence of canopy gaps has proved to be a useful indicator of the forest structure and biodiversity in these areas.Two methods – Object Based Image Analysis (OBIA) and Image Texture Based Analysis (ITBA) – were assessed to detect and quantify canopy gaps and to investigate the influence of forest type on their performance. The research was undertaken in two Natura 2000 sites in Bulgaria. To estimate the gap fractions in the field, 100 square plots (150 m by 150 m) were established. Within each plot, 25 circular sub-plots were laid out in a regular pattern. Gap size within each sub-plot was estimated visually.The methods were assessed using very high-resolution (0.13 m ground resolution) aerial imagery. For the OBIA method, five parameter settings were tested and the gap fractions estimated on the imagery and compared with the field estimates. Likewise, for the ITBA method, five different settings were tested. In general, both methods overestimated canopy gap fraction relative to the field-based estimates, especially where the gap fractions were relatively small. Larger gaps were more accurately estimated by the OBIA method. Neither method performed well in broadleaved forest. Statistical comparison showed that, overall, the correlations of the estimates from the imagery with field data are only moderate and that there is no significant difference between the two methods.