Parameters Influencing Forest Gap Detection Using Canopy Height Models Derived From Stereo Aerial Imagery

Gaps in the canopy are important elements for forest biodiversity. We developed a method based on Canopy Height Models (CHMs) derived from stereoscopic aerial imagery and a LiDAR-based Digital Terrain Model (LiDAR DTM) to automatically delineate forest gaps in relation to height and cover of the surrounding forest. To evaluate the factors affecting the mapping accuracy, we compared the results from three different flight campaigns (2009, 2012 and 2014) in a 1021-ha model region in the Black Forest, Southwestern Germany. The public campaigns of 2009 and 2012 were taken with an overlap of 60% within stripe and 30% between stripes and an overall resolution on ground of 20cm. Data from 2014 had a 10cm resolution and an overlap of 80% within stripe and 60% between stripes. The validation was done by visual stereo-interpretation. Shadow occurrence and geometric limitations of the stereo aerial imagery were identified as main error sources.

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