Automated Detection of Forest Gaps in Spruce Dominated Stands Using Canopy Height Models Derived from Stereo Aerial Imagery

Zielewska-Büttner, Katarzyna; Adler, Petra; Ehmann, Michaela; Braunisch, Veronika (2016). Automated Detection of Forest Gaps in Spruce Dominated Stands Using Canopy Height Models Derived from Stereo Aerial Imagery. Remote sensing, 8(3), p. 175. Molecular Diversity Preservation International MDPI 10.3390/rs8030175

[img]
Preview
Text
Zielewska-Büttner_RemSen2016.pdf - Published Version
Available under License Creative Commons: Attribution (CC-BY).

Download (3MB) | Preview

Forest gaps are important structural elements in forest ecology to which various conservation-relevant, photophilic species are associated. To automatically map forest gaps and detect their changes over time, we developed a method based on Digital Surface Models (DSM) derived from stereoscopic aerial imagery and a LiDAR-based Digital Elevation Model (LiDAR DEM). Gaps were detected and delineated in relation to height and cover of the surrounding forest comparing data from two public flight campaigns (2009 and 2012) in a 1023-ha model region in the Northern Black Forest, Southwest Germany. The method was evaluated using an independent validation dataset obtained by visual stereo-interpretation. Gaps were automatically detected with an overall accuracy of 0.90 (2009) and 0.82 (2012). However, a very high producers’ accuracy of more than 0.95 (both years) was counterbalanced by a user’s accuracy of 0.84 (2009) and 0.73 (2012) as some gaps were not automatically detected. Accuracy was mainly dependent on the shadow occurrence and height of the surrounding forest with user’s accuracies dropping to 0.70 (2009) and 0.52 (2012) in high stands (>8 m tree height). As one important step in the workflow, the class of open forest, an important feature for many forest species, was delineated with a very good overall accuracy of 0.92 (both years) with uncertainties occurring mostly in areas with intermediate canopy cover. Presence of complete or partial shadow and geometric limitations of stereo image matching were identified as the main sources of errors in the method performance, suggesting that images with a higher overlap and resolution and ameliorated image-matching algorithms provide the greatest potential for improvement.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Biology > Institute of Ecology and Evolution (IEE)
08 Faculty of Science > Department of Biology > Institute of Ecology and Evolution (IEE) > Conservation Biology

UniBE Contributor:

Braunisch, Veronika

Subjects:

500 Science > 570 Life sciences; biology

ISSN:

2072-4292

Publisher:

Molecular Diversity Preservation International MDPI

Language:

English

Submitter:

Olivier Roth

Date Deposited:

18 Jul 2017 07:48

Last Modified:

18 Jul 2017 07:48

Publisher DOI:

10.3390/rs8030175

BORIS DOI:

10.7892/boris.93871

URI:

https://boris.unibe.ch/id/eprint/93871

Actions (login required)

Edit item Edit item
Provide Feedback