Florian Hartig Theoretical Ecology & Ecological Data Science

← Publications

Estimating over- and understorey canopy density of temperate mixed stands by airborne LiDAR data

Hooman Latifi, Marco Heurich, Florian Hartig, Jörg Müller, Peter Krzystek, Hans Jehl, Stefan Dech

Forestry, 89(1), 69–81 (2015)
Cite this
@article{latifi2015assessing,
  author = {Hooman Latifi and Marco Heurich and Florian Hartig and Jörg Müller and Peter Krzystek and Hans Jehl and Stefan Dech},
  title = {Estimating over- and understorey canopy density of temperate mixed stands by airborne LiDAR data},
  journal = {Forestry},
  volume = {89},
  number = {1},
  pages = {69–81},
  year = {2015},
  doi = {10.1093/forestry/cpv032},
}

DOI: 10.1093/forestry/cpv032
Cited by 96 (Google Scholar) · 78 (OpenAlex), as of 07 September 2026

View article (DOI)

Abstract

Estimating forest structural attributes is one of the essential forestry-related remote sensing applications. The methods applied so far typically concentrate on the structure of the overstorey. For various conservation and management applications, however, information on lower layers is also of great interest. Detecting understorey cover by remote sensing is challenging, as passive sensors do not penetrate to the ground layer. An alternative to these is 3D metrics from airborne light detection and ranging (LiDAR). Here, we evaluate this technique for describing the vegetation density of multiple stand layers within temperate stands of a large protected area in south-eastern Germany. We combined LiDAR metrics and habitat types with regression models to investigate which LiDAR metrics are significantly correlated with vegetation density. The top canopy and herb layer showed strong correlations with the metrics, whereas the predictive power was lower for intermediate stand layers. Moreover, our results suggest that the relationship between LiDAR predictors and vegetation depends on forest type. In conclusion, this study highlights the value of characterizing forest properties of lower layers, which has implications for wildlife management, especially in protected areas.

What the paper shows and why it matters (AI-generated)

Passive remote sensors can map a forest's top canopy easily enough, but they can't see through it to the understorey — information conservation managers in protected areas specifically need. This study shows airborne LiDAR's 3D point-cloud metrics can fill that gap, correlating strongly with vegetation density in both the top canopy and herb layer, though less reliably for the intermediate layers in between and depending on forest type. It's become a standard reference point for later LiDAR forest-structure work, still being cited in vertical-heterogeneity and growing-stock-volume studies a decade on.