Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data

By Marc Bouvier, Sylvie Durrieu, Richard A. Fournier, Jean-Pierre Renaud. 2015

349 citations recorded by the source corpus.

Subfields: Environmental Engineering, Insect Science, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/732b67d721614e92d3b52002d27b03ae51cb339a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Shelley A. Hinsley
2. Ross A. Hill
3. M. Sumnall

In Insect Science

1. Shelley A. Hinsley
2. Ross A. Hill
3. M. Sumnall

In Nature and Landscape Conservation

1. Shelley A. Hinsley
2. Ross A. Hill
3. M. Sumnall

Citations in the corpus

• Comparison of small-footprint discrete return and full waveform airborne lidar data for estimating multiple forest variables (2016, methodology): “Plot- or stand-level regression analysis or non-103 parametric model estimates of canopy density, mean tree height, basal area and volume have 104 been applied (Bouvier et al. 2015; Hyyppä et al., 2008; Næsset, 2007).”