Back to Search Start Over

Robust processing of airborne laser scans to plant area density profiles

Authors :
Johan Arnqvist
Julia Freier
Ebba Dellwik
Publica
Source :
Biogeosciences, Vol 17, Pp 5939-5952 (2020), Arnqvist, J, Freier, J & Dellwik, E 2020, ' Robust processing of airborne laser scans to plant area density profiles ', Biogeosciences, vol. 17, no. 23, pp. 5939-5952 . https://doi.org/10.5194/bg-17-5939-2020
Publication Year :
2020
Publisher :
Copernicus Publications, 2020.

Abstract

We present a new algorithm for the estimation of plant area density (PAD) profiles and plant area index (PAI) for forested areas based on data from airborne lidar. The new element in the algorithm is to scale and average returned lidar intensities for each lidar pulse, whereas other methods either do not use the intensity information at all, only use average intensity values or do not scale the intensity information, which can cause problems for heterogeneous vegetation. We compare the performance of the new and three previously published algorithms over two contrasting types of forest: a boreal coniferous forest with a relatively open structure and a dense beech forest. For the beech forest site, both summer (full leaf) and winter (bare trees) scans are analyzed, thereby testing the algorithm over a wide spectrum of PAIs. Whereas all tested algorithms give qualitatively similar results, absolute differences are large (up to 400 % for the average PAI at one site). A comparison with ground-based estimates shows that the new algorithm performs well for the tested sites, and further and more importantly – it never produces clearly dubious results. Specific weak points for estimation of PAD from airborne lidar data are addressed; the influence of ground reflections and the effect of small-scale heterogeneity, and we show how the effect of these points is minimized using the new algorithm. We further show that low-resolution gridding of PAD will lead to a negative bias in the resulting estimate according to Jensen’s inequality for concave functions, and that the severity of this bias is method-dependent. As a result, PAI magnitude as well as heterogeneity scales should be carefully considered when setting the resolution for PAD gridding of airborne lidar scans.

Details

Language :
English
ISSN :
17264189 and 17264170
Volume :
17
Database :
OpenAIRE
Journal :
Biogeosciences
Accession number :
edsair.doi.dedup.....30e18ffca4ae872f4be5416b79713c00
Full Text :
https://doi.org/10.5194/bg-17-5939-2020