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Using discrete‐return airborne laser scanning to quantify number of canopy strata across diverse forest types
Author(s) -
Wilkes Phil,
Jones Simon D.,
Suarez Lola,
Haywood Andrew,
Mellor Andrew,
Woodgate William,
SotoBerelov Mariela,
Skidmore Andrew K.
Publication year - 2016
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12510
Subject(s) - canopy , environmental science , laser scanning , tree canopy , remote sensing , ecology , atmospheric sciences , geography , geology , biology , laser , physics , optics
Summary The vertical arrangement of forest canopies is a key descriptor of canopy structure, a driver of ecosystem function and indicative of forest successional stage. Yet techniques to attribute for canopy vertical structure across large and potentially heterogeneously forested areas remain elusive. This study introduces a new technique to estimate the Number of Strata ( NoS ) that comprise a canopy profile, using discrete‐return Airborne Laser Scanning (ALS) data. Vertically resolved gap probability ( P gap ) aggregated over a plot is generalized with a nonparametric cubic spline regression ( P s ). Subsequently a count of the positive zero‐crossings of second derivative of 1 − P s is used to estimate NoS . Comparison with inventory derived estimates at 24 plots across three diverse study areas shows a good agreement between the two techniques (RMSE = 0·41 strata). Furthermore, this is achieved without altering model parameters, indicating the transferability of the technique across diverse forest types. NoS values ranged from 0 to 4 at a further 239 plots, emphasizing the need for a method to quantify canopy vertical structure across forested landscapes. Comparison of NoS with other commonly derived ALS descriptors of canopy structure (canopy height, canopy cover and return height coefficient of determination) returned only a moderate correlation ( r 2 < 0·4). It is proposed the presented method provides a primary descriptor of canopy structure to complement canopy height and cover, as well as a candidate Ecological Biodiversity Variable for characterizing habitat structure.