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Uncrewed aircraft system spherical photography for the vertical characterization of canopy structural traits
Author(s) -
Ribas Costa Vicent Agustí,
Durand Maxime,
Robson T. Matthew,
PorcarCastell Albert,
Korpela Ilkka,
Atherton Jon
Publication year - 2022
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.17998
Subject(s) - canopy , remote sensing , environmental science , photography , lidar , tree canopy , trait , picea abies , geography , botany , biology , computer science , art , visual arts , programming language
Summary The plant area index (PAI) is a structural trait that succinctly parametrizes the foliage distribution of a canopy and is usually estimated using indirect optical techniques such as digital hemispherical photography. Critically, on‐the‐ground photographic measurements forgo the vertical variation of canopy structure which regulates the local light environment. Hence new approaches are sought for vertical sampling of traits. We present an uncrewed aircraft system (UAS) spherical photographic method to obtain structural traits throughout the depth of tree canopies. Our method explained 89% of the variation in PAI when compared with ground‐based hemispherical photography. When comparing UAS vertical trait profiles with airborne laser scanning data, we found highest agreement in an open birch ( Betula pendula / pubescens ) canopy. Minor disagreement was found in dense spruce ( Picea abies ) stands, especially in the lower canopy. Our new method enables easy estimation of the vertical dimension of canopy structural traits in previously inaccessible spaces. The method is affordable and safe and therefore readily usable by plant scientists.