Multispectral indices and individual-tree level attributes explain forest productivity in a pine clonal orchard of Northern Mexico

Multispectral indices are useful to improve the knowledge of plant organic functionality. Geographically weighted regression (GWR), multispectral data from unmanned aerial vehicles (UAVs) and individual tree attributes were used in combination to generate forest parameters in an even-aged orchard of...

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Bibliographic Details
Published in:Geocarto international 2022-08, Vol.37 (15), p.4441-4453
Main Authors: Gallardo-Salazar, José L., Carrillo-Aguilar, Daniela M., Pompa-García, Marín, Aguirre-Salado, Carlos A.
Format: Article
Language:English
Subjects:
DJI Phantom 4 multispectral
NDVI
Pinus clonal orchard
UAV
vegetation health
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Summary:Multispectral indices are useful to improve the knowledge of plant organic functionality. Geographically weighted regression (GWR), multispectral data from unmanned aerial vehicles (UAVs) and individual tree attributes were used in combination to generate forest parameters in an even-aged orchard of Pinus arizonica Engelm. The NDVI index was the best indicator of vegetation vigour, correlated to diameter at breast height (DBH) and total estimated tree height (UAVe) as explanatory variables. Geospatial models explained the variance of orchard vigour (R 2 = 39 for DBH and R 2 = 52 for UAVe), suggesting the crucial requirement for individual or zonal management of the trees. Our results thus provide timely indicators of plant health conditions in the clonal orchard that may be useful for adaptive management strategies in the face of predicted climatic change.
ISSN:1010-6049
1752-0762
DOI:10.1080/10106049.2021.1886341