Compiled by: Michelle Cleary, Axelina Jonsson, Henrik Johansen, Alice Penanhoat, Tage Rosenqvist, Hampus Jörning, Langning Huo
Introduction
Detecting Phytophthora-infected trees in the field is a time-consuming process. Remote sensing, particularly using multispectral imagery, provides an efficient alternative for assessing tree health and detecting stress symptoms associated with disease and vitality loss. The objective of project tasks T3.4.1. and T4.5 is to develop and validate methods for detecting Phytophthora-infected trees from drone-based multispectral data. The nine spectral bands, capturing information across the visible and near-infrared range, will be used to calculate vegetation indices sensitive to canopy stress and defoliation. The high spatial resolution of the multispectral imagery (around 10 cm/pixel) enables detection and monitoring at the individual tree-crown scale.