Classification of Defoliated Trees Using Tree-Level Airborne Laser Scanning Data Combined with Aerial Images

Tuula Kantola,Xiaowei Yu,Sanna Kaasalainen,Svein Solberg,Juha Hyyppa,Paivi Lyytikainen-Saarenmaa,Mervi Talvitie,Mikko Vastaranta,Markus Holopainen

doi:10.3390/rs2122665

Tuula Kantola, Xiaowei Yu + Show 7 more

Open Access

https://doi.org/10.3390/rs2122665

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Abstract

Climate change and rising temperatures have been observed to be related to the increase of forest insect damage in the boreal zone. The common pine sawfly (Diprion pini L.) (Hymenoptera, Diprionidae) is regarded as a significant threat to boreal pine forests. Defoliation by D. pini can cause severe growth loss and tree mortality in Scots pine (Pinus sylvestris L.) (Pinaceae). In this study, logistic LASSO regression, Random Forest (RF) and Most Similar Neighbor method (MSN) were investigated for predicting the defoliation level of individual Scots pines using the features derived from airborne laser scanning (ALS) data and aerial images. Classification accuracies from 83.7% (kappa 0.67) to 88.1% (kappa 0.76) were obtained depending on the method. The most accurate result was produced using RF with a combination of data from the two sensors, while the accuracies when using ALS and image features separately were 80.7% and 87.4%, respectively. Evidently, the combination of ALS and aerial images in detecting needle losses is capable of providing satisfactory estimates for individual trees.

Highlights

The world’s climate has experienced dramatic changes over the past decades causing, among other things, rising temperatures across the globe [1]
We propose the hypothesis that the distribution of the laser returns of a defoliated tree differs from that of a healthy tree estimated by LASSO, Random Forest (RF) and MSN
We showed that distributions of airborne laser scanning (ALS) pulses and spectral features of aerial photographs vary between healthy and defoliated trees

Summary

Introduction

The world’s climate has experienced dramatic changes over the past decades causing, among other things, rising temperatures across the globe [1]. Some forest insects, formerly regarded as harmless species, have altered their pest status and are causing serious damage in Finland [6,7]. Economic losses from needle defoliators can be considerable, approximately EUR 300–1000 per hectare, depending on the intensity of needle loss and number of years with high population densities. It can require over a decade for a tree to fully recover after a 1–3 year outbreak [8]

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