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

Remote Sens. 2010, 2(12), 2665-2679; doi:10.3390/rs2122665

Author 

Tuula Kantola ^1,* , Mikko Vastaranta ¹

, Xiaowei Yu ²

, Paivi Lyytikainen-Saarenmaa ¹

, Markus Holopainen ¹

, Mervi Talvitie ¹

, Sanna Kaasalainen ²

, Svein Solberg ³

 and Juha Hyyppa ²

¹

Department of Forest Sciences, University of Helsinki, Helsinki, Finland

²

Finnish Geodetic Institute, FI-02431, Masala, Finland

³

Norwegian Forest and Landscape Institute, Norway

^*

Author to whom correspondence should be addressed. 

Received: 12 October 2010 / Revised: 18 November 2010 / Accepted: 22 November 2010 / Published: 26 November 2010

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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. View Full-Text

Keywords: ALS;  defoliation;  Diprion pini;  forest disturbance;  logistic regression;  MSN;  random forest

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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