Predicting tree crown defoliation using color-infrared orthophoto maps

doi:10.3832/ifor0721-006

Predicting tree crown defoliation using color-infrared orthophoto maps

M Eigirdas⁽¹⁾ , A Augustaitis⁽²⁾, G Mozgeris⁽³⁾

iForest - Biogeosciences and Forestry, Volume 6, Issue 1, Pages 23-29 (2013)
doi: https://doi.org/10.3832/ifor0721-006
Published: Jan 14, 2013 - Copyright © 2013 SISEF

Research Articles

Collection/Special Issue: IUFRO 7.01.00 - COST Action FP0903, Kaunas (Lithuania - 2012)
Biological Reactions of Forest to Climate Change and Air Pollution
Guest Editors: Elena Paoletti, Andrzej Bytnerowicz, Algirdas Augustaitis

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Geo-mapping

Orthophoto maps based on color-infrared aerial photography have been used by the Lithuanian forest inventory since 2001. This study aimed to investigate the opportunities for using these orthophoto maps to predict tree crown defoliation at the single tree and sample plot levels. The test area was located in the Aukstaitija National Park, eastern Lithuania, and it was photographed in the summer of 2008 using a Vexcel UltraCam D digital frame aerial camera to produce digital orthophoto maps with a 0.5 x 0.5 m ground sampling density. Some 1721 tree crowns (mainly pine, spruce and birch), located in 166 permanent sample plots, were identified and delineated on the orthophoto maps. Crown defoliation and other dendrometric characteristics were field-estimated for all of these trees in summer 2008. Judgments on the suitability of using color-infrared aerial photography based orthophotos to estimate tree crown defoliation were based on the accuracy of the defoliation prediction. Defoliation for each crown was predicted using the non-parametric k-Nearest Neighbor (k-NN) method and characteristics extracted from the digital orthophoto maps as the auxiliary variables for prediction. Prediction accuracies were validated using the “Leave One Out” technique by comparing the predicted data with data from field-assessed crown defoliations. The lowest root mean square errors for the predicted tree crown defoliation values were 7.564 for pine trees, 9.166 for spruce and 7.712 for birch and the highest coefficients of correlation between field-estimated and predicted crown defoliations were 0.576, 0.600 and 0.386, respectively. However, there was no best performing solution for using the k-NN prediction found, as the best results were achieved using different approaches. Next, predicted and field estimated tree crown defoliation values were aggregated up to the sample plot level by taking an averaging of trees in the same sample plot. The root mean square error at the sample plot level was around 3.7 %, the bias was statistically not significant and the correlation coefficients between plot-wise average values of field-estimated and predicted defoliations were around 0.8. The achieved results suggested that color-infrared orthophoto maps could be a potential data source of forest health characteristics for use in stand-wise forest inventories.

Keywords

Color-infrared Aerial Image, Orthophoto Map, Non-parametric k-Nearest Neighbor Method, Tree Crown Defoliation

Authors’ address

(1)

Laboratory of Geomatics, Institute of Land Management and Geomatics, Aleksandras Stulginskis University, Studentu 11, LT-53361 Akademija, Kaunas distr. (Lithuania)

(2)

Laboratory of Forest Monitoring, Institute of Forest Management and Wood Science, Aleksandras Stulginskis University, Studentu 11, LT-53361 Akademija, Kaunas distr. (Lithuania)

(3)

Institute Forest Management and Wood Science, Aleksandras Stulginskis University, Studentu 11, LT-53361 Akademija, Kaunas distr. (Lithuania)

Corresponding author

M Eigirdas
marijus.eigirdas@gmail.com

Citation

Eigirdas M, Augustaitis A, Mozgeris G (2013). Predicting tree crown defoliation using color-infrared orthophoto maps. iForest 6: 23-29. - doi: 10.3832/ifor0721-006

Academic Editor

Alberto Santini

Paper history

Received: Jul 31, 2012
Accepted: Nov 19, 2012

First online: Jan 14, 2013
Publication Date: Feb 05, 2013
Publication Time: 1.87 months

Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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