Using high density ALS data in plot level estimation of the defoliation by the Common pine sawfly

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

Kuvaus

The climate change has been related to the increase of forest insect damages in the boreal zone. The prediction of the changes in the distribution of insect-caused forest damages has become a topical issue. The common pine sawfly (Diprion pini L.) is regarded as a significant threat to boreal Scots pine (Pinus sylvestris L.) forests. Efficient and accurate methods are needed for monitoring and predicting changes in insect defoliation. In this study, the field work has been carried out in 2009 in Eastern Finland, where D. pini has caused considerable damage in managed Scots pine forests. Altogether 95 sampling plots were used in the analysis. The tree and stand variables were measured and the defoliation level was estimated in the field. A high density ALS data was acquired simultaneously. The aim of the present study was to test the accuracy of the plot level needle loss predictions determined from the area based and single tree ALS features separately. The Random Forest method (RF) was utilized in the estimation. The best classification accuracy for the test set was 67.4% (area based features). The best plot level accuracy using the tree-wise features was 60.6%, respectively.
Alkuperäiskielienglanti
OtsikkoSilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems : conference handbook
Sivumäärä9
JulkaisupaikkaHobart
Kustantaja11th SilviLaser Organising and Scientific Committee
Julkaisupäivä2011
TilaJulkaistu - 2011
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaSilvilaser 2011 - Hobart, Australia
Kesto: 16 lokakuuta 201120 lokakuuta 2011
Konferenssinumero: 11th

Tieteenalat

  • 4112 Metsätiede

Lainaa tätä

Kantola, T., Lyytikäinen-Saarenmaa, P., Vastaranta, M., Kankare, V., Yu, X., Holopainen, M., ... Hyyppä, J. (2011). Using high density ALS data in plot level estimation of the defoliation by the Common pine sawfly. teoksessa SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems: conference handbook Hobart: 11th SilviLaser Organising and Scientific Committee.
Kantola, Tuula ; Lyytikäinen-Saarenmaa, Päivi ; Vastaranta, Mikko ; Kankare, Ville ; Yu, Xiaowei ; Holopainen, Markus ; Talvitie, Mervi ; Solberg, Svein ; Puolakka, Paula ; Hyyppä, Juha. / Using high density ALS data in plot level estimation of the defoliation by the Common pine sawfly. SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems: conference handbook. Hobart : 11th SilviLaser Organising and Scientific Committee, 2011.
@inproceedings{47cbdee8794c40abb8619334e740a4e0,
title = "Using high density ALS data in plot level estimation of the defoliation by the Common pine sawfly",
abstract = "The climate change has been related to the increase of forest insect damages in the boreal zone. The prediction of the changes in the distribution of insect-caused forest damages has become a topical issue. The common pine sawfly (Diprion pini L.) is regarded as a significant threat to boreal Scots pine (Pinus sylvestris L.) forests. Efficient and accurate methods are needed for monitoring and predicting changes in insect defoliation. In this study, the field work has been carried out in 2009 in Eastern Finland, where D. pini has caused considerable damage in managed Scots pine forests. Altogether 95 sampling plots were used in the analysis. The tree and stand variables were measured and the defoliation level was estimated in the field. A high density ALS data was acquired simultaneously. The aim of the present study was to test the accuracy of the plot level needle loss predictions determined from the area based and single tree ALS features separately. The Random Forest method (RF) was utilized in the estimation. The best classification accuracy for the test set was 67.4{\%} (area based features). The best plot level accuracy using the tree-wise features was 60.6{\%}, respectively.",
keywords = "4112 Forestry, ALS, random forest, defoliation, Diprion pini, Forest disturbances",
author = "Tuula Kantola and P{\"a}ivi Lyytik{\"a}inen-Saarenmaa and Mikko Vastaranta and Ville Kankare and Xiaowei Yu and Markus Holopainen and Mervi Talvitie and Svein Solberg and Paula Puolakka and Juha Hyypp{\"a}",
note = "Volume: Proceeding volume:",
year = "2011",
language = "English",
booktitle = "SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems",
publisher = "11th SilviLaser Organising and Scientific Committee",
address = "Australia",

}

Kantola, T, Lyytikäinen-Saarenmaa, P, Vastaranta, M, Kankare, V, Yu, X, Holopainen, M, Talvitie, M, Solberg, S, Puolakka, P & Hyyppä, J 2011, Using high density ALS data in plot level estimation of the defoliation by the Common pine sawfly. julkaisussa SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems: conference handbook. 11th SilviLaser Organising and Scientific Committee, Hobart, Silvilaser 2011, Hobart, Australia, 16/10/2011.

Using high density ALS data in plot level estimation of the defoliation by the Common pine sawfly. / Kantola, Tuula; Lyytikäinen-Saarenmaa, Päivi; Vastaranta, Mikko; Kankare, Ville; Yu, Xiaowei; Holopainen, Markus; Talvitie, Mervi; Solberg, Svein; Puolakka, Paula; Hyyppä, Juha.

SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems: conference handbook. Hobart : 11th SilviLaser Organising and Scientific Committee, 2011.

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

TY - GEN

T1 - Using high density ALS data in plot level estimation of the defoliation by the Common pine sawfly

AU - Kantola, Tuula

AU - Lyytikäinen-Saarenmaa, Päivi

AU - Vastaranta, Mikko

AU - Kankare, Ville

AU - Yu, Xiaowei

AU - Holopainen, Markus

AU - Talvitie, Mervi

AU - Solberg, Svein

AU - Puolakka, Paula

AU - Hyyppä, Juha

N1 - Volume: Proceeding volume:

PY - 2011

Y1 - 2011

N2 - The climate change has been related to the increase of forest insect damages in the boreal zone. The prediction of the changes in the distribution of insect-caused forest damages has become a topical issue. The common pine sawfly (Diprion pini L.) is regarded as a significant threat to boreal Scots pine (Pinus sylvestris L.) forests. Efficient and accurate methods are needed for monitoring and predicting changes in insect defoliation. In this study, the field work has been carried out in 2009 in Eastern Finland, where D. pini has caused considerable damage in managed Scots pine forests. Altogether 95 sampling plots were used in the analysis. The tree and stand variables were measured and the defoliation level was estimated in the field. A high density ALS data was acquired simultaneously. The aim of the present study was to test the accuracy of the plot level needle loss predictions determined from the area based and single tree ALS features separately. The Random Forest method (RF) was utilized in the estimation. The best classification accuracy for the test set was 67.4% (area based features). The best plot level accuracy using the tree-wise features was 60.6%, respectively.

AB - The climate change has been related to the increase of forest insect damages in the boreal zone. The prediction of the changes in the distribution of insect-caused forest damages has become a topical issue. The common pine sawfly (Diprion pini L.) is regarded as a significant threat to boreal Scots pine (Pinus sylvestris L.) forests. Efficient and accurate methods are needed for monitoring and predicting changes in insect defoliation. In this study, the field work has been carried out in 2009 in Eastern Finland, where D. pini has caused considerable damage in managed Scots pine forests. Altogether 95 sampling plots were used in the analysis. The tree and stand variables were measured and the defoliation level was estimated in the field. A high density ALS data was acquired simultaneously. The aim of the present study was to test the accuracy of the plot level needle loss predictions determined from the area based and single tree ALS features separately. The Random Forest method (RF) was utilized in the estimation. The best classification accuracy for the test set was 67.4% (area based features). The best plot level accuracy using the tree-wise features was 60.6%, respectively.

KW - 4112 Forestry

KW - ALS

KW - random forest

KW - defoliation

KW - Diprion pini

KW - Forest disturbances

M3 - Conference contribution

BT - SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems

PB - 11th SilviLaser Organising and Scientific Committee

CY - Hobart

ER -

Kantola T, Lyytikäinen-Saarenmaa P, Vastaranta M, Kankare V, Yu X, Holopainen M et al. Using high density ALS data in plot level estimation of the defoliation by the Common pine sawfly. julkaisussa SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems: conference handbook. Hobart: 11th SilviLaser Organising and Scientific Committee. 2011