Tree biomass estimation using ALS features

Minna Räty, Ville Kankare, Xiaowei Yu, Markus Holopainen, Mikko Vastaranta, Tuula Kantola, Juha Hyyppä, Risto Viitala

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

Kuvaus

Today the estimation of biomass and detection of changes in biomass in large areas is based on coarse remote sensing data and field measurements, which are time consuming, expensive and, above all, in local level inaccurate. The recent development of techniques has offered opportunities to develop new methods, e.g. laser scanning. Airborne laser scanning (ALS) derived features could be used to estimate the total biomass of standing trees. The objective of
this study was to make preliminary investigations between accurately measured biomasses in the field and ALS derived features. Study material consisted of 38 sample trees: 19 Scots pines (Pinus sylvestris) and Norway spruces (Picea abies), which biomasses were accurately measured. ALS derived segments representing the field trees were matched and features for trees were extracted from ALS points within segments. Correlations between biomasses and ALS features were calculated and simple regression models were formulated. The relative residual errors were 21% for Scots pine and 40% for Norway spruce. More empirical tests are needed for ALS based tree biomass estimations.
Alkuperäiskielienglanti
OtsikkoSilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems : conference handbook
Sivumäärä8
JulkaisupaikkaHobart
Kustantaja11th SilviLaser Organising and Scientific Committee
Julkaisupäivälokakuuta 2011
TilaJulkaistu - lokakuuta 2011
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaSilvilaser 2011 - Hobart, Australia
Kesto: 16 lokakuuta 201120 lokakuuta 2011
Konferenssinumero: 11

Tieteenalat

  • 4112 Metsätiede

Lainaa tätä

Räty, M., Kankare, V., Yu, X., Holopainen, M., Vastaranta, M., Kantola, T., ... Viitala, R. (2011). Tree biomass estimation using ALS features. teoksessa SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems: conference handbook Hobart: 11th SilviLaser Organising and Scientific Committee.
Räty, Minna ; Kankare, Ville ; Yu, Xiaowei ; Holopainen, Markus ; Vastaranta, Mikko ; Kantola, Tuula ; Hyyppä, Juha ; Viitala, Risto. / Tree biomass estimation using ALS features. SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems: conference handbook. Hobart : 11th SilviLaser Organising and Scientific Committee, 2011.
@inproceedings{0129d6312e034720815694aea94f3cb0,
title = "Tree biomass estimation using ALS features",
abstract = "Today the estimation of biomass and detection of changes in biomass in large areas is based on coarse remote sensing data and field measurements, which are time consuming, expensive and, above all, in local level inaccurate. The recent development of techniques has offered opportunities to develop new methods, e.g. laser scanning. Airborne laser scanning (ALS) derived features could be used to estimate the total biomass of standing trees. The objective ofthis study was to make preliminary investigations between accurately measured biomasses in the field and ALS derived features. Study material consisted of 38 sample trees: 19 Scots pines (Pinus sylvestris) and Norway spruces (Picea abies), which biomasses were accurately measured. ALS derived segments representing the field trees were matched and features for trees were extracted from ALS points within segments. Correlations between biomasses and ALS features were calculated and simple regression models were formulated. The relative residual errors were 21{\%} for Scots pine and 40{\%} for Norway spruce. More empirical tests are needed for ALS based tree biomass estimations.",
keywords = "4112 Forestry, ALS, Biomass, Estimation, Regression",
author = "Minna R{\"a}ty and Ville Kankare and Xiaowei Yu and Markus Holopainen and Mikko Vastaranta and Tuula Kantola and Juha Hyypp{\"a} and Risto Viitala",
note = "Volume: Proceeding volume:",
year = "2011",
month = "10",
language = "English",
booktitle = "SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems",
publisher = "11th SilviLaser Organising and Scientific Committee",
address = "Australia",

}

Räty, M, Kankare, V, Yu, X, Holopainen, M, Vastaranta, M, Kantola, T, Hyyppä, J & Viitala, R 2011, Tree biomass estimation using ALS features. 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.

Tree biomass estimation using ALS features. / Räty, Minna; Kankare, Ville; Yu, Xiaowei; Holopainen, Markus; Vastaranta, Mikko; Kantola, Tuula; Hyyppä, Juha; Viitala, Risto.

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 - Tree biomass estimation using ALS features

AU - Räty, Minna

AU - Kankare, Ville

AU - Yu, Xiaowei

AU - Holopainen, Markus

AU - Vastaranta, Mikko

AU - Kantola, Tuula

AU - Hyyppä, Juha

AU - Viitala, Risto

N1 - Volume: Proceeding volume:

PY - 2011/10

Y1 - 2011/10

N2 - Today the estimation of biomass and detection of changes in biomass in large areas is based on coarse remote sensing data and field measurements, which are time consuming, expensive and, above all, in local level inaccurate. The recent development of techniques has offered opportunities to develop new methods, e.g. laser scanning. Airborne laser scanning (ALS) derived features could be used to estimate the total biomass of standing trees. The objective ofthis study was to make preliminary investigations between accurately measured biomasses in the field and ALS derived features. Study material consisted of 38 sample trees: 19 Scots pines (Pinus sylvestris) and Norway spruces (Picea abies), which biomasses were accurately measured. ALS derived segments representing the field trees were matched and features for trees were extracted from ALS points within segments. Correlations between biomasses and ALS features were calculated and simple regression models were formulated. The relative residual errors were 21% for Scots pine and 40% for Norway spruce. More empirical tests are needed for ALS based tree biomass estimations.

AB - Today the estimation of biomass and detection of changes in biomass in large areas is based on coarse remote sensing data and field measurements, which are time consuming, expensive and, above all, in local level inaccurate. The recent development of techniques has offered opportunities to develop new methods, e.g. laser scanning. Airborne laser scanning (ALS) derived features could be used to estimate the total biomass of standing trees. The objective ofthis study was to make preliminary investigations between accurately measured biomasses in the field and ALS derived features. Study material consisted of 38 sample trees: 19 Scots pines (Pinus sylvestris) and Norway spruces (Picea abies), which biomasses were accurately measured. ALS derived segments representing the field trees were matched and features for trees were extracted from ALS points within segments. Correlations between biomasses and ALS features were calculated and simple regression models were formulated. The relative residual errors were 21% for Scots pine and 40% for Norway spruce. More empirical tests are needed for ALS based tree biomass estimations.

KW - 4112 Forestry

KW - ALS

KW - Biomass

KW - Estimation

KW - Regression

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 -

Räty M, Kankare V, Yu X, Holopainen M, Vastaranta M, Kantola T et al. Tree biomass estimation using ALS features. julkaisussa SilviLaser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems: conference handbook. Hobart: 11th SilviLaser Organising and Scientific Committee. 2011