SAR radargrammetry and scanning LiDAR in predicting forest canopy height

Mikko Vastaranta, Markus Holopainen, Mika Karjalainen, Ville Kankare, Juha Hyyppä, Sanna Kaasalainen, Hannu Hyyppä

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

Kuvaus

Our objective was to evaluate the accuracy of estimating forest canopy height when using scanning LiDAR and TerraSAR-X stereo radargrammetry. The study area was located in southern Finland. We used SAR radargrammetry and LiDAR to extract 3D point clouds to derive predictors used in the non-parametric prediction of forest canopy height. We used tree-wise measured field plots (n=110) as reference data. Our results showed that with SAR radargrammetry, the relative RMSE for forest canopy height was 12.2% whereas it was 8.1% with LiDAR. We concluded that SAR radargrammetry is a promising remote-sensing method for predicting forest canopy height when an accurate digital terrain model is available.
Alkuperäiskielienglanti
Otsikko2012 IEEE International Geoscience & Remote Sensing Symposium : Proceedings
Sivumäärä4
JulkaisupaikkaPiscataway, NJ
KustantajaIEEE
Julkaisupäivä2012
Sivut6515-6518
ISBN (painettu)978-1-4673-1160-1
ISBN (elektroninen)978-1-4673-1158-8
DOI - pysyväislinkit
TilaJulkaistu - 2012
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaIEEE International Geoscience & Remote Sensing Symposium - Munchen, Saksa
Kesto: 21 elokuuta 201126 elokuuta 2011

Tieteenalat

  • 4112 Metsätiede

Lainaa tätä

Vastaranta, M., Holopainen, M., Karjalainen, M., Kankare, V., Hyyppä, J., Kaasalainen, S., & Hyyppä, H. (2012). SAR radargrammetry and scanning LiDAR in predicting forest canopy height. teoksessa 2012 IEEE International Geoscience & Remote Sensing Symposium: Proceedings (Sivut 6515-6518). Piscataway, NJ: IEEE. https://doi.org/10.1109/IGARSS.2012.6352752
Vastaranta, Mikko ; Holopainen, Markus ; Karjalainen, Mika ; Kankare, Ville ; Hyyppä, Juha ; Kaasalainen, Sanna ; Hyyppä, Hannu. / SAR radargrammetry and scanning LiDAR in predicting forest canopy height. 2012 IEEE International Geoscience & Remote Sensing Symposium: Proceedings. Piscataway, NJ : IEEE, 2012. Sivut 6515-6518
@inproceedings{c8bb6ac9567c4cb9a1c4d51d7ad8cba1,
title = "SAR radargrammetry and scanning LiDAR in predicting forest canopy height",
abstract = "Our objective was to evaluate the accuracy of estimating forest canopy height when using scanning LiDAR and TerraSAR-X stereo radargrammetry. The study area was located in southern Finland. We used SAR radargrammetry and LiDAR to extract 3D point clouds to derive predictors used in the non-parametric prediction of forest canopy height. We used tree-wise measured field plots (n=110) as reference data. Our results showed that with SAR radargrammetry, the relative RMSE for forest canopy height was 12.2{\%} whereas it was 8.1{\%} with LiDAR. We concluded that SAR radargrammetry is a promising remote-sensing method for predicting forest canopy height when an accurate digital terrain model is available.",
keywords = "4112 Forestry",
author = "Mikko Vastaranta and Markus Holopainen and Mika Karjalainen and Ville Kankare and Juha Hyypp{\"a} and Sanna Kaasalainen and Hannu Hyypp{\"a}",
note = "Volume: Proceeding volume:",
year = "2012",
doi = "10.1109/IGARSS.2012.6352752",
language = "English",
isbn = "978-1-4673-1160-1",
pages = "6515--6518",
booktitle = "2012 IEEE International Geoscience & Remote Sensing Symposium",
publisher = "IEEE",
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Vastaranta, M, Holopainen, M, Karjalainen, M, Kankare, V, Hyyppä, J, Kaasalainen, S & Hyyppä, H 2012, SAR radargrammetry and scanning LiDAR in predicting forest canopy height. julkaisussa 2012 IEEE International Geoscience & Remote Sensing Symposium: Proceedings. IEEE, Piscataway, NJ, Sivut 6515-6518, IEEE International Geoscience & Remote Sensing Symposium, Munchen, Saksa, 21/08/2011. https://doi.org/10.1109/IGARSS.2012.6352752

SAR radargrammetry and scanning LiDAR in predicting forest canopy height. / Vastaranta, Mikko; Holopainen, Markus; Karjalainen, Mika; Kankare, Ville; Hyyppä, Juha; Kaasalainen, Sanna; Hyyppä, Hannu.

2012 IEEE International Geoscience & Remote Sensing Symposium: Proceedings. Piscataway, NJ : IEEE, 2012. s. 6515-6518.

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

TY - GEN

T1 - SAR radargrammetry and scanning LiDAR in predicting forest canopy height

AU - Vastaranta, Mikko

AU - Holopainen, Markus

AU - Karjalainen, Mika

AU - Kankare, Ville

AU - Hyyppä, Juha

AU - Kaasalainen, Sanna

AU - Hyyppä, Hannu

N1 - Volume: Proceeding volume:

PY - 2012

Y1 - 2012

N2 - Our objective was to evaluate the accuracy of estimating forest canopy height when using scanning LiDAR and TerraSAR-X stereo radargrammetry. The study area was located in southern Finland. We used SAR radargrammetry and LiDAR to extract 3D point clouds to derive predictors used in the non-parametric prediction of forest canopy height. We used tree-wise measured field plots (n=110) as reference data. Our results showed that with SAR radargrammetry, the relative RMSE for forest canopy height was 12.2% whereas it was 8.1% with LiDAR. We concluded that SAR radargrammetry is a promising remote-sensing method for predicting forest canopy height when an accurate digital terrain model is available.

AB - Our objective was to evaluate the accuracy of estimating forest canopy height when using scanning LiDAR and TerraSAR-X stereo radargrammetry. The study area was located in southern Finland. We used SAR radargrammetry and LiDAR to extract 3D point clouds to derive predictors used in the non-parametric prediction of forest canopy height. We used tree-wise measured field plots (n=110) as reference data. Our results showed that with SAR radargrammetry, the relative RMSE for forest canopy height was 12.2% whereas it was 8.1% with LiDAR. We concluded that SAR radargrammetry is a promising remote-sensing method for predicting forest canopy height when an accurate digital terrain model is available.

KW - 4112 Forestry

U2 - 10.1109/IGARSS.2012.6352752

DO - 10.1109/IGARSS.2012.6352752

M3 - Conference contribution

SN - 978-1-4673-1160-1

SP - 6515

EP - 6518

BT - 2012 IEEE International Geoscience & Remote Sensing Symposium

PB - IEEE

CY - Piscataway, NJ

ER -

Vastaranta M, Holopainen M, Karjalainen M, Kankare V, Hyyppä J, Kaasalainen S et al. SAR radargrammetry and scanning LiDAR in predicting forest canopy height. julkaisussa 2012 IEEE International Geoscience & Remote Sensing Symposium: Proceedings. Piscataway, NJ: IEEE. 2012. s. 6515-6518 https://doi.org/10.1109/IGARSS.2012.6352752