A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Estimation of forest stand characteristics using individual tree detection, stochastic geometry and a sequential spatial point process model (2022)
Mehtätalo, L., Yazigi, A., Kansanen, K., Packalen, P., Lähivaara, T., Maltamo, M., Myllymäki, M., & Penttinen, A. (2022). Estimation of forest stand characteristics using individual tree detection, stochastic geometry and a sequential spatial point process model. International Journal of Applied Earth Observation and Geoinformation, 112, Article 102920. https://doi.org/10.1016/j.jag.2022.102920
JYU-tekijät tai -toimittajat
Julkaisun tiedot
Julkaisun kaikki tekijät tai toimittajat: Mehtätalo, Lauri; Yazigi, Adil; Kansanen, Kasper; Packalen, Petteri; Lähivaara, Timo; Maltamo, Matti; Myllymäki, Mari; Penttinen, Antti
Lehti tai sarja: International Journal of Applied Earth Observation and Geoinformation
ISSN: 1569-8432
eISSN: 1872-826X
Julkaisuvuosi: 2022
Volyymi: 112
Artikkelinumero: 102920
Kustantaja: Elsevier BV
Julkaisumaa: Alankomaat
Julkaisun kieli: englanti
DOI: https://doi.org/10.1016/j.jag.2022.102920
Julkaisun avoin saatavuus: Avoimesti saatavilla
Julkaisukanavan avoin saatavuus: Kokonaan avoin julkaisukanava
Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/82579
Tiivistelmä
Airborne Laser Scanning (ALS) results in point-wise measurements of canopy height, which can further be used for Individual Tree Detection (ITD). However, ITD cannot find all trees because small trees can hide below larger tree crowns. Here we discuss methods where the plot totals and means of tree-level characteristics are estimated in such context. The starting point is a previously presented Horvitz–Thompson-like (HT-like) estimator, where the detectability is based on the larger tree crowns and a tuning parameter that models the detection condition. We propose a new method which is based on modeling the spatial pattern of hidden tree locations using a sequential spatial point process model, with a tuning parameter . We also explore whether the variability of the tuning parameters and can be predicted using ALS features to improve the predictions. The accuracy of stand density, dominant height and mean height is used as comparison criteria in a cross-validation procedure. The HT-like estimator with empirically estimated tuning parameter performed the best. The overall performance of the new method was comparable. The new method was computationally less demanding, which makes it attractive for practical use.
YSO-asiasanat: metsät; puut (kasvit); puusto; tiheys; inventointi; kaukokartoitus; metsänarviointi; mittausmenetelmät; mittauslaitteet; laserit; laserlaitteet; lasertekniikka
Vapaat asiasanat: forest inventory; Airborne Laser Scanning; Horvitz-Thompson-like estimator; stand density:tree height
Liittyvät organisaatiot
OKM-raportointi: Kyllä
Raportointivuosi: 2022
JUFO-taso: 1