Extraction of forest inventory parameters using handheld mobile laser scanning: A case study from Trabzon, Turkey
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Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier B.V.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Forest inventory (FI) surveys are cumbersome when field measurements are performed by manual means. We propose a semi-automated data collection approach using handheld mobile laser scanning (HMLS) to estimate and map key FI parameters. To this end, machine learning (e.g., random forest classifier for tree detection) and innovative algorithms (e.g., ellipse fitting for diameter estimation of noncircular trees) were used for the first time in FI surveying. After surveying nine plots, we compared HMLS-derived data against the field reference. HMLS-derived tree diameters (DBHs) were strongly correlated with the reference data at the single-tree level (r= 0.93–0.99; p< 0.001). At the plot level, HMLS slightly overestimated DBHs in complex plots due to the influence of undergrowth and creepers on trunks. Yet, no statistically significant difference was found between the two datasets (p> 0.05). Overall, HMLS was concluded as efficient and effective tool for FIs, even if used alone.
Açıklama
Anahtar Kelimeler
Crown closure, Individual tree extraction, Light detection and ranging (LiDAR), Machine learning, Tree attributes
Kaynak
WoS Q Değeri
Scopus Q Değeri
Cilt
177
Sayı
Künye
Vatandaşlar, C., & Zeybek, M. (2021). Extraction of forest inventory parameters using handheld mobile laser scanning: A case study from Trabzon, Turkey. Measurement, 177, 109328.
