Scopus
YÖKSİS Eşleşti
Extraction of forest inventory parameters using handheld mobile laser scanning: A case study from Trabzon, Turkey
Measurement: Journal of the International Measurement Confederation · Haziran 2021
YÖKSİS Kayıtları
Extraction of forest inventory parameters using handheld mobile laser scanning: A case study from Trabzon, Turkey
Measurement · 2021 SCI-Expanded
DOÇENT MUSTAFA ZEYBEK →
Makale Bilgileri
DergiMeasurement: Journal of the International Measurement Confederation
Yayın TarihiHaziran 2021
Cilt / Sayfa177
Scopus ID2-s2.0-85106253720
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.
Yazarlar (2)
1
Can Vatandaşlar
2
Mustafa Zeybek
ORCID: 0000-0001-8640-1443
Anahtar Kelimeler
Crown closure
Individual tree extraction
Light detection and ranging (LiDAR)
Machine learning
Tree attributes
Kurumlar
Artvin Coruh University, Turkey
Artvin Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
16
Atıf
2
Yazar
5
Anahtar Kelime