Estimating Crown Variables of Individual Trees Using Airborne and Terrestrial Laser Scanners

Remote Sensing

Sung-Eun Jung¹  Doo-Ahn Kwak²  Taejin Park²  Woo-Kyun Lee² 

[1] Department of Environment & Marine Information, Sundosoft, Seoul 153-759, Korea; E-Mail:;Division of Environmental Science and Ecological Engineering, Korea University, Seoul 136-701, Korea; E-Mails:

关键词: airborne laser scanner;    terrestrial laser scanner;    digital canopy model;    k-means clustering;    crown geometric volume;   

DOI  :  10.3390/rs3112346

来源: mdpi

【 摘 要 】

In this study, individual tree height (TH), crown base height (CBH), crown area (CA) and crown volume (CV), which were considered as essential parameters for individual stem volume and biomass estimation, were estimated by both an airborne laser scanner (ALS) and a terrestrial laser scanner (TLS). These ALS- and TLS-derived tree parameters were compared because TLS has been introduced as an instrument to measure objects more precisely. ALS-estimated TH was extracted from the highest value within a crown boundary delineated with the crown height model (CHM). The ALS-derived CBH of individual trees was estimated by k-means clustering method using the ALS data within the boundary. The ALS-derived CA was calculated simply with the crown boundary, after which CV was computed automatically using the crown geometric volume (CGV). On the other hand, all TLS-derived parameters were detected manually and precisely except the TLS-derived CGV. As a result, the ALS-extracted TH, CA, and CGV values were underestimated whereas CBH was overestimated when compared with the TLS-derived parameters. The coefficients of determination (R²) from the regression analysis between the ALS and TLS estimations were approximately 0.94, 0.75, 0.69 and 0.58, and root mean square errors (RMSEs) were approximately 0.0184 m, 0.4929 m, 2.3216 m² and 13.2087 m³ for TH, CBH, CA and CGV, respectively. Thereby, the error rate decreased to 0.0089, 0.0727 and 0.0875 for TH, CA and CGV via the combination of ALS and TLS data.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.