Authors: Cynthia Sellers*, Clark University, Nicholas Geron, Graduate School of Geography, Clark University, 950 Main Street, Worcester, MA 01610, USA, Arthur Elmes, University of Massachusetts, 100 Morrissey Blvd, Boston, MA 02125, USA , John Rogan, Graduate School of Geography, Clark University, 950 Main Street, Worcester, MA 01610, USA, Marc Healy, Graduate School of Geography, Clark University, 950 Main Street, Worcester, MA 01610, USA, Deborah Martin, Graduate School of Geography, Clark University, 950 Main Street, Worcester, MA 01610, USA
Topics: Remote Sensing, Urban Geography, Quantitative Methods
Keywords: above-ground biomass (AGB), terrestrial laser scanning (TLS), urban forestry, quantitative structure model (QSM), compact biomass LiDAR (CBL), i-Tree, CloudCompare
Session Type: Paper
Presentation File: No File Uploaded
Urban forests play a critical role in carbon storage within increasingly urbanized landscapes. Allometric models are widely used for estimating above-ground biomass (AGB) and carbon storage of urban forests. However, allometric equations derived from natural forest allometry are not representative of urban trees. It is therefore important to explore more accurate methods for estimating AGB. Limited research has utilized Light Detection and Ranging (LiDAR) to measure AGB in complex urban landscapes. This study highlights the potential of high-resolution terrestrial laser scanners (TLS) to effectively estimate the AGB of juvenile street trees on Granville Avenue in Worcester (Massachusetts). The tree species measured were: Pyrus calleryana ‘Bradford’, Gleditsia triacanthos, Quercus rubra, Quercus coccinea, Tilia cordata, and Prunus serrulata ‘Kwanzan’. TLS point clouds for each tree were generated in CloudCompare software using scans from the Compact Biomass LiDAR (CBL). AGB was estimated from each point cloud using quantitative structure models (QSM) to obtain tree volume. TLS AGB estimations were compared with estimations generated through i-Tree allometric models and field measurements from each tree.
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