Comparing airborne laser scanning and UAV photogrammetry for estimating aboveground biomass of individual urban trees in Helsinki

Abstract

The rapid urbanization trend is posing a threat to urban green spaces (UGS) worldwide. Consequently, scientific research has addressed the need to develop monitoring methods for UGS and their attributes. One example is the estimation of Aboveground biomass (AGB) using Airborne laser scanning (ALS) and UAV photogrammetry , which are applied to measure attributes of urban vegetation from three-dimensional (3D) point clouds. The aim of this study is to examine and compare the use of ALS and drone photogrammetry with allometric models to estimate the AGB of urban trees on a neighbourhood-level city area. 3D point clouds generated by means of ALS and UAV photogrammetry were used to study a residential area located in Helsinki, Finland. The point clouds were classified and automatic Individual tree detection ( ) method was utilized to extract urban trees. In-situ measurements were conducted to estimate DBH and assess the accuracy of the tree detection. Species-specific and generic allometric models were used to determine the AGB of urban vegetation. results revealed an overestimation of detected trees from both datasets, and differences in DBH, tree height, and volume were observed in both datasets. Notably, AGB estimation results indicated that species-specific models showed a lower estimation compared to generic allometric models. Overall, the results suggested that ALS and UAV photogrammetry can be used for mapping biomass in urban residential areas, as both methods are cost-effective and time-efficient. However, future research should focus on monitoring low vegetation types such as shrubs and estimating the biomass as existing methods are specific for certain tree species and not suitable for broader vegetation types beyond individual trees.

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