Abstract
BackgroundUrban trees have long been valued for providing ecosystem services (mitigation of the “heat island” effect, suppression of air pollution, etc.); more recently the potential of urban forests to store significant above ground biomass (AGB) has also be recognised. However, urban areas pose particular challenges when assessing AGB due to plasticity of tree form, high species diversity as well as heterogeneous and complex land cover. Remote sensing, in particular light detection and ranging (LiDAR), provide a unique opportunity to assess urban AGB by directly measuring tree structure. In this study, terrestrial LiDAR measurements were used to derive new allometry for the London Borough of Camden, that incorporates the wide range of tree structures typical of an urban setting. Using a wall-to-wall airborne LiDAR dataset, individual trees were then identified across the Borough with a new individual tree detection (ITD) method. The new allometry was subsequently applied to the identified trees, generating a Borough-wide estimate of AGB.ResultsCamden has an estimated median AGB density of 51.6 Mg ha–1 where maximum AGB density is found in pockets of woodland; terrestrial LiDAR-derived AGB estimates suggest these areas are comparable to temperate and tropical forest. Multiple linear regression of terrestrial LiDAR-derived maximum height and projected crown area explained 93% of variance in tree volume, highlighting the utility of these metrics to characterise diverse tree structure. Locally derived allometry provided accurate estimates of tree volume whereas a Borough-wide allometry tended to overestimate AGB in woodland areas. The new ITD method successfully identified individual trees; however, AGB was underestimated by ≤ 25% when compared to terrestrial LiDAR, owing to the inability of ITD to resolve crown overlap. A Monte Carlo uncertainty analysis identified assigning wood density values as the largest source of uncertainty when estimating AGB.ConclusionOver the coming century global populations are predicted to become increasingly urbanised, leading to an unprecedented expansion of urban land cover. Urban areas will become more important as carbon sinks and effective tools to assess carbon densities in these areas are therefore required. Using multi-scale LiDAR presents an opportunity to achieve this, providing a spatially explicit map of urban forest structure and AGB.
Highlights
Urban trees have long been valued for providing ecosystem services; more recently the potential of urban forests to store significant above ground biomass (AGB) has be recognised
A large number of trees were discarded from the quantitative structure modelling (QSM) tree set for reasons including; (i) scanning domain did not cover the complete region of interest, trees on the periphery suffered from low point density, (ii) scan pattern were too sparse, for St Pancras where leaf-on conditions resulted in high occlusion and low point density towards the top of the canopy and (iii) wind effects
The distribution of AGB is likely skewed to the right by an overestimate of “forest” C density calculated with the Borough-wide allometry (Table 3), Camden does have a greater proportion of park land compared to inner London [69]
Summary
Urban trees have long been valued for providing ecosystem services (mitigation of the “heat island” effect, suppression of air pollution, etc.); more recently the potential of urban forests to store significant above ground biomass (AGB) has be recognised. Urban vegetation plays a disproportionate role in sequestrating anthropogenic carbon emissions as it is proximate to major sources i.e. vehicle emissions, as well as providing shade for buildings which reduce energy consumption [9, 10]. This biogenic sequestration of carbon by urban trees has been valued at £4.8 M ($6.3 M) per annum or £17.80 per tree in Greater London [10] and $2 bn per annum in the USA [11]. As urban vegetation can be highly dynamic e.g. higher mortality [16] and faster growth rates [17] than natural forests, and methods designed for natural ecosystems may not be transferable to urban areas [18]
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