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Dear Colleagues,

Urban forests are widely recognised for the multiple ecosystem services they provide and the positive impact this has on urban populations. These forests are also unique in that they are highly managed; tree density, species composition and forest succession are generally dictated by municipal decisions rather than environmental processes. The ability to measure forest structure in the heterogeneous urban matrix has so far been limited to ad hoc inventory or limited sampling of a particular cohort (e.g. trees on public land). New remote sensing opportunities could allow for a more timely, detailed and synoptic assessment of urban forest structure. The ubiquity of sensors in urban areas, coupled with new satellite or open-access remote sensing datasets, could elicit new information beyond over-simplistic canopy cover metrics. This new information could then be used to identify patterns in urban forest dynamics, quantifying the multiple co-benefits of ecosystem services, improve understanding of the link between urban forest and socio-economics and be used as a planning tool to improve the livability of urban centres. We invite contributions on the novel use of remote sensing for assessment of urban forest structure, particularly using new sensors, open-access computing and applied to large or multiple urban centres.

Dr. Phil Wilkes
Guest Editor

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Keywords

urban forest
green infrastructure
ecosystem services
liveable cities
forest inventory
open-access
sensor network

Published Papers (2 papers)

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18 pages, 4455 KiB

Open AccessArticle

Influence of Scale Effect of Canopy Projection on Understory Microclimate in Three Subtropical Urban Broad-Leaved Forests

by Xueyan Gao, Chong Li, Yue Cai, Lei Ye, Longdong Xiao, Guomo Zhou and Yufeng Zhou

Remote Sens. 2021, 13(18), 3786; https://doi.org/10.3390/rs13183786 - 21 Sep 2021

Cited by 5 | Viewed by 2168

Abstract

The canopy is the direct receiver and receptor of external environmental variations, and affects the microclimate and energy exchange between the understory and external environment. After autumn leaf fall, the canopy structure of different forests shows remarkable variation, causes changes in the microclimate and is essential for understory vegetation growth. Moreover, the microclimate is influenced by the scale effect of the canopy. However, the difference in influence between different forests remains unclear on a small scale. In this study, we aimed to analyze the influence of the scale effect of canopy projection on understory microclimate in three subtropical broad-leaved forests. Three urban forests: evergreen broad-leaved forest (EBF), deciduous broad-leaved forest (DBF), and mixed evergreen and deciduous broad-leaved forest (MBF) were selected for this study. Sensors for environmental monitoring were used to capture the microclimate data (temperature (T), relative humidity (RH), and light intensity (LI)) for each forest. Terrestrial laser scanning was employed to obtain the canopy projection intensity (CPI) at each sensor location. The results indicate that the influence range of canopy projection on the microclimate was different from stand to stand (5.5, 5, and 3 m). Moreover, there was a strong negative correlation between T and RH, and the time for T and LI to reach a significant correlation in different urban forests was different, as well as the time for RH and LI during the day. Finally, the correlation between CPI and the microclimate showed that canopy projection had the greatest effect on T and RH in MBF, followed by DBF and EBF. In conclusion, our findings confirm that canopy projection can significantly affect understory microclimate. This study provides a reference for the conservation of environmentally sensitive organisms for urban forest management. Full article

(This article belongs to the Special Issue Remote Sensing of Urban Forest Structure)

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20 pages, 3742 KiB

Open AccessArticle

Measuring the Contribution of Leaves to the Structural Complexity of Urban Tree Crowns with Terrestrial Laser Scanning

by Georgios Arseniou, David W. MacFarlane and Dominik Seidel

Remote Sens. 2021, 13(14), 2773; https://doi.org/10.3390/rs13142773 - 14 Jul 2021

Cited by 10 | Viewed by 3098

Abstract

Trees have a fractal-like branching architecture that determines their structural complexity. We used terrestrial laser scanning technology to study the role of foliage in the structural complexity of urban trees. Forty-five trees of three deciduous species, Gleditsia triacanthos, Quercus macrocarpa, Metasequoia glyptostroboides, were sampled on the Michigan State University campus. We studied their structural complexity by calculating the box-dimension (D_b) metric from point clouds generated for the trees using terrestrial laser scanning, during the leaf-on and -off conditions. Furthermore, we artificially defoliated the leaf-on point clouds by applying an algorithm that separates the foliage from the woody material of the trees, and then recalculated the D_b metric. The D_b of the leaf-on tree point clouds was significantly greater than the D_b of the leaf-off point clouds across all species. Additionally, the leaf removal algorithm introduced bias to the estimation of the leaf-removed D_b of the G. triacanthos and M. glyptostroboides trees. The index capturing the contribution of leaves to the structural complexity of the study trees (the ratio of the D_b of the leaf-on point clouds divided by the D_b of the leaf-off point clouds minus one), was negatively correlated with branch surface area and different metrics of the length of paths through the branch network of the trees, indicating that the contribution of leaves decreases as branch network complexity increases. Underestimation of the D_b of the G. triacanthos trees, after the artificial leaf removal, was related to maximum branch order. These results enhance our understanding of tree structural complexity by disentangling the contribution of leaves from that of the woody structures. The study also highlighted important methodological considerations for studying tree structure, with and without leaves, from laser-derived point clouds. Full article

(This article belongs to the Special Issue Remote Sensing of Urban Forest Structure)

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