Influence of Tree Canopy Coverage and Leaf Area Density on Urban Heat Island Mitigation

Urban heat islands (UHI) are a widely documented phenomenon that adversely increases urban overheating and, among other effects, contributes to heat-related mortalities and morbidities in urban areas. Consequently, comprehensive UHI-mitigating measures are essential for improving urban microclimate environments and contributing to salutogenic urban design practices. This study proposed urban cooling strategies involving different tree percentages and leaf area densities in a dense urban area during the summertime in Korea. The cooling effects of sixteen various combinations of proposed scenarios based on common urban tree types were studied via in-situ field measurements and numerical modeling, considering both vegetated and exposed areas. It was observed that by changing the characteristics of the leaf area density (LAD) per plant of our vegetated base area—for instance, from 4% trees to 60% trees, from a low LAD to a high LAD—the daily average and daily maximum temperatures were reduced by approximately 3 °C and 5.23 °C, respectively. The obtained results demonstrate the usefulness of urban trees to mitigate urban heating, and they are particularly useful to urban designers and policymakers in their efforts to minimize UHI effects.

Estimating cover fraction from TLS return intensity in coniferous and broadleaved tree shoots

Terrestrial laser scanning (TLS) provides a unique opportunity to study forest canopy structure and its spatial patterns such as foliage quantity and dispersal. Using TLS point clouds for estimating leaf area density with voxel-based methods is biased by the physical dimensions of laser beams, which violates the common assumption of beams being infinitely thin. Real laser beams have a footprint size larger than several millimeters. This leads to difficulties in estimating leaf area density from light detection and ranging (LiDAR) in vegetation, where the target objects can be of similar or even smaller size than the beam footprint. To compensate for this bias, we propose a method to estimate the per-pulse cover fraction, defined as the fraction of laser beams’ footprint area that is covered by vegetation targets, using the LiDAR return intensity and an experimental calibration measurement. We applied this method to a Leica P40 single-return instrument, and report our experimental results. We found that conifer foliage had a lower average per-pulse cover fraction than broadleaved foliage, indicating an increased number of partial hits in conifer foliage. We further discuss limitations of our method that stem from unknown target properties that influence the LiDAR return intensity and highlight potential ways to overcome the limitations and manage the remaining uncertainty. Our method’s output, the per-beam cover fraction, may be useful in a weight function for methods that estimate leaf area density from LiDAR point clouds.

Estimation of maize plant height and leaf area index dynamics using an unmanned aerial vehicle with oblique and nadir photography

Background and Aims High-throughput phenotyping is a limitation in plant genetics and breeding due to large-scale experiments in the field. Unmanned aerial vehicles (UAVs) can help to extract plant phenotypic traits rapidly and non-destructively with high efficiency. The general aim of this study is to estimate the dynamic plant height and leaf area index (LAI) by nadir and oblique photography with a UAV, and to compare the integrity of the established three-dimensional (3-D) canopy by these two methods. Methods Images were captured by a high-resolution digital RGB camera mounted on a UAV at five stages with nadir and oblique photography, and processed by Agisoft Metashape to generate point clouds, orthomosaic maps and digital surface models. Individual plots were segmented according to their positions in the experimental design layout. The plant height of each inbred line was calculated automatically by a reference ground method. The LAI was calculated by the 3-D voxel method. The reconstructed canopy was sliced into different layers to compare leaf area density obtained from oblique and nadir photography. Key Results Good agreements were found for plant height between nadir photography, oblique photography and manual measurement during the whole growing season. The estimated LAI by oblique photography correlated better with measured LAI (slope = 0.87, R2 = 0.67), compared with that of nadir photography (slope = 0.74, R2 = 0.56). The total number of point clouds obtained by oblique photography was about 2.7–3.1 times than those by nadir photography. Leaf area density calculated by nadir photography was much less than that obtained by oblique photography, especially near the plant base. Conclusions Plant height and LAI can be extracted automatically and efficiently by both photography methods. Oblique photography can provide intensive point clouds and relatively complete canopy information at low cost. The reconstructed 3-D profile of the plant canopy can be easily recognized by oblique photography.