Article

Mapping leaf area of urban greenery using aerial LiDAR and ground-based measurements in Gothenburg, Sweden

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Abstract

Leaf area of urban vegetation is an important ecological characteristic, influencing urban climate through shading and transpiration cooling and air quality through air pollutant deposition. Accurate estimates of leaf area over large areas are fundamental to model such processes. The aim of this study was to explore if an aerial LiDAR dataset acquired to create a high resolution digital terrain model could be used to map effective leaf area index (Le) and to assess the Le variation in a high latitude urban area, here represented by the city of Gothenburg, Sweden. Le was estimated from LiDAR data using a Beer-Lambert law based approach and compared to ground-based measurements with hemispherical photography and the Plant Canopy Analyser LAI-2200. Even though the LiDAR dataset was not optimized for Le mapping the comparison with hemispherical photography showed good agreement (r² = 0.72, RMSE = 0.97) for urban parks and woodlands. Leaf area density of single trees, estimated from LiDAR and LAI-2200, did not show as good agreement (r² = 0.53, RMSE = 0.49). Le in 10 m resolution covering most of Gothenburg municipality ranged from 0 to 14 (0.3% of the values >7) with an average Le of 3.5 in deciduous forests and 1.2 in urban built-up areas. When Le was averaged over larger scales there was a high correlation with canopy cover (r² = 0.97 in 1 × 1 km² scale) implying that at this scale Le is rather homogenous. However, when Le was averaged only over the vegetated parts, differences in Le became clear. Detailed study of Le in seven urban green areas with different amount and type of greenery showed a large variation in Le, ranging from average Le of 0.9 in a residential area to 4.1 in an urban woodland. The use of LiDAR data has the potential to considerably increase information of forest structure in the urban environment.

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... Only urban grid cells (f urb > 0.1) are shown. burg, Sweden (Klingberg et al., 2017). The tree species measured by Klingberg et al. (2017) are assumed to be rather representative as they correspond to 6 of the 12 most common species present in Basel (Geoportal Kanton Basel-Stadt, 2019). ...
... burg, Sweden (Klingberg et al., 2017). The tree species measured by Klingberg et al. (2017) are assumed to be rather representative as they correspond to 6 of the 12 most common species present in Basel (Geoportal Kanton Basel-Stadt, 2019). The density of street trees above the building column (L D,bld , representing trees overhanging roofs) was assumed to be 0. ...
... This assumption was made given that no reliable information was available about the overlapping between tree crowns and roofs. Further details regarding the methodology used to derive the urban canopy parameters are given in the Appendix A. The resulting L can (Fig. 4e) have values ranging from 0 up to 3 m 2 m −2 , which is within the same range as reported in previous urban studies (Liss et al., 2010;Alonzo et al., 2015;Klingberg et al., 2017). ...
Article
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Street trees are more and more regarded as an effective measure to reduce excessive heat in urban areas. However, the vast majority of mesoscale urban climate models do not represent street trees in an explicit manner and, for example, do not take the important effect of shading by trees into account. In addition, urban canopy models that take interactions of trees and urban fabrics directly into account are usually limited to the street or neighbourhood scale and hence cannot be used to analyse the citywide effect of urban greening. In order to represent the interactions between street trees, urban elements and the atmosphere in realistic regional weather and climate simulations, we coupled the Building Effect Parameterisation with Trees (BEP-Tree) vegetated urban canopy model and the Consortium for Small-scale Modeling (COSMO) mesoscale weather and climate model. The performance and applicability of the coupled model, named COSMO-BEP-Tree, are demonstrated over the urban area of Basel, Switzerland, during the heatwave event of June–July 2015. Overall, the model compared well with measurements of individual components of the surface energy balance and with air and surface temperatures obtained from a flux tower, surface stations and satellites. Deficiencies were identified for nighttime air temperature and humidity, which can mainly be traced back to limitations in the simulation of the nighttime stable boundary layer in COSMO. The representation of street trees in the coupled model generally improved the agreement with observations. Street trees produced large changes in simulated sensible and latent heat flux, and wind speed. Within the canopy layer, the presence of street trees resulted in a slight reduction in daytime air temperature and a very minor increase in nighttime air temperature. The model was found to realistically respond to changes in the parameters defining the street trees: leaf area density and stomatal conductance. Overall, COSMO-BEP-Tree demonstrated the potential of (a) enabling city-wide studies on the cooling potential of street trees and (b) further enhancing the modelling capabilities and performance in urban climate modelling studies.
... The multispectral data could be used to parameterize the surface properties required for LST calculation such as broadband albedo (e.g., Vanino et al., 2018). The geometry of vegetation, especially of trees, is also an important parameter in realistic modeling the solar irradiance and LST (Tooke et al., 2012;Fogl and Moudrý, 2016;Klingberg et al., 2017;Hu and Wendel, 2019). The geometry of trees is a dynamic property especially in midlatitudes with significant phenologic changes of deciduous tree species (Hofierka et al., 2017). ...
... S2 NDVI -0.16, R 2 = 0.585, r = 0.76). For this purpose, LAI eTLS was calculated by the modified approach of Klingberg et al. (2017) based on Beer-Lambert Law: ...
... where R ground is the number of ground returns (including all return types), R total is the number of ground and canopy returns and β is a constant which can be expected to take a value around 2 (Richardson et al., 2009;Klingberg et al., 2017). We calculated the LAI eTLS for raster cells of 10 by 10 meters to match the resolution of Sentinel 2 imagery. ...
Article
Mitigation of urban heat islands requires understanding of the factors affecting the interaction of solar radiation and urban surfaces. In this study, we developed a novel algorithm for high-resolution spatial modeling of land surface temperature by combining the r.sun solar radiation model in GRASS GIS, the Stefan-Boltzmann Law and raster input data derived from a 3-D city model and Sentinel 2 multispectral imagery. The 3-D city model was the source of the urban land surface geometry and land cover properties, Sentinel 2 data was used to estimate broadband albedo and thermal emissivity. The developed modeling tool also implements the attenuation effect of high vegetation (transmittance) on beam solar irradiance at the ground beneath the vegetation canopy. The transmittance was estimated using the leaf area index as a proxy derived from a linear relationship between Sentinel 2 NDVI and terrestrial LiDAR. The computed land surface temperature was compared to the Landsat 8 derived land surface temperature with a good correlation expressed by a Pearson’s correlation coefficient of 0.88. The proposed approach has the advantage of providing the high spatial detail coupled with the flexibility of GIS to evaluate various geometrical and land surface properties for any daytime horizon.
... Specifically, trees located over mostly impervious surface (≥ 50%) are classified as street trees. A local leaf area density (inside individual trees) L D,loc of 1 m 3 m −2 was used according to measurements over urban trees during summertime in Gothenburg, Sweden (Klingberg et al., 2017). The tree species measured by Klingberg et al. (2017) are assumed to be rather representative as they correspond to 6 of the 12 most common species present in Basel (Basel-Stadt, 10 2019). ...
... A local leaf area density (inside individual trees) L D,loc of 1 m 3 m −2 was used according to measurements over urban trees during summertime in Gothenburg, Sweden (Klingberg et al., 2017). The tree species measured by Klingberg et al. (2017) are assumed to be rather representative as they correspond to 6 of the 12 most common species present in Basel (Basel-Stadt, 10 2019). The density of street trees above the building column (L D,bld , representing trees overhanging roofs) was assumed to be 0. ...
... This assumption was made giving that no reliable information was available about the overlapping between tree crowns and roofs. Further details regarding the methodology used to derive the urban canopy parameters are given in the Appendix A. The resulting L can (Figure 4e) have values ranging from 0 up to 3 m 2 m −2 , which is within the same range as reported in previous urban studies (Liss et al., 2010;Alonzo et al., 2015;Klingberg et al., 2017). 15 The thermal and physical properties of urban elements are listed in Table 2. ...
Preprint
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Street trees are more and more regarded as an effective measure to reduce excessive heat in urban areas. However, the vast majority of mesoscale urban climate models do not represent street trees in an explicit manner and for example do not take the important effect of shading by trees into account. In addition, urban canopy models that take interactions of trees and urban fabrics directly into account are usually limited to the street or neighbourhood scale and, hence, cannot be used to analyse the citywide effect of urban greening. In order to represent the interactions between street trees, urban elements and the atmosphere in realistic regional weather and climate simulations, we coupled the vegetated urban canopy model BEP-Tree and the mesoscale weather and climate model COSMO. The performance and applicability of the coupled model, named COSMO-BEP-Tree, are demonstrated over the urban area of Basel, Switzerland, during the heatwave event of June–July 2015. Overall, the model compared well with measurements of individual components of the surface energy balance and with air and surface temperatures obtained from a flux tower, surface stations and satellites. Deficiencies were identified for night-time air temperature and humidity, which can mainly be traced back to limitations in the simulation of the night-time stable boundary layer in COSMO. The representation of street trees in the coupled model generally improved the agreement with observations. Street trees produced large changes in simulated sensible and latent heat flux, and wind speed. Within the canopy layer, the presence of street trees resulted in a slight reduction in daytime air temperature and a very minor increase in night-time air temperature. The model was found to realistically respond to changes in the parameters defining the street trees: leaf area density and stomatal conductance. Overall, COSMO-BEP-Tree demonstrated the potential of (a) enabling city-wide studies on the cooling potential of street trees and (b) further enhancing the modelling capabilities and performance in urban climate modelling studies.
... The tree species categorization, as well as an accurate estimation of LAI, under both leaf-on and leaf-off conditions are challenging (high-density stands, logistical challenges, cost issues) to refine air pollution removal estimation by urban trees. To quantify ecosystem services such as air quality regulation, the LAI is an important index (Klingberg et al., 2017b). The urban areas are heterogeneous with a wide range of plant species and LAI values, emphasizing the importance of accurate estimates of LAI variation in cities in different climates for assessments of ecosystem services of urban forests (Alonzo et al., 2015;Klingberg et al., 2017b;Ren et al., 2018). ...
... To quantify ecosystem services such as air quality regulation, the LAI is an important index (Klingberg et al., 2017b). The urban areas are heterogeneous with a wide range of plant species and LAI values, emphasizing the importance of accurate estimates of LAI variation in cities in different climates for assessments of ecosystem services of urban forests (Alonzo et al., 2015;Klingberg et al., 2017b;Ren et al., 2018). The UFORE/i-Tree models estimate urban LAI from allometric relationships (Nowak et al., 2018), however, adjustments of LAI logarithms may be performed for crowns with dimensions beyond the limits for which the equations were developed, for instance for crowns with leaf loss, pest-diseases and/or after pruning (Alonzo et al., 2015). ...
... LAI-2200 LI-COR), hemispherical photography and/or remote sensing. Over larger areas, groundbased measurements are time consuming and costly, making remote sensing techniques more attractive (Alonzo et al., 2015;Klingberg et al., 2017b). LAI can be estimated from LiDAR data, using a Beer-Lambert law based approach, or by remote sensing to provide near-continuous observations at a high temporal and spatial resolution (Pleiades). ...
... The study sites are numbered according to their ID numbers in Table S1: 1) Suburban woodland, 2) Urban woodland, 3) Urban park, 4) Allotment area, 5) Infrastructural green space, 6) Urban park and woodland, 7) Residential area. Adapted from Klingberg et al. (2017a). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) ...
... LAI can be an appropriate indicator of the area of foliage available for photosynthesis, transpiration and deposition of air pollutants. However, LAI data can be time-consuming and costly to obtain compared to accurate, high-resolution canopy cover datasets (Klingberg et al., 2017a), which may be acceptable substitutes in some cases. Water retardation through storage and soil evaporation is related to the surface permeability (EEA, 2015;Olsson et al., 2013;Peng et al., 2016), and leaf area through transpiration (Benyon and Doody, 2015;Zhang et al., 1999Zhang et al., , 2001. ...
... At each study site the leaf area index (LAI) and canopy cover were estimated from aerial LiDAR (light detection and ranging) data covering Gothenburg municipality acquired in 2010. Using laser penetration metrics, high resolution maps of canopy cover (1 m) and LAI (10 m) were produced following Klingberg et al. (2017a). Permeable surface (%) estimates were acquired from map information, and soil types were estimated using wet sieved soil samples collected at the study sites, following procedures presented by Van Kleef (2017). ...
Article
Full-text available
Ongoing urban exploitation is increasing pressure to transform urban green spaces, while there is increasing awareness that greenery provides a range of important benefits to city residents. In efforts to help resolve associated problems we have developed a framework for integrated assessments of ecosystem service (ES) benefits and values provided by urban greenery, based on the ecosystem service cascade model. The aim is to provide a method for assessing the contribution to, and valuing, multiple ES provided by urban greenery that can be readily applied in routine planning processes. The framework is unique as it recognizes that an urban greenery comprises several components and functions that can contribute to multiple ecosystem services in one or more ways via different functional traits (e.g. foliage characteristics) for which readily measured indicators have been identified. The framework consists of five steps including compilation of an inventory of indicator; application of effectivity factors to rate indicators' effectiveness; estimation of effects; estimation of benefits for each ES; estimation of the total ES value of the ecosystem. The framework was applied to assess ecosystem services provided by trees, shrubs, herbs, birds, and bees, in green areas spanning an urban gradient in Gothenburg, Sweden. Estimates of perceived values of ecosystem services were obtained from interviews with the public and workshop activities with civil servants. The framework is systematic and transparent at all stages and appears to have potential utility in the existing spatial planning processes.
... The study sites are numbered according to their ID numbers in Table S1: 1) Suburban woodland, 2) Urban woodland, 3) Urban park, 4) Allotment area, 5) Infrastructural green space, 6) Urban park and woodland, 7) Residential area. Adapted from Klingberg et al. (2017a). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) ...
... LAI can be an appropriate indicator of the area of foliage available for photosynthesis, transpiration and deposition of air pollutants. However, LAI data can be time-consuming and costly to obtain compared to accurate, high-resolution canopy cover datasets (Klingberg et al., 2017a), which may be acceptable substitutes in some cases. Water retardation through storage and soil evaporation is related to the surface permeability (EEA, 2015;Olsson et al., 2013;Peng et al., 2016), and leaf area through transpiration (Benyon and Doody, 2015;Zhang et al., 1999Zhang et al., , 2001. ...
... At each study site the leaf area index (LAI) and canopy cover were estimated from aerial LiDAR (light detection and ranging) data covering Gothenburg municipality acquired in 2010. Using laser penetration metrics, high resolution maps of canopy cover (1 m) and LAI (10 m) were produced following Klingberg et al. (2017a). Permeable surface (%) estimates were acquired from map information, and soil types were estimated using wet sieved soil samples collected at the study sites, following procedures presented by Van Kleef (2017). ...
Article
Ongoing urban exploitation is increasing pressure to transform urban green spaces, while there is increasing awareness that greenery provides a range of important benefits to city residents. In efforts to help resolve associated problems we have developed a framework for integrated assessments of ecosystem service (ES) benefits and values provided by urban greenery, based on the ecosystem service cascade model. The aim is to provide a method for assessing the contribution to, and valuing, multiple ES provided by urban greenery that can be readily applied in routine planning processes. The framework is unique as it recognizes that an urban greenery comprises several components and functions that can contribute to multiple ecosystem services in one or more ways via different functional traits (e.g. foliage characteristics) for which readily measured indicators have been identified. The framework consists of five steps including compilation of an inventory of indicator; application of effectivity factors to rate indicators' effectiveness; estimation of effects; estimation of benefits for each ES; estimation of the total ES value of the ecosystem. The framework was applied to assess ecosystem services provided by trees, shrubs, herbs, birds, and bees, in green areas spanning an urban gradient in Gothenburg, Sweden. Estimates of perceived values of ecosystem services were obtained from interviews with the public and workshop activities with civil servants. The framework is systematic and transparent at all stages and appears to have potential utility in the existing spatial planning processes. © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
... Data was rasterized at 1 m 2 . We estimated LAI from these aerial LIDAR data using variations of the Beer-Lambert law, according to the equations published by Klingberg et al. (2017) [52]. Canopy area was determined by using supervised machine learning classification with LiDAR and multispectral data to delineate areas of canopy cover. ...
... Data was rasterized at 1 m 2 . We estimated LAI from these aerial LIDAR data using variations of the Beer-Lambert law, according to the equations published by Klingberg et al. (2017) [52]. Canopy area was determined by using supervised machine learning classification with LiDAR and multispectral data to delineate areas of canopy cover. ...
Article
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Exposure to greenness has been studied through objective measures of remote visualization of greenspace; however, the link to how individuals interpret spaces as green is missing. We examined the associations between three objective greenspace measures with perceptions of greenness. We used a subsample (n = 175; 2018–2019) from an environmental cardiovascular risk cohort to investigate perceptions of residential greenness. Participants completed a 17-item survey electronically. Objective measurements of greenness within 300 m buffer around participants home included normalized difference vegetation index (NDVI), tree canopy and leaf area index. Principal component analysis reduced the perceived greenspaces to three dimensions reflecting natural vegetation, tree cover and built greenspace such as parks. Our results suggest significant positive associations between NDVI, tree canopy and leaf area and perceived greenness reflecting playgrounds; also, associations between tree canopy and perceived greenness reflecting tree cover. These findings indicate that the most used objective greenness measure, NDVI, as well as tree canopy and leaf area may most align with perceptions of parks, whereas tree canopy alone captures individuals’ perceptions of tree cover. This highlights the need for research to understand the complexity of green metrics and careful interpretation of data based on the use of subjective or objective measures of greenness.
... It represents an important attribute of vegetation structure and is regularly used in research concerning photosynthetic activity, energy exchange, carbon sequestration, and water and nutrient use (Bréda 2008). LAI thus applies to ecological monitoring at various scales-from mapping terrestrial biomes and crop yields, to more detailed modeling of how LAI influences rainfall interception and microclimates in urban settings (Gower et al. 1999;Xiao and McPherson 2002;Hardin and Jensen 2007;Venkatraman et al. 2016;Klingberg et al. 2017). As a key variable of terrestrial ecosystem processes, research in climate change designates LAI as an indicator of fluctuation in temperatures and humidity in relation to global warming, land cover change, and human activity (as in Buermann et al. 2001;Jiapaer et al. 2015). ...
... Whilst LAI and PAI measurements for trees are typically appraised for forest stands, orchards, and crop production, estimations of solitary (or isolated) trees in urban landscapes are less studied (Chianucci et al. 2015). Recognized challenges are proximity to nearby built infrastructure, as well as instruments sensitive to reflectance from foliage and changeable light conditions that provide inaccurate rendering (Chianucci et al. 2015;Klingberg et al. 2017). Several studies have investigated the technical challenges of capturing LAI (PAI) and wood area index (WAI) values in urban settings and as such deal with only a handful of tree species (as described in Nowak 1996;Peper and McPherson 2003;Chianucci et al. 2015;Wei et al. 2020). ...
Article
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Background: We present the plant area index (PAI) measurements taken for 63 deciduous broadleaved tree species and 1 deciduous conifer tree species suitable for urban areas in Nordic cities. The aim was to evaluate PAI and wood area index (WAI) of solitary-grown broadleaved tree species and cultivars of the same age in order to present a data resource of individual tree characteristics viewed in summer (PAI) and in winter (WAI). Methods: All trees were planted as individuals in 2001 at the Hørsholm Arboretum in Denmark. The field method included a Digital Plant Canopy Imager where each scan and contrast values were set to consistent values. Results: The results illustrate that solitary trees differ widely in their WAI and PAI and reflect the integrated effects of leaf material and the woody component of tree crowns. The indications also show highly significant (P < 0.001) differences between species and genotypes. The WAI had an overall mean of 0.91 (± 0.03), ranging from Tilia platyphyllos ‘Orebro’ with a WAI of 0.32 (± 0.04) to Carpinus betulus ‘Fastigiata’ with a WAI of 1.94 (± 0.09). The lowest mean PAI in the dataset was Fraxinus angustifolia ‘Raywood’ with a PAI of 1.93 (± 0.05), whereas Acer campestre ‘Kuglennar’ represents the cultivar with the largest PAI of 8.15 (± 0.14). Conclusions: Understanding how this variation in crown architectural structure changes over the year can be applied to climate responsive design and microclimate modeling where plant and wood area index of solitary-grown trees in urban contexts are of interest.
... [80,113,114]) are added: [115]. The LAD of the trees is selected based on a study by Klingberg et al. [116], who mapped the leaf area of urban greenery using aerial LiDAR (light detection and ranging) and ground-based measurements in Gothenburg, Sweden. The reported LADs for Maples and Chestnuts, very common tree species for the area of interest, were between around 0.6 and 2.1 m -1 . ...
... coniferous trees in the explicitly modelled area of the domain, only deciduous trees are used as a simplification. With 1.0 m -1 , a slightly lower LAD than the average from Klingberg et al.'s study [116] is applied, as the trees already started to defoliate in the VPs (see Fig. 3). Many other urban MC CFD studies addressed dense and concretedominated city environments [65,71,80,81] and therefore either only included the tree crowns or fully omitted the microclimatic impact of vegetation. ...
Article
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The urban microclimate is a rapidly evolving field of research gaining increasing interest from public authorities and researchers. However, studies at high-latitude cities are scarce and researchers primarily focus on summerly overheating. This study focuses on the validation process of a CFD model that applies the 3D URANS approach with the realisable k-ε turbulence model at a highly complex urban area in Trondheim, Norway (63.4° N) during autumn. The CFD model features a polyhedral grid of the urban environment, including geometrically explicitly modelled buildings and trees in the area of interest. Furthermore, solar radiation, longwave radiation exchange, heat transfer from the buildings, heat storage in the urban surface, and the thermal effects of evapotranspiration from trees and grass surfaces are considered. The CFD model is validated with experimental results from a network of five mobile and one reference weather stations in the study area, providing hourly-averaged measurements for wind speed, wind direction (only reference weather station) and air temperature for two 48-h periods from September 27–28 and October 19–20. The results show that the CFD model is well able to reproduce the measured conditions at the area of interest with a mean R² of 0.60, 0.63, and 0.96 for wind speed, wind direction and air temperature, respectively, at the reference weather station. It will be used in future studies, including the analysis of the impact of urban microclimate on buildings’ energy performance, outdoor thermal and pedestrian wind comfort.
... The indirect methods have also been widely used for measurements of LAI for individual trees, especially the three methods considered in this study: i) TLS (Béland et al., 2011;Hu et al., 2018;Y. Li et al., 2017c;Moorthy et al., 2011); ii) LAI-2200 (Abraha and Savage, 2010;Behera et al., 2010;Chianucci et al., 2015;Gillner et al., 2015;Gratani et al., 2016;Jiapaer et al., 2017;Klingberg et al., 2017;S. Li et al., 2017b;T.E. ...
... Li et al., 2017b;T.E. Morakinyo et al., 2017;Moser et al., 2015;Ow et al., 2019;Peper and McPherson, 2003;Shahidan et al., 2010;Taib et al., 2019;Yuan et al., 2017;Zheng et al., 2018); and iii) DHP (Alonzo et al., 2015;Chianucci et al., 2015;de Abreu-Harbich et al., 2015;Klingberg et al., 2017;J. Li et al., 2017a;Morakinyo et al., 2018Morakinyo et al., , T.E. ...
Article
Field measurements of leaf area density (LAD) and leaf area index (LAI) for individual trees have increased in importance and relevance with the advent of high spatial resolution remote sensing for the urban landscape. However, indirect field measurements of LAD/LAI for widely dispersed individual trees have not been comprehensively evaluated. The present study compares the accuracy of three indirect LAD/LAI estimation methods, including single-return terrestrial laser scanning (TLS), LAI-2200, and digital hemispherical photography (DHP) on urban trees. To this end, field measurements were inter-compared and physically modeled by discrete anisotropic radiation transfer (DART). The inter-comparisons of field data revealed substantial inconsistencies between DHP and the other two approaches. For the physical modeling, reference LAI was obtained from realistic 3-D tree objects in DART, and the LAD/LAI was derived from simulated TLS, LAI-2200, and DHP acquisitions and was evaluated against the references. The physical modeling results showed that TLS could reasonably estimate LAD/LAI for LAD < 3 and LAI < 6 using a small (0.3 m) voxel size. However, the measurements became saturated for dense foliage (LAD > 3 and LAI > 6). The LAD/LAI accuracy was sharply reduced as voxel size increased. In addition, the trunks caused overestimation for both of LAD and LAI, while branches caused LAD underestimation and LAI overestimation. Further research is needed to compensate for the effects of occlusions and clumping in the estimates of LAD/LAI for dense-foliated trees using TLS. LAI-2200 grossly underestimated LAD for all cases, while it accurately estimated LAI for LAI < 5 and became gradually saturated for LAI > 5. The estimation accuracy of LAI-2200 declined markedly with increasing uncertainty in crown shape. The 90° view cap had higher accuracy than the 180° or 270° view caps using four or all five LAI-2200 rings. Additional sensors or algorithms for crown shape measurement should be developed for LAI-2200 to reduce its reliance on other data sources. DHP is not recommended for individual trees as the LAI estimations were biased from the reference values, and improvements in reliability will depend on new algorithms to account for differences in path length. These results serve as a benchmark for evaluating the accuracy of in situ LAD/LAI measurement techniques and for optimizing the configurations required for each indirect measurement method applied to individual trees.
... The Gothenburg LiDAR data were obtained in October 2010. Further details of the data and data processing can be found in Klingberg et al. (2017). The methodology was developed for mapping effective leaf area index (L e ), which revealed a high positive correlation to canopy cover (Klingberg et al. 2017). ...
... Further details of the data and data processing can be found in Klingberg et al. (2017). The methodology was developed for mapping effective leaf area index (L e ), which revealed a high positive correlation to canopy cover (Klingberg et al. 2017). One of the experimental sites, 3 Skatås, was not covered by the Gothenburg LiDAR data. ...
Article
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Birds that are foraging in tree canopies can cause a substantial decrease in arthropod numbers. Trees may benefit from avian insectivores attacking insect herbivores. In a field study, we tested whether the intensity of bird predation on caterpillars is linked quantitatively to leaf damage caused by insect herbivores, a hypothesized relationship that previously was poorly investigated. Artificial caterpillars were placed in the lower part of oak trees (Quercus robur) in urban and suburban sites across the city of Gothenburg, Sweden. Two days later, we recorded the survival: the pooled predation rate was 11.5% (5.7% day⁻¹). Mean predation rate per tree was 10.4%. Mean leaf damage, i.e. leaf area eaten by insect herbivores, per tree was 5.7% but there was large variation between trees. We found a significant negative relationship between survival probability of caterpillars and leaf damage in an analysis using a mixed model logistic regression. This suggests that caterpillars are at high risk of bird attacks in trees with a high degree of leaf damage and avian insectivores may increase the foraging effort in the foliage of such oak trees. Our findings concerning the quantitative relationship between the predator–prey interactions and plant damage suggested tentatively that the survival probability of caterpillars decreases rapidly at 15–20% leaf damage in lower part of oak canopies. Furthermore, our findings add credence to the idea of using artificial caterpillars as a means to obtain standardized comparisons of predation rates in various habitats. Electronic supplementary material The online version of this article (10.1007/s00442-018-4234-z) contains supplementary material, which is available to authorized users.
... (2017) measured LAD ranging from 0.67 to 1.56 m 2 m − 3 for six common urban tree species [148]. LAD in CFD modeling ranged from 0.1 to 4 m 2 m − 3 , with a mean value of approximately 1 m 2 m − 3 [43]. ...
Article
In order to address the increased urban heat island (UHI) effects and energy demand caused by global urbanization, it is imperative to seek sustainable urban design solutions. It is widely acknowledged that urban green infrastructure (UGI), which includes site-scale vegetation and building-integrated vegetation, influences the energy consumption of urban buildings. In the planning and design phases of UGI, numerical simulations are essential tools for evaluating and optimizing design strategies. However, the methodology for the simulation at various scales is still unclear, necessitating a comprehensive review of relevant studies. This review examined the research conducted on UGI modeling in numerical simulations of building energy consumption over the past 35 years and outlined the general workflow of these simulations. The numerical methods and tools for each step, as well as the coupling and validation methods for these tools, were described in detail. Thus, this study equips researchers with the knowledge necessary to analyze the impact of UGI on the energy consumption of buildings using numerical simulations. According to the review, existing building energy model (BEM) tools have not yet integrated modeling of site-scale vegetation for microclimate and shading. Future collaboration between urban climatologists and building physicists should be encouraged to improve the integration of climate and UGI shading simulations with BEM in order to simplify the use of numerical simulation tools.
... (2017) measured LAD ranging from 0.67 to 1.56 m 2 m − 3 for six common urban tree species [148]. LAD in CFD modeling ranged from 0.1 to 4 m 2 m − 3 , with a mean value of approximately 1 m 2 m − 3 [43]. ...
Article
Smart metering and the internet of things (IoT) accumulate massive time-series building data. Mining operation patterns from time-series data have huge potential to provide extra information for improving energy efficiency. Previous studies mainly focused on mining control patterns of the heating, ventilation, and air-conditioning system (HVAC). Mining operational patterns from time-series data can help building managers identify energy-wasting operations. This study proposes three methods of mining the operation hours on the time-series data of hundreds of buildings. A key performance indicator (KPI) of facility hours is proposed to indicate the discrepancy between occupants’ requirements and facility hours. The study is carried out on the 240 office buildings of building data genome project 2 (BDG2). The proposed methods are evaluated by comparing mined hours with annotated hours. The impacts of eight operational KPIs are quantified with correlation coefficients and ensemble learning. The practicality of the proposed methods is evaluated on three case buildings. The results show that the cumulative histogram method is effective in mining operation hours. The regression results indicate that mined KPIs can improve the energy prediction accuracy (R²) from 0.35 to 0.41. The impacts of operational KPIs reveal that the KPI of weekends has a tremendous impact on energy consumption. The case study results show that reducing unnecessary facility hours can save from 2.9% to 10.6% energy. This study verifies that operational KPIs mined from time-series data can provide building managers with intuitive knowledge for improving operations.
... Klingberg et al. [100] explored a method of evaluating the urban Leaf Area Index (LAI) using an aerial LiDAR dataset. The LAI is defined as the ratio between total one-sided green leaf area and unit ground surface area [222]. ...
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From the use of a pinhole camera placed under a water tank, which was proposed almost 100 years ago, to the application of modern digital cameras mounted with sophisticated fisheye lenses, acquisition methods for capturing hemispherical photographs undergone vigorous research and development. Over the past few decades, such photographs have been extensively used in evaluating energy and environmental aspects in urban contexts. In this review article, the advantages, limitations, and challenges of the various methods of acquiring photographs are described and compared. This involves both the devices themselves and the software tools. Several methods of direct acquisition of hemispheric photographs involving digital cameras, smartphones, the use of drones for photographs at elevations, and the application of thermal imaging technologies are discussed in detail. Indirect methods for generating hemispheric photographs are also discussed, highlighting the use of images from applications such as Google Street View (GSV). Based on a review of technical literature, several applications in energy and the environment that use information from hemispheric photographs as an analysis tool are presented and discussed. Among others, the following are discussed: the quantification of solar radiation potential; the assessment of indicators of local temperature and level of thermal comfort for pedestrians in urban areas; indoor and outdoor daylighting; and air and light pollution. Finally, several potential future research directions for the use of hemispherical photographs in built environments are discussed. These include advances in image processing, use of thermal imaging, solar potential assessment of solar-powered vehicles, applications of drone-mounted hemispherical photography, and fisheye videos.
... The indirect methods assume that (i) light does not transmit through the foliage as it is black, (ii) the leaf sizes are smaller compared to the canopy and the field of view (FOV) of the sensor, and (iii) leaves are randomly distributed. DHP based estimates could progressively replace LAI-2200 and AccuPAR because of its accuracy, sensitivity, extraction of clumping effect, and cost-effectiveness Garrigues et al., 2008;Klingberg et al., 2017). ...
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The leaf area index (LAI) serves as a proxy to understand the dynamics of plant productivity, energy balance, and gas exchange. Cost-effective and accurate estimation of LAI is essential for under-assessed carbon-rich tropical forests, e.g., mangroves. Here, we developed allometric equations to estimate LAI using a combination of non-destructive, optical measurements through digital hemispherical photographs (DHP), and genetic programming-based Symbolic Regression (SR). We used three structural variables: diameter at breast height (DBH), tree density (TD), and canopy height (Ht) for a mangrove forest in the BhitarKanika Wildlife Sanctuary (BWS), located along the Eastern coast of India. Triplet combination using SR provided the best equation (R² = 0.51) than any singlet or duplet combination of the variables, and even it was better than Partial Least Square (PLS) based regression (R² = 0.42). To the best of our knowledge, the current study is the maiden attempt to develop an allometric model to estimate LAI for a mangrove ecosystem in India. In-situ measurements of structural variables such as DBH, Ht, and TD can be used for LAI estimates, as shown here. LAI estimates using cost-effective methods would greatly enhance our understanding of the spatial and temporal dynamics of mangrove ecosystems.
... There are also studies dedicated to the calculation of micro-scale vegetation indices, squares, parks, or street afforestation indices, such as leaf area, shading, and density indices, used in studies for Cuiabá, in Mato Grosso (Brazil) and Gothenburg (Sweden) (Oliveira et al., 2013;Klingberg et al., 2017). ...
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Green spaces in cities are seen as beneficial to, for example, the microclimate, human health, and ecological networks. In this sense, this study aims to evaluate the relationship between urban green areas (UGA) and the effectively urbanized area (EUA) in the city of Rio Grande, in the extreme south of Brazil. The following indicators were used: UGA per inhabitant and per 100,000 inhabitants, the percentage of UGA in the urban perimeter, and according to a radius of influence (buffers). Voronoi diagrams were also generated to verify the UGA concentration or dispersion, and the relationship with socioeconomic indicators (population density and average income). The results: 1) 59.82 Ha of UGA/100,000 inhab.; 2) 5.98 m² of UGA/inhabitant; 3) 2.45% UGA in the EUA; 4) 50.00% and 84.13% of the EUA covered by radii of influence of 300 m and 1200 m from the UGA; 5) and 67.59% of the EUA by radii of influence of 1 km of UGA > 1 Ha. These values are considered low but in line with the values found for other Brazilian cities or in other countries. Therefore, it is expected to contribute to the debate related to the theme and actions to improve the cities quality and distribution of green spaces.
... This manual method is known as the direct LAI method, and is widely used for crops and adapted for vegetation in small-scale studies (Bréda 2003;Pérez et al. 2017). This method is useful in agriculture and ecological studies where the plant is harvested to measure the leaf area (Klingberg et al. 2017). ...
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This study analysed the net rainfall components under different ages and leaf area index (LAI) of the oil palm to determine the contribution of net rainfall towards water requirements of the palm. We hypothesised that older palms, with their higher LAI, would have lower net rainfall due to higher interception of rain. The study was conducted in oil palm plantations in Mendis village, Bayung Lincir District, Sumatra. Tipping-bucket rain gauges connected to data loggers were used to measure the rainfall components (throughfall, stemflow, interception and gross rainfall) at ten-minute intervals for four months. The proportions of throughfall, stemflow, and interception for the oil palm aged between 5 to 20 years were 92.2%-58%, 2.4-0.7%, and 5.4%-41%, respectively. The equations relating throughfall (Tf), stemflow (Sf), and net rainfall (Pn) to LAI were Tf =-8.5032 LAI + 116.74, Sf =-0.469 LAI + 3.8808, and Pn =-8.9722 LAI + 120.62, respectively. Under various oil palm ages, net rainfall (Pn) had an inverse linear relationship with an increase in LAI by 3.5 and 7.2 with a decrease in net rainfall from 94.6% to 58.8%. The results from this study should serve as a guide to the water management of oil palm plantations.
... LiDAR is a breakthrough technology offering photon (laser) penetration through the tree and shrub canopy layer down to the ground level to obtain returns (echoes) that provide a description of the vertical structure of vegetation (Matasci et al., 2018;. Various VIs derived from airborne laser scanning (ALS) and point cloud processing have been used to estimate the height of UF (Alexander et al., 2018;Plowright et al., 2016), leaf area index (LAI) (Klingberg et al., 2017) and the biomass of greenery (Dalponte et al., 2018;Singh et al., 2015). However, the volume of tree crowns is very difficult to precisely measure, mostly due to their irregular shapes. ...
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Modern cities face challenges in responding to the needs of diverse groups, therefore urban space must be appropriately shaped to be as resident-friendly as possible. Particular attention needs to be paid to urban vegetation, which is an essential component of a suitable quality of life. Research to date has often relied on two-dimensional (2D) mapping of urban vegetation using remote sensing imagery and vegetation indicators, where greenery is evenly distributed regardless of the cubature. However, in reality, vegetation's spatial and vertical structure varies, and the layers often overlap. In the current paper concerning Luxembourg City, we propose a novel 3D method exploring such indices as Vegetation 3D Density (V3DI) and Vegetation Volume to Building Volume (VV2BV). The goal of the study is to investigate the spatial relationship between the volume of vegetation and of buildings in the rapidly developing Luxembourg City. The vegetation volume was calculated using airborne laser scanning point clouds (ALS LiDAR) processed into voxels (0.5 m). The volume of the buildings was calculated based on the results of 3D ALS LiDAR point cloud modelling. Proposed spatial indices were estimated for districts, for cadastral parcels, in a cell grid of 100 m and for each building individually, using a 100 m buffer. We found that in 2019, urban forests covered 1689 ha of Luxembourg City, accounting for 33 per cent of the entire administrative area. The 3D GIS analyses show that the total volume of vegetation (> 1.0 m above ground) was about 40 million m³, equating to 328 m³ of greenery per resident. The V3DI produced a value of 0.77 m³/m². The overall VV2BV(%) index calculated for Luxembourg was 41.6 per cent. Only five districts of Luxembourg were characterized by a high value for the VV2BV index, which indicates areas with a high level of green infrastructure to contribute to health and a better quality of life.
... Furthermore, tree canopies weaken the urban heat-island effect by reducing air temperature through shading and evapotranspiration. As well as these benefits, trees reduce urban flood risk because stormwater runoff is mitigated by rainwater interception and storage in urban tree canopies [1,4,5]. Finally, urban trees also have important ecological functions in providing habitats for urban wildlife, abating noise, decreasing wind speed, increasing surface runoff and conditioning the urban microclimate [6,7], maintaining urban ecological balance, and protecting 2 of 18 biodiversity [8 -10]. ...
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Tree information in urban areas plays a significant role in many fields of study, such as ecology and environmental management. Airborne LiDAR scanning (ALS) excels at the fast and efficient acquisition of spatial information in urban-scale areas. Tree extraction from ALS data is an essential part of tree structural studies. Current raster-based methods that use canopy height models (CHMs) suffer from the loss of 3D structure information, whereas the existing point-based methods are non-robust in complex environments. Aiming at making full use of the canopy’s 3D structure information that is provided by point cloud data, and ensuring the method’s suitability in complex scenes, this paper proposes a new point-based method for tree extraction that is based on 3D morphological features. Considering the elevation deviations of the ALS data, we propose a neighborhood search method to filter out the ground and flat-roof points. A coarse extraction method, combining planar projection with a point density-filtering algorithm is applied to filter out distracting objects, such as utility poles and cars. After that, a Euclidean cluster extraction (ECE) algorithm is used as an optimization strategy for coarse extraction. In order to verify the robustness and accuracy of the method, airborne LiDAR data from Zhangye, Gansu, China and unmanned aircraft vehicle (UAV) LiDAR data from Xinyang, Henan, China were tested in this study. The experimental results demonstrated that our method was suitable for extracting trees in complex urban scenes with either high or low point densities. The extraction accuracy obtained for the airborne LiDAR data and UAV LiDAR data were 99.4% and 99.2%, respectively. In addition, a further study found that the aberrant vertical structure of the artificially pruned canopy was the main cause of the error. Our method achieved desirable results in different scenes, with only one adjustable parameter, making it an easy-to-use method for urban area studies.
... However, the integration of these technologies and data are less established in urban forestry, given the cost of data acquisition compared to less traditionally valued economic returns (e.g., human health and wellbeing benefits in urban forests compared to fiber production in commercial forests). Moreover, in cities there is often demand/pressure to acquire LiDAR data during leaf-off periods outside of the growing season in order to have better coverage of built/gray infrastructure (Klingberg et al., 2017). ...
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Forest ecosystem resilience is of considerable interest worldwide, particularly given the climate crisis, biodiversity loss, and recent instances of zoonotic diseases linked to deforestation and forest loss. Novel, digital-based technologies are also increasingly ubiquitous. We provide a more comprehensive understanding of how these new technologies are being used for forest management in different sectors and contexts, and discuss potential implications and future research needs for forestry researchers, managers, and policymakers. We carried out a literature database search and scoping review to collect peer-reviewed articles from 2010-2020, and developed a forest-technology classification to identify hardware and/or software technologies and techniques, methodology used, forest management application(s), spatial and temporal context, subsequent challenges and limitations, and opportunities. A qualitative analysis revealed a strong emphasis on remote sensing-based innovations for forest monitoring, planning, and management, where machine-learning techniques also play an important role in data collection, processing, and analysis. Data fusion approaches are also becoming more common, enabled by open-source datasets and data sharing practices. More emerging technologies and applications include virtual/augmented environments for understanding human-nature relationships and behaviour patterns, automated workflows for forestry operations, and urban green infrastructure mapping and ecosystem services assessments via social media and mobile tracking applications. The continued adoption of digital-based tools will likely bring about new research questions about forest ecosystems as dynamic social, ecological, and technological landscapes, and future work should more closely examine how forestry researchers, managers, and stakeholders can anticipate and adapt to both environmental and technological uncertainty change in a forest-ecosystem context.
... One is the extraction of tree features such as canopy volume, branches and trunks to build 3D tree models [35]. The other is the extraction of tree parameters that may be used by urban foresters for assessing the ecosystem service benefits of trees such as canopy height and volume leaf area index [36,37], leaf area density distribution [38] or the hazards of potential wildfires in areas of urban interfaces [39]. ...
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Estimation of urban tree canopy parameters plays a crucial role in urban forest management. Unmanned aerial vehicles (UAV) have been widely used for many applications particularly forestry mapping. UAV-derived images, captured by an onboard camera, provide a means to produce 3D point clouds using photogrammetric mapping. Similarly, small UAV mounted light detection and ranging (LiDAR) sensors can also provide very dense 3D point clouds. While point clouds derived from both photogrammetric and LiDAR sensors can allow the accurate estimation of critical tree canopy parameters, so far a comparison of both techniques is missing. Point clouds derived from these sources vary according to differences in data collection and processing, a detailed comparison of point clouds in terms of accuracy and completeness, in relation to tree canopy parameters using point clouds is necessary. In this research, point clouds produced by UAV-photogrammetry and-LiDAR over an urban park along with the estimated tree canopy parameters are compared, and results are presented. The results show that UAV-photogrammetry and-LiDAR point clouds are highly correlated with R 2 of 99.54% and the estimated tree canopy parameters are correlated with R 2 of higher than 95%.
... The results obtained in this study are similar to those of Klingberg et al. (2017) indicating that individual urban trees have a higher LAI value than the trees of a stand, although in this case the LAI measurement was not specifically the tree, but the area of pedestrian traffic which the tree influences. However, an additional study involving the same species in both contexts could be necessary to analyze the influence of these conditions. ...
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The relationship between leaf area index (LAI), ultraviolet radiation (UV) and temperature measured at 1.5 meters (T°1.5) and at ground level (T°s) was studied, in three urban forest areas of Talca City, Chile. Circular plots with different tree projection coverage areas were defined for the registration of the T° and UV data. Measurements between 13 and 14 hours were performed and distributed for each year season, while the LAI was obtained with a single record per season; the selection zones and measurement points were done by a non-probabilistic method. The results showed that LAI, as a factor, had a statistical significance effect for UV, T°1.5 and T°s, with 0.0081; 0.0058 and 0.0334 respectively (P <0.05), demonstrating that LAI is related as indicator of the mitigating function of urban forest, regardless of season of the year. The correlations were positive, although weak, as they failed to robustly explain their relationship with the measured variables; and LAI did not fully explain the variability that it has with T°s and T°1.5 (r = 0.47 and r = 0.48 respectively), the same for UV (r = 0.38). In the context studied, it was not possible to determine that the LAI is an index that explains the variability presented, obtaining R2 of 22.15%, 23.28% and 14.47% for T°s, T°1,5 and UV, respectively, so the tree species and the characteristics associated with the plots, would explain the high dispersion of the results. The presence of trees favors the condition of T ° and UV in the city pedestrian displacements.
... Urban vegetation, which can provide a large number of ecosystem services such as temperature reduction and air quality regulation, has been recognized as an important factor for urban ecosystem (Klingberg et al. 2017). Therefore, the process of mapping, quantifying and monitoring changes in the physical characteristics of vegetation has become essential to understand the dynamics of state variables in urban ecosystem (Balacco et al. 2015, Nolè et al. 2015, and the regular and accurate observation of urban vegetation status and damages can facilitate the development of adequate management strategies (Tillack et al. 2014). ...
Article
Leaf area index (LAI) is an important indicator of vegetation growth and health monitoring. The free access of Sentinel-2 optical satellite data from European Space Agency (ESA) since June 2015 made it possible to determine dynamic monitoring of LAI in a large area and a short re-entry period, owing to its high spatial resolution (up to 10 m) and unique band combination. These features of Sentinel-2 may bring great application potential in urban forestry management and ecological environment monitoring. In case of Zhongshan city in Guangdong Province, based on Sentinels Application Platform (SNAP) software and two scenes of Sentinel-2 data, LAI of the whole city, as well as specific areas, were retrieved and analyzed. The retrieval result was consistent with the ecological spatial pattern and the vegetation protection status in Zhongshan city, also highly consistent with the field LAI measurement in the forest in a reservoir. The result indicates that this method has good applicability and accuracy in urban LAI inversion.
... Furthermore, tree canopies weaken the urban heat-island effect by reducing air temperature through shading and evapotranspiration. As well as these benefits, trees reduce urban flood risk because stormwater runoff is mitigated by rainwater interception and storage in urban tree canopies [1,4,5]. Finally, urban trees also have important ecological functions in providing habitats for urban wildlife, abating noise, decreasing wind speed, increasing surface runoff and conditioning the urban microclimate [6,7], maintaining urban ecological balance, and protecting biodiversity [8][9][10]. ...
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Canopy gaps affect the spatial distribution of radiation in the canopy. The estimation of gap fraction (GF) is important for the study of leaf area index (LAI). Terrestrial laser scanning (TLS) has been widely used for retrieving canopy structure parameters through massive high-resolution spatial samples in the form of 3-D point cloud data sets. Monte Carlo simulations can be used to obtain approximate solutions to quantitative problems through a large number of random sampling while avoiding complicated mathematical calculations. Monte Carlo simulations are suitable for analyzing TLS data and could help overcome resolution reductions inherent to current point cloud processing approaches. However, few studies have applied the Monte Carlo method to capture the canopy structure features implicit in high-resolution point clouds. This letter proposes a method for estimating the GF based on Monte Carlo simulations. A large number of randomly simulated laser beams were emitted to identify the canopy and gaps according to the discrimination distance, and the results were compared with the GFs derived from digital hemispherical photography (DHP). In general, the proposed TLS method estimated smaller GFs than the DHP method since DHP was vulnerable to exposure conditions and complex canopy structure. The GF estimated by the two methods is consistent (R² = 0.7522), indicating the effectiveness of the Monte Carlo method.
... They observed different spatial distributions and associations with the social status of residents related to different types of urban greenery. The literature suggests that a large number of ecosystem services benefitting the urban population are provided by trees, for instance, reducing the temperature through shading and evapotranspiration [26]. ...
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Measuring urban environmental performance supports understanding and improving the livability and sustainability of a city. Creating a more livable and attractive environment facilitates a greater shift to active and greener transport modes. Two key aspects, among many others, that determine the environmental performance of an urban area are greenery and noise. This study aims to map street-level greenery and traffic noise using emerging data sources including crowd-sourced mobile phone-based data and street-level imagery data in Sydney, Australia. Results demonstrate the applicability of emerging data sources and the presented advanced techniques in capturing the seasonal variations in urban greenery and time-dependent nature of traffic noise. Results also confirm the presence of a negative correlation between urban greenery and traffic noise.
... It is known that during the construction of the road, a set of tasks is carried out to reduce its negative effect on the environment. This group of methods aimed at protecting atmospheric air from pollution near the road include the following: planting vegetation [5][6][7][8][9][10]; installing barriers (screens) near highways [10][11]; the usage of axial fans on barriers; the usage of special coatings on the road [12][13][14]; removal of polluted air from the road surface (usage of local exhaust devices on the road) [10]; and usage of underground tunnels to unload transport routes. ...
Article
In this study, the methodological foundations of the technology for the local reduction of chemical pollution from vehicles were improvedthrough the use of two-level suction units and guide plates of various lengths installed on the nozzles of the suction devices. A program has been developed for the numerical calculation of the carbon monoxide concentration field for evaluating the efficiency of using two-level exhaust systems with different lengths of guide plates on the gas flow selection pipes. The solution of the equations of hydrodynamics and mass transfer is carried out on the basis of finite-difference methods. A number of physical and computational experiments have been carried out; it has been established that the concentration of carbon monoxide in the zone of two-level suctions location decreases by 46-68%.
... Following the methodology of Lindberg and Grimmond (2011b), the total and partial SVFs were also calculated for the same sites in the 2.5-dimensional version of the model based on high-resolution (1 m) DSMs derived from airborne LIDAR data set sampled in 2010 with a density of 13.6 points m − 2 (Klingberg et al., 2016). Since the photographs were taken five years after the LIDAR data were collected, it was important to ensure that no changes in building or vegetation structure (a newly constructed building or a harvested tree) took place at sampling sites during this period. ...
Article
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Digital hemispherical photography (DHP) is widely used to measure the radiative environment and estimate sky view factors (SVF) in urban areas and leaf area index (LAI) in forests. However, a limitation is the difficulty to distinguish trees from buildings, or leaves from stems and branches. In this study, we collected and processed dual-wavelength photographs recording visible and near-infrared (NIR) light in order to classify pixels into sky, green and woody plant elements, and buildings. Three applications of the method are presented: calculation of partial SVFs accounting for the obstruction of sky by buildings and vegetation separately, the modelling of mean radiant temperature (Tmrt), and the correction of LAI estimates for light intercepted by woody elements and buildings. The obtained partial SVFs were in good agreement with values modelled based on digital surface models. Distinguishing between buildings and vegetation in the modelling of long-wave radiation fluxes in the SOLWEIG model resulted in differences in modelled Tmrt by up to 3 °C. The bias of LAI estimates in urban parks caused by the light interception by woody elements and buildings was found to be relatively small (3–4 %). However, the presented method shows a high potential for estimates of LAI of urban vegetation in densely built-up areas.
... When using at high spatial resolution, a DSM can approximate even vertical surfaces present in urban areas [18]. The trees often mapped using Light Detection and Ranging (LiDAR) technology also play an important role in accurate estimates of solar radiation and LST in a complex urban environment [19,20]. ...
Article
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Land surface temperature (LST) in urban areas is a dynamic phenomenon affected by various factors such as solar irradiance, cloudiness, wind or urban morphology. The problem complexity requires a comprehensive geographic information system (GIS)-based approach. Our solution is based on solar radiation tools, a high-resolution digital surface model of urban areas, spatially distributed data representing thermal properties of urban surfaces and meteorological conditions. The methodology is implemented in GRASS GIS using shell scripts. In these shell scripts, the r.sun solar radiation model was used to calculate the effective solar irradiance for selected time horizons during the day. The calculation accounts for attenuation of beam solar irradiance by clouds estimated by field measurements. The suggested algorithm accounts for heat storage in urban structures depending on their thermal properties and geometric configuration. Computed land surface temperature was validated using field measurements of LST in 10 locations within the study area. The study confirmed the applicability of our approach with an acceptable accuracy expressed by the root mean square error of 3.45 K. The proposed approach has the advantage of providing high spatial detail coupled with the flexibility of GIS to evaluate various geometrical and land surface properties for any daytime horizon.
... While the strong correlation between LAI and DBH and also between LAI and tree height was shown previously for Canadian and Bavarian boreal forests [103,104] our results did not allow us to confirm this correlation. This lack of correlation is possibly explained by the small number of trees in consideration and the urban conditions of our study site [105]. However the real-time dynamics of LAI and WAI is the advantage of our device which is important for plant physiological processes and models [106]. ...
Article
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Urban green infrastructure plays an increasingly significant role in sustainable urban development planning as it provides important regulating and cultural ecosystem services. Monitoring of such dynamic and complex systems requires technological solutions which provide easy data collection, processing, and utilization at affordable costs. To meet these challenges a pilot study was conducted using a network of wireless, low cost, and multiparameter monitoring devices, which operate using Internet of Things (IoT) technology, to provide real-time monitoring of regulatory ecosystem services in the form of meaningful indicators for both human health and environmental policies. The pilot study was set in a green area situated in the center of Moscow, which is exposed to the heat island effect as well as high levels of anthropogenic pressure. Sixteen IoT devices were installed on individual trees to monitor their ecophysiological parameters from 1 July to 31 November 2019 with a time resolution of 1.5 h. These parameters were used as input variables to quantify indicators of ecosystem services related to climate, air quality, and water regulation. Our results showed that the average tree in the study area during the investigated period reduced extreme heat by 2 °C via shading, cooled the surrounding area by transferring 2167 ± 181 KWh of incoming solar energy into latent heat, transpired 137 ± 49 mm of water, sequestered 8.61 ± 1.25 kg of atmospheric carbon, and removed 5.3 ± 0.8 kg of particulate matter (PM10). The values of the monitored processes varied spatially and temporally when considering different tree species (up to five to ten times), local environmental conditions, and seasonal weather. Thus, it is important to use real-time monitoring data to deepen understandings of the processes of urban forests. There is a new opportunity of applying IoT technology not only to measure trees functionality through fluxes of water and carbon, but also to establish a smart urban green infrastructure operational system for management.
... For illustration, crowns of the adjacent tree of identical heights and distribution of density can be wrongly identified as a single treetop. Instead, the local maxima nontreetop may be incorrectly interpreted as treetops and may impact the tree structure attributes that are vulnerable to errors [14]. This should also be noted that errors arising during single tree extraction are duplicated in subsequent stages of the study of tree attributes, thus the removal or at least reduction of such inaccuracies is of considerable significance. ...
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Knowing rainforest environments is rendered challenging by distance, vegetation intensity, and coverage; however, knowing the complexity and sustainability of these landscapes is important for ecologists and conservationists. The airborne light detection and ranging (LiDAR) system has made dramatic improvements to forest data collection and management especially on the forest inventory aspect. LiDAR can reliably calculate tree-level characteristics such as crown scale and tree height as well as derived measures such as breast height diameter (DBH). To do this, an exact tree extraction method is needed inside LiDAR data. Within LiDAR data, tree extraction often starts by locating the treetops via local maxima (LM). Wide-ranging efforts have been developed to extract individual trees from LiDAR data by starting to localize treetops through LM within LiDAR data. Throughout this research, a demonstration of a new tree extraction framework inside LiDAR Point Cloud by incorporating a new tree extraction method using the bounding-box coordinates provided by deep learning-based object detection. Tree extraction inside the LiDAR point cloud using the bounding-box coordinates was successful and feasible.
... The direct LAI method has been widely used for crops and adapted for vegetation in small-scale studies (Bréda, 2003;Pérez et al., 2017). This method is useful in agriculture and ecological studies by harvesting the plant (Klingberg et al., 2017) to get the leaf area. ...
Article
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Vertical greenery system (VGS) is a subset of urban green infrastructure that ameliorates thermal performance, potential energy savings, and urban heat island. Plants provide shadow effects through the absorption or filtration of the heat radiant, which respond to these issues. The frequent variable used to indicate the leaf mass of a plant is the leaf area index (LAI). There are two methods to measure LAI: direct and indirect methods. However, little attention was given to calculating the LAI using direct measurement in VGS. This study was undertaken to distinguish the LAI value from four plant species, i.e., Philodendron burle-marxii, Phyllanthus cochinchinensis, Nephrolepis exaltata, and Cordyline fructicosa ‘Miniature’ in the industrial city of Pasir Gudang. An image analysis tool was used to facilitate the measurement. The results showed the LAI values are highly dependent on the number of leaves. It also found plants that keep growing have the highest LAI value. Importantly, the characteristics of a plant need to be considered before planting in a shrub bed.
... The maximum LAI has been set equal to all tree types despite conifers are usually considered to have a higher LAI (more than 6) than broadleaf trees (around 3-5) (Teske and Thistle, 2004;Peters et al., 2010). However, LAI in urban areas has been determined as considerably lower than in closed woodlands (Klingberg et al., 2017) with air pollution being a possible reason (Gratani and Varone, 2007). In fact, values for deciduous trees are commonly reported to be around 3 (Gratani and Varone, 2007;Öztürk (Grote et al., 2016) as well as in the forests around Berlin (Tigges et al., 2017) are also assumed to have a leaf area around 3 (Bréda, 2003). ...
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With increasing realization that particles in the air are a major health risk in urban areas, strengthening particle deposition is discussed as a means to air-pollution mitigation. Particles are deposited physically on leaves and thus the process depends on leaf area and surface properties, which change throughout the year. Current state-of-the-art modeling accounts for these changes only by altering leaf longevity, which may be selected by vegetation type and geographic location. Particle removal also depends on weather conditions, which determine deposition and resuspension but generally do not consider properties that are specific to species or plant type. In this study, we modeled < 2.5 µm-diameter particulate-matter (PM 2.5) deposition, resuspension, and removal from urban trees along a latitudinal gradient (Berlin, Munich, Rome) while comparing coniferous with broadleaf (deciduous and evergreen) tree types. Accordingly, we re-implemented the removal functionality from the i-Tree Eco model, investigated the uncertainty connected with parameterizations, and evaluated the efficiency of pollution mitigation depending on city conditions. We found that distinguishing deposition velocities between conifers and broadleaves is important for model results, i.e., because the removal efficiency of conifers is larger. Because of the higher wind speed, modeled PM 2.5 deposition from conifers is especially large in Berlin compared to Munich and Rome. Extended periods without significant precipitation decrease the amount of PM 2.5 removal because particles that are not occasionally washed from the leaves or needles are increasingly resuspended into the air. The model predicted this effect particularly during the long summer periods in Rome with only very little precipitation and may be responsible for less-efficient net removal from urban trees under climate change. Our analysis shows that the range of uncertainty in particle removal is large and that parameters have to be adjusted at least for major tree types if not only the species level. Furthermore, evergreen trees (broadleaved as well as coniferous) are predicted to be more effective at particle removal in northern regions than in Mediterranean cities, which is unexpected given the higher number of evergreens in southern cities. We discuss to what degree the effect of current PM 2.5 abundance can be mitigated by species selection and which model improvements are needed.
... Future studies intending to use LULC data should seek more detailed LULC data, along with high spatial resolution satellite images for feature extraction (Su et al., 2019;Reid et al., 2018). Examples of systems that can provide such data include Sentinel-2 at 10 m spatial resolution (Labib and Harris, 2018), LiDAR-based systems (Klingberg et al., 2017), and high-resolution EnviroAtlas community scale land use data at a 1 m spatial resolution (Egorov et al., 2017). For cross-checking LULC, studies can also use very high-resolution Google Earth images and commercial satellite images such as Geo-Eye or Worldview (Su et al., 2019;Labib and Harris, 2018;Mukherjee et al., 2017). ...
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Background: (free download: https://bit.ly/3mIrn0d) There is an increasing volume of literature investigating the links between urban environments and human health, much of which involves spatial conceptualisations and research designs involving various aspects of geographical information science. Despite intensifying research interest, there has been little systematic investigation of pragmatic methodological concerns, such as how studies are realised in terms of the types of data that are gathered and the analytical techniques that are applied, both of which have the potential to impact results. The aim of this systematic review is, therefore, to understand how spatial scale, datasets, methods, and analytics are currently applied in studies investigating the relationship between green and blue spaces and human health in urban areas. Method: We systematically reviewed 93 articles following PRISMA protocol, extracted information regarding different spatial dimensions, and synthesised them in relation to various health indicators. Results and discussion: We found a preponderance of the use of neighbourhood-scale in these studies, and a majority of the studies utilised land-use and vegetation indices gleaned from moderate resolution satellite imagery. We also observed the frequent adoption of fixed spatial units for measuring exposure to green and blue spaces based on physical proximity, typically ranging between 30 and 5000 m. The conceptual frameworks of the studies (e.g., the focus on physical vs. mental health or the definition of exposure to green space) were found to have an influence on the strength of association between exposure and health outcomes. Additionally, the strength and significance of associations also varied by study design, something which has not been considered systematically. Conclusion: On the basis of our findings, we propose a set of recommendations for standardised protocols and methods for the evaluation of the impact of green-blue spaces on health. Our analysis suggests that future studies should consider conducting analyses at finer spatial scales and employing multiple exposure assessment methods to achieve a comprehensive and comparable evaluation of the association between greenspace and health along multiple pathways.
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Building extent and size were computed using an object-based approach based on connectivity and height rules. The classification of tree crown areas was derived from the location of last-return data, filtered to remove the incidence of last returns caused by the interaction of the lidar beam with building edges, and height rules. Validation showed that building areas derived from lidar compared well with aerial photography estimates (r 2 = 0.96, p < 0.001, n = 98). The percentage difference between estimates was equal to 16% (n = 83) when buildings were discriminated from the surrounding features. However, the percentage difference between estimates increased to 35% (n = 98) when commission errors were considered, as lidar often overestimated building areas due to closely spaced buildings (gaps less than 1–2 m) not being separated. Similarly, the height and area of lidar-extracted trees were highly correlated with field-based measurements (r 2 = 0.84 and 0.76, respectively, p < 0.001, n = 50). Once these primary attributes were derived, we demonstrate the extraction of a number of secondary attributes including building mean height, normalized building volume, building wall surface area, and interelement spacing. Of significance, this research has shown that lidar can provide spatially detailed estimates of urban structure and cover which characterize the aerodynamic and energetic properties of urban areas. 309 Résumé. Les planificateurs du milieu urbain et du paysage sont de plus en plus conscients du potentiel des données lidar (« light detection and ranging ») pour dériver de l'information sur la hauteur et la structure au-dessus des grands espaces géographiques tant du point de vue économique que de l'efficacité en terme de temps de travail. Dans les environnements urbains où la complexité structurelle est grande, par exemple, les données lidar sont perçues comme constituant un ensemble de données essentielles et innovatrices pour améliorer la caractérisation des attributs de la végétation et des bâtiments. À l'aide d'un ensemble de données de premiers et de derniers retours lidar à faible empreinte de Vancouver, Canada, nous démontrons le potentiel de ces données pour dériver une série d'attributs importants permettant de décrire les interactions de la surface urbaine et de l'atmosphère dans le contexte de la prévision météorologique, de la pollution de l'air et de la modélisation de la dispersion urbaine. Deux niveaux d'attributs ont été définis. Premièrement, on a calculé les attributs primaires tels que la forme, la dimension et la localisation des bâtiments de même que réalisé la classification des arbres. L'étendue et la dimension des bâtiments ont été calculées à l'aide d'une approche orientée objet basée sur des règles de connectivité et de hauteur. La classification de la surface des couronnes d'arbres a été dérivée à partir de la localisation des données des derniers retours, filtrées pour éliminer l'influence des derniers retours engendrés par l'interaction du faisceau lidar avec les arêtes des bâtiments, ainsi qu'à partir des règles de hauteur. La validation a montré que les superficies des bâtiments obtenues des données lidar se comparaient favorablement aux estimations dérivées des photographies aériennes (r 2 = 0,96, p < 0,001, n = 98). La différence en pourcentage entre les estimations était égale à 16 % (n = 83) lorsque les bâtiments étaient déterminés par rapport aux caractéristiques environnantes. Cependant, la différence en pourcentage entre les estimations augmentait à 35 % (n = 98) quand les erreurs de commission étaient prises en considération étant donné que le lidar surestimait souvent les superficies des bâtiments lorsque ceux-ci étaient trop rapprochés (espace de < 1–2 m) les uns des autres pour pouvoir les séparer. De la même manière, la hauteur et la surface des arbres dérivées des données lidar hautement corrélées avec les mesures de terrain (r 2 = 0,84 et 0,76 respectivement, p < 0,001, n = 50). Une fois que ces attributs primaires ont été dérivés, nous réalisons l'extraction d'un certain nombre d'attributs secondaires incluant : la hauteur moyenne, le volume normalisé et la surface murale des bâtiments et l'espacement entre les éléments. Fait significatif, cette recherche a montré que les données lidar peuvent fournir des estimations spatialement détaillées de la structure et du couvert en milieu urbain permettant ainsi de caractériser les propriétés aérodynamiques et énergétiques des zones urbaines. [Traduit par la Rédaction] Goodwin et al 309
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