Estimation of urban tree canopy cover using random point sampling and remote sensing methods

Trees play an important role in urban areas by improving air quality, mitigating urban heat islands, reducing stormwater runoff and providing biodiversity habitat. Accurate and up-to-date estimation of urban tree canopy cover (UTC) is a basic need for the management of green spaces in cities, providing a metric from which variation can be understood, change monitored and areas prioritised. Random point sampling methods, such as i-Tree canopy, provide a cheap and quick estimation of UTC for a large area. Remote sensing methods using airborne Light Detection And Ranging (LiDAR) and multi-spectral images produce accurate UTC maps, although greater processing time and technical skills are required. In this paper, random point sampling and remote sensing methods are used to estimate UTC in Williamstown, a suburb of Melbourne, Australia. High resolution multi-spectral satellite images fused with LiDAR data with pixel-level accuracy are employed to produce the UTC map. The UTC is also estimated by categorising random points (a) automatically using the LiDAR derived UTC map and (b) manually using Google Maps and i-Tree canopy software. There was a minimum 1% difference between UTC estimated from the map derived from remotely sensed data and only 1000 random points automatically categorised by that same map, indicating the level of error associated with a random sampling approach. The difference between UTC estimated by remote sensing and manually categorised random point sampling varied in range of 4.5% using a confidence level of 95%. As monitoring of urban forest canopy becomes an increasing priority, the uncertainties associated with different UTC estimates should be considered when tracking change or comparing different areas using different methods.     

The impact of pruning and mortality on urban tree canopy volume

Urban trees provide a wide range of ecosystem services for city residents, with tall, mature trees with wide crowns generally regarded as preferable. The tree biomass which is responsible for shading, pollution removal, rain runoff retention etc. gets periodically reduced by the municipal tree management practice of pruning. This is a necessary activity, which reduces the risk of infrastructure damage and falling branches, but many estimates of ecosystem service provision in cities do not consider its impact explicitly. Tree mortality is also higher in cities, preventing trees from attaining and remaining at large sizes. This study used extensive field measurements of tree structure to estimate the impact of pruning on 8 tree species in two Italian cities: Taranto and Florence. Crown widths were reduced by 1.6 m on average, however there is large variation between species variation with branches more often being removed for thinning crowns resulting in larger gap fractions, which increased by 15% on average. No significant differences were observed for crown widths or gap fraction between trees pruned 3 and 4 years previously, suggesting that tree crowns structurally recover from pruning after 3 years. A deterministic model revealed that current urban forest pruning rates (every 6 years) and mortality (1%) may create a situation in which a city dominated by the species studied benefits from 93.5% of the maximum ecosystem services possible. This work will allow more nuanced estimates of urban forest services to be calculated.     

The feasibility of remotely sensed data to estimate urban tree dimensions and biomass

Accurately measuring the biophysical dimensions of urban trees, such as crown diameter, stem diameter, height, and biomass, is essential for quantifying their collective benefits as an urban forest. However, the cost of directly measuring thousands or millions of individual trees through field surveys can be prohibitive. Supplementing field surveys with remotely sensed data can reduce costs if measurements derived from remotely sensed data are accurate. This study identifies and measures the errors incurred in estimating key tree dimensions from two types of remotely sensed data: high-resolution aerial imagery and LiDAR (Light Detection and Ranging). Using Sacramento, CA, as the study site, we obtained field-measured dimensions of 20 predominant species of street trees, including 30–60 randomly selected trees of each species. For each of the 802 trees crown diameter was estimated from the aerial photo and compared with the field-measured crown diameter. Three curve-fitting equations were tested using field measurements to derive diameter at breast height (DBH) (r² = 0.883, RMSE = 10.32 cm) from the crown diameter. The accuracy of tree height extracted from the LiDAR-based surface model was compared with the field-measured height (RMSE = 1.64 m). We found that the DBH and tree height extracted from the remotely sensed data were lower than their respective field-measured values without adjustment. The magnitude of differences in these measures tended to be larger for smaller-stature trees than for larger stature species. Using DBH and tree height calculated from remotely sensed data, aboveground biomass (r² = 0.881, RMSE = 799.2 kg) was calculated for individual tree and compared with results from field-measured DBH and height. We present guidelines for identifying potential errors in each step of data processing. These findings inform the development of procedures for monitoring tree growth with remote sensing and for calculating single tree level carbon storage using DBH from crown diameter and tree height in the urban forest.     

Urban density does not impact tree growth and canopy cover in native species in Melbourne,Australia

Trees provide multiple ecosystem services in urban centers and increases in tree canopy cover is a key strategy for many municipalities. However, urban trees also experience multiple stresses and tree growth can be impacted by urban density and impervious surfaces. We investigated the impact of differences in urban form on tree growth in the City of Merri-bek, a local government area in metropolitan Melbourne, which is the temperate climate zone. Merri-bek has a gradient in population density and urban greenness from north to south, and we hypothesized that tree growth in the southern areas would be lower because trees were more likely to have less access to water with high levels of impervious surfaces. We selected three common native evergreen species, Eucalyptus leucoxylon, Melaleuca linariifolia, and Lophostemon confertus that exhibit differences in climate vulnerability and assessed the tree canopy expansion in four urban density zones in Merri-bek between 2009 and 2020 using aerial image analysis. The differences in urban form did not significantly influence tree canopy growth and all species showed similar canopy expansion rates. However, smaller trees showed a greater relative canopy increase in the ten years, whereas larger trees had a greater absolute canopy growth. Thus, older and larger trees should be protected and maintained to achieve the canopy expansion. Our study indicated that differences in urban form are unlikely to have major impacts on the growth and canopy expansion of well adapted native tree species in open, suburban centers.     

Spatiotemporal patterns of tree canopy cover and socioeconomics in Melbourne

This paper introduces a method to study the temporal relationship between the distribution of trees in cities and the residents’ income, rate of home ownership and level of education. Through photo-interpretation methods, it documents tree cover percentages in five inner city Local Government Areas in Melbourne. A 10-year time frame (2001–2011) is examined. Prior socioeconomic indicators are juxtaposed against future tree cover levels to investigate relationships. This study demonstrates that tree cover inequity is increasing over time in Melbourne. The study indicates that prior income level is a fair precursor to future canopy cover. By comparing different tree policy approaches of the five adjacent local government areas in Melbourne, it is identified that progressive policy helps generate positive outcomes for the urban forest.     

Declining urban and community tree cover in the United States

Paired aerial photographs were interpreted to assess recent changes (c. 2009–2014) in tree, impervious and other cover types within urban/community and urban land in all 50 United States and the District of Columbia. National results indicate that tree cover in urban/community areas of the United States is on the decline at a rate of about 175,000 acres per year, which corresponds to approximately 36 million trees per year. Estimated loss of benefits from trees in urban areas is conservatively valued at $96 million per year. Overall, for both urban and the broader urban/community areas, 23 states/districts had statistically significant declines in tree cover, 25 states had non-significant decreases or no change in tree cover, and three states showed a non-significant increase in tree cover. The most intensive change occurred within urban areas, with tree cover in these areas dropping one percent over the 5-year period, compared to a 0.7 percent drop in urban/community areas. States/districts with the greatest statistically significant annual decline in percent urban tree cover were: Oklahoma (−0.92%/yr), District of Columbia (−0.44%/yr), Rhode Island (−0.40%/yr), Oregon (−0.38%/yr) and Georgia (−0.37%/yr). Coinciding with the loss of tree cover was a gain in impervious cover, with impervious cover increasing 0.6 percent in urban/community areas and 1.0 percent in urban areas over the 5-year period. Such changes in cover types affect the benefits derived from urban forests and consequently the health and well-being of urban residents.     

Survival is not enough: The effects of microclimate on the growth and health of three common urban tree species in San Francisco,California

Urban forest managers must balance social, economic, and ecological goals through tree species selection and planting location. Ornamental trees are often popular in tree planting programs for their aesthetic benefits, but studies find that they have lower survivability and growth compared to larger shade trees. To maximize ecosystem services within these aesthetic preferences, it is important to select species carefully based on their ability to grow in each particular climate. However, little locality-specific and species-specific data exist on urban trees in many regions. This study examines the growth, survival, and vigor of three common ornamental street trees in San Francisco’s three different microclimate zones after over 16 years since planting. While we found over 70% survival for all three species throughout the city, there were significant differences in health and vigor among microclimates for each species, likely due to differences in drought-tolerance. While Arbutus had the greatest proportion of healthy trees in the Fog Belt and Sun Belt zones, Prunus cerasifera had the greatest proportion in the Sun Belt, and Prunus serrulata had the greatest proportions in the Transition and the Sun Belt zones. This species-specific and climate-specific information will better equip urban foresters to target both planting and tree-care of these popular species appropriately to maximize the benefits provided by these street trees while still maintaining a diverse canopy. Finally, we argue that simple survival calculations can mask more complex differences in the health and ability of different urban tree species to provide ecosystem services.     

Perception and preference of trees: A psychological contribution to tree species selection in urban areas

Trees can enhance human mental and physical well-being in urban environments. However, the tree benefits in urban planning are insufficiently recognised, and there is little knowledge on the tree characteristics that are relevant to humans and how they are evaluated. This paper presents perceptual tree parameters and their relation to human preferences. In study 1, participants sorted 24 tree images by perceived similarity. Hierarchical cluster analysis and multidimensional scaling (MDS) revealed the distinction between conifers and deciduous trees, crown shape, the two-dimensional crown size to trunk height ratio and the crown density as important to humans. In study 2, participants rated the trees based on their preferences. Multiple linear regression analyses showed that a high two-dimensional crown size to trunk height ratio and a high crown density predicted deciduous tree preferences. These findings are discussed in light of the savannah hypothesis and the Gestalt grouping principle of closure. In the task of tree selection and placement for urban areas, the identified perceptual tree parameters may allow for achieving a coherent overall picture with a simultaneous increase of tree species richness. Thus, urban landscape planning can apply the presented findings for increasing ecosystem health and residential satisfaction.     

Private residential urban forest structure and carbon storage in a moderate-sized urban area in the Midwest,United States

In conjunction with urbanization and its importance as a major driver of land-use change, increased efforts have been placed on understanding urban forests and the provisioning of ecosystem services. However, very little research has been conducted on private property and little is known about the structure and function of privately owned urban forests. This research examines the structure of and carbon storage services provided by private residential urban forests in a moderate-sized Midwestern city. The primary research questions are as follows: What is the structure of private urban forests, and how does it vary across parcels? How much carbon is stored in tree and soil pools of private urban forests, and how does carbon vary across parcels? Ecological inventories were conducted on 100 residential parcels within 14 Neighborhood and Homeowners Associations of varying size and development age. Tree species richness, diversity, density, and diameter distribution were determined on a per parcel basis and for the entire tree population sampled. Further, tree and soil carbon storage were determined for each parcel. Results of this research demonstrated large variability in per-parcel tree metrics. Twelve of the parcels sampled had two or fewer trees, while eleven had greater than 50 trees. Further, tree carbon storage ranged from no carbon to 11.22 kg C m^?2. Alternatively, soil carbon storage was less variable and averaged 4.7 kg C m^?2, approximately 1.9 times higher than the average carbon stored in trees (2.5 kg C m^?2). Management efforts aimed at maintaining or enhancing carbon storage and other ecosystem services should focus on both soil protection and maximizing services in living biomass. Our results demonstrate that sustaining tree-produced ecosystem services requires maintenance of large old trees and species diversity, not only in terms of relative abundance, but also relative dominance, and in combination, species–specific size distributions.     

Mapping the urban forest in detail: From LiDAR point clouds to 3D tree models

Trees are an integral component of the urban environment and important for human well-being, adaption measures to climate change and sustainable urban transformation. Understanding the small-scale impacts of urban trees and strategically managing the ecosystem services they provide requires high-resolution information on urban forest structure, which is still scarce. In contrast, there is an abundance of data portraying urban areas and an associated trend towards smart cities and digital twins as analysis platforms. A GIS workflow is presented in this paper that may close this data gap by classifying the urban forest from LiDAR point clouds, detecting and reconstructing individual crowns, and enabling a tree representation within semantic 3D city models. The workflow is designed to provide robust results for point clouds with a density of at least 4 pts/m² that are widely available. Evaluation was conducted by mapping the urban forest of Dresden (Germany) using a point cloud with 4 pts/m². An object-based data fusion approach is implemented for the classification of the urban forest. A classification accuracy of 95 % for different urban settings is achieved by combining LiDAR with multispectral imagery and a 3D building model. Individual trees are detected by local maxima filtering and crowns are segmented using marker-controlled watershed segmentation. Evaluation highlights the influences of both urban and forest structure on individual tree detection. Substantial differences in detection accuracies are evident between trees along streets (72 %) and structurally more complex tree stands in green areas (31 %), as well as dependencies on tree height and crown diameter. Furthermore, an approach for parameterized reconstruction of tree crowns is presented, which enables efficient and realistic city-wide modeling. The suitability of LiDAR to measure individual tree metrics is illustrated as well as a framework for modeling individual tree crowns via geometric primitives.     

Indigenous and spontaneous vegetation: their relationship to urban development in the city of Leeds, UK

The concepts of indigenous and spontaneous vegetation are considered as subsets of the broader category, semi-natural vegetation. Indigenous vegetation is conceptualised as that which has originated in a rural landscape and developed over a time period of several centuries or more, either naturally or as a result of traditional management methods, together with the environmental conditions supporting it. In contrast, spontaneous vegetation is that which has naturally colonised derelict urban sites, mainly within the last century. An investigation, using map and aerial photographic data, examined the relative proportions of potentially indigenous and spontaneous vegetation on proposed development sites in Leeds, a large industrial city in the UK. Results suggested that spontaneous vegetation occupied approximately 13% by area of the development sites while possible indigenous vegetation occupied as little as 5%. However, further analysis suggested that approximately 25% of the proposed development sites were within 0.5 km of a designated site containing indigenous vegetation. It is argued that both types of semi-natural vegetation can make positive contributions to the urban environment but that public perception of spontaneous vegetation and, in particular, the locations where it occurs, are often negative. Further research into public perceptions of semi-natural vegetation and ways of incorporating it into urban development are required.     

The inequity of distribution of urban forest and ecosystem services in Cali,Colombia

Little is known about urban forest planning, management and its benefits in emerging countries. The uneven distribution of tree canopy cover and parks in urban area is related to environmental justice, especially with disadvantaged socio-economic and marginated communities. However, the inequity of urban forest in many cities of emerging countries where often found irregular and unregulated land use patterns and social and socio-economic inequities, is hardly highlighted. This study explores the inequity of distribution of tree canopy cover and public park in Cali, Colombia. Utilizing the traditional socio-economic indices, the stratification, linear regression analysis is conducted to describe relationship between total tree canopy cover, tree canopy cover of various land use types, number of parks and park area per capita. The result demonstrates that lower income communities have lower tree canopy cover, fewer parks and smaller park area than higher income communities. This paper discusses importance of accounting for urban forests and ecosystem service in city planning efforts and better strategies of reducing inequity in emerging countries. Addressing the inequity of urban forest could be a better strategy to create resilient, sustainable, safe and livable cities in emerging countries.