Refined Wilding and Urban Forests: Conceptual Guidance for a More Significant Urban Green Space Type

Abstract

Urban forests have a definition that has developed over time. Initially defined as urban greenery or as a measure of human impacts from urbanisation on forest systems, urban forests have varying definitions and are more often referred to for urban greenery. This urban greenery and measures of outcomes in sustainability terms are in urban landscapes and surroundings. With more specific definitions according to forest system definitions the complexity, multiple functions and advanced outcomes and functions of urban forest systems compared to other urban green space (UGS) types is more clearly understood. This article, using a literature review, discusses the definition of urban forests influencing how their impacts are measured, expected, and optimised. With clarified definitions, urban forest quality is considered in the literature review by search terms and topics of selected articles. Examples of selected indicators of the quality of urban forests and then of software and metrics used to plan and design urban greenery are presented. Refined wilding as a concept for urban functional biodiversity is then compared and used as a conceptual frame to analyse findings and prove the relevance and contribution of knowledge of the concept itself. Indicators of measures are provided, and they lead to a suggestion for clearer defining of urban forests. The findings can influence planning, design, implementation, and evaluation of urban forests as a higher-quality UGS type with multiple functions. Urban forests require improved defining of the value, quality, and coverage of their UGS type to be optimised. Refined wilding can give conceptual guidance for understanding the multiple and advanced functions that urban forest biodiversity provides for urban landscapes and populations. Urban tree canopy and urban forest systems in an urban landscape, as compared to other UGSs that connect to forested areas, either urban or peri-urban, are important differentiating definitional factors. Different metrics encourage a measure of this difference. The human realities of an urban landscape and population will determine whether and how a forest system can exist in a suburban landscape and are influential as to whether an urban tree canopy compared to a multifunctional diverse stratified semi-natural system of wild native and non-native varieties is established and can be maintained. The importance of maintaining newly established and existing urban forests and trees is a significant factor.

1. Introduction

Urban forests, an urban green space (UGS) type with a significant positive impact, are assumed to be positively impactful for urban environmental and societal outcomes. They are a nature-based solution for urban development and result from renaturing strategies. Their quality and their impact as positive varies. Societal outcomes of urban forests are studied and proven, having therapeutic, sensescape (sight, sound, scents), and air purification functions, alongside combined use by design. As studies of functions of UGSs advance, even the most positively impactful by stratification and functional diversity require further interdisciplinary study and could improve with optimised knowledge organisation and response to local factors. Disciplinary studies that advance understandings of the function of urban forests include health, aerobiome, and plant, tree, shrub, and grass (PTSG) selections and balance in measures of air purification and filtration compared to the negative effects of pollen content emitted. The sensescape factors of urban forests for therapeutic benefit can also be considered as counterbalanced with other negative health effects of more diverse UGSs due to wildlife, zoonotic disease, and vector-borne disease. These factors, when adequately taken into consideration and designed for, can lead to advanced functions that refined wilding UGSs intend. It is suggested that, with promoted increases in UGSs for improved sustainable urban development, UGS quality by advanced function must be a consistent requirement alongside quantity of and access to UGSs for various sustainability benefits.

This article provides examples of urban forests, definitions, and metrics for quality and uses the refined wilding concept as a measure of function in urban biodiversity from the aboveground ecologically complex UGS type, by stratification and taxa diversity. The analysis uses the aspects of the Ecological Sensitivity within Human Realities (ESHR) and the specifics of refined wilding as the concept that substantiates functional biodiversity for the urban landscape. The outcomes of the urban forest are most focused on function and advanced function, whether advanced function is intentional, and where function could improve to advanced function. The analysis then determines the balance between positive outcomes or impacts, and any negative impacts or measured outcomes. Eventually more specific definitions of urban forests and applications of refined wilding for urban forests are suggested and presented. Refined wilding compared with more significant findings prove the relevance of metrics, different definitions, and an advancing in understanding of functional biodiversity outcomes when the concept is applied.

1.1. Refined Wilding for Functional Urban Biodiversity

The refined wilding concept [1] substantiates functional biodiversity for urban landscapes, and the ESHR [2] provides general substantiation for functional biodiversity in any landscape. This concept brings attention to varying complexities of ecological interactions and processes, and a reciprocal influence between human realities and ecological interactions and processes at a system and landscape level, and between systems. In most cases, the complexities of these interactions and processes vary according to human realities as a result of human interactions with the naturaenvironment. The exceptions to the rule which provide discussion about the indirect influence of human activity are natural occurrences and disasters and other natural-environment-influenced limitations or encouragements. The variability of control humans have over their direct interactions with the natural-environment is brought forward with a categorising of significant factors as intangible and tangible human realities and their indirect influence. The human population in urban landscapes is significantly influential and important and is a reason for requiring a refinement in what could be a realistic outcome and intention. Refined wilding works to ensure a selection of wild PTSGs which are native and non-native and assembled in a seminatural UGS for functional biodiversity.

As a concept it accepts that urban landscapes are driven and influenced by human populations, and wild UGSs face resistance and barriers caused by human realities of habit, preference, attitude regarding aesthetics, safety, and access to resources. While a wild natural environment would be most environmentally beneficial and more easily provide societal and economic benefits, other human realities present significant limitations. A refined wilding UGS and landscape are conducive to most limitations and subsequently the sustainability of urban landscapes. The ESHR encourages landscape-level functional connectivity, including functional influences between different UOS types, UGSs, urban transparent spaces, and urban grey spaces and between different UGSs. The different UGS types are a significant factor in encouraging refined wilding UGSs of higher complexities and functions as compared to specific functions. Like the ESHR, complexity is second to function, particularly advanced function. However, multifunctions provided by higher ecological complexity are more positive outcomes and more likely to be closer to a self-regulated natural system. The adaptation of indirect weakening factors to UGSs, including urban forests, is also of importance, including decreasing air pollutants and extreme weather exposures, such as sun, wind, and rain exposures, while knowing that particular PTSG selections are resilient to these factors is an additional aspect of the concept.

The functional urban biodiversity concept therefore ensures ESHR substantiates by balancing between function for human realities and ecological interactions and processes. The other UOS types are integrated multifunctions for and from refined wilding UGSs. Urban transparent spaces is a new term introduced with refined wilding and includes air and aquatic spaces which are easily impacted by and influential to functional biodiversity. Refined wilding is proven relevant and as advancing knowledge for urban green landscapes. The concept provides an interdisciplinary organising of advanced findings intended for guiding planning, designing, implementing, and evaluating any UGS and its functional connection across an urban landscape. To prove the applicability of refined wilding for urban forests, the varying definitions of urban forests and measures of quality using the concept as an analytical framing require revising and specifying. For an urban forest the PTSG selection is for a more complex and stratified UGS as traditional forest definitions would. It requires more advanced design and planning to ensure function, with variability according to adaptation or transformation from a wild or semi-wild forested or green space or the creation of an urban forest system from a grey space or other type of natural or built environment.

1.2. Urban Green Spaces for Urban Sustainability

UGSs are proven as a reliable strategy for sustainable urban development. There are several different UGS types, including green roofs, green corridors, urban agriculture, residential gardens, parks, and cemeteries, and there is a variable approach to studying, implementing, measuring, and defining them. The difference between UGS types and intended function, definitions, and uses of UGSs as identifying terms requires specification. This specificity is most required for the different functions and strengths of different UGS types.

Urban forests are occasionally referred to when urban tree coverage or canopy is meant. Urban forests can, however, be different to urban trees, urban tree coverage, and urban tree canopy. Urban trees are urban greenery or UGS, and their coverage is considered as a mitigative strategy against climate variability. Urban tree canopy measures the cover of trees across an urban landscape and is a starting measure for different urban forest types. This measure can also be referred to as urban forest.

For this article, urban forests are stratified complex UGSs that are established and designed as a forest or conserved in an urban landscape. The tree canopy or coverage across an urban landscape as an urban forest is a considered definition that does not take stratification or vegetative layers of a UGS into consideration but can provide strategies and targets for urban canopy cover [3]. Urban forests provide different and improved mitigative functions for cooling and mitigative functions for transparent space regulation for quality as compared to grassed or meadow parks [4,5,6].

1.3. History

In 1965 in Toronto, urban forest was introduced as a concept for an area affected by human populations and urban influence. More recent definitions and uses of urban forests refer to positive impacts for human populations rather than the impact of human populations on forests. Koch [7] refers to the Agricultural Revolution, urban settlements and vegetation, modern European urban design, Industrial Revolution American urban development, and then the legislation and urban development of trees. Management strategies include streets, parks, green belts, watersheds, and recreational areas [7]. The history is from 5000 years ago on the floodplains of the Tigris, Nile, Euphrates, and Indus, to AD 1100 with agricultural land around cities, the medieval age with gardens in spaces behind the home, the 14th century with urban design and formal gardens, public gardens, and street trees, with tree-lined pathways and gardens referred to as garden alleys, the 16th century in Italy with the Renaissance and public role of trees, then in France with trees used for design of urban recreational areas and landscape patterns and frames with landscape designs of planted lines of trees and wall promenades with trees planted along public walls and medieval walls.

By the 17th century most trees were for landscape and recreation and wall promenades across Western Europe, with canals also introduced as waterway promenades. The beginning of spatial planning of houses, trees, and traffic along the canal rather than allees or garden space and wall promenades was separate. Trees and vegetation are always for adornment and recreation. Playing grounds and malls are grassed and tree spaces, sometimes used for promenades or as cours for carriages, while garden alleys turned into vehicle places. Exterior avenues, baroque boulevards, and interior avenues, which are commonly integrated into urban design with trees and plants along streets, provide shade and ornaments. The Industrial Revolution led to the naturalenvironment in urban landscapes being romanticised and for the upper classes. For American urban development, urbanisation was a settling amongst dense forest in most cases and therefore deforestation, and then the inclusion of street trees and urban greenery for settled and designed urban landscapes occurred. Their Industrial Revolution resulted in a similar idea of the naturalenvironment being a romanticised idea. The impacts of highways and vehicles, traffic, and even suburbanisation, which decreased urban greenery and led to improved greenery in suburbs, developed a focus on human impacts. Koch [7] implies a need for public money and investment for urban forests as urban greenery akin to European urban design. Eventually, tree sciences and legislation are needed, as care of trees becomes a focal point. These historic developments led to an American and Canadian concept of urban forestry, which is the 1965 Toronto introduction of the concept.

The concept of “urban forest”, first introduced in the United States in 1894, was revived in the 1960s as a comprehensive and interdisciplinary approach to address the challenges and growth difficulties associated with trees in urban areas and their surrounding environments. The definition of the urban forest concept varies, reflecting the forestry traditions and forest resources of each country, and while there are similarities, significant differences also exist. Ender Altay et al. [8] provide an overview of modern urban forestry definitions from different countries that are different to the definition in Turkey which introduced a definition in the 1980s with urban forest projects rapidly implemented from 2003. These definitions of urban forests provide a history of how they became a significant concept for sustainable urban development. How their definitions developed are country and regionally specific. In Germany, urban forests are defined as areas that are managed and designed to meet the recreational needs of urban inhabitants; in the United States, urban forests are seen as a combination of vegetation and green spaces that enhance the community’s quality of life; in Iceland, urban forests are defined as areas that provide firewood, offer natural beauty, and create positive values by serving the community through recreational and other societal services; in Finland, urban forests refer to forested areas within or around urban areas, with their primary purpose and function being recreation. The concept of urban forestry entered the literature in various countries after the 1960s, but in Turkey, it was not introduced until the 1980s. They are defined as green spaces that involve planning, designing, establishing, protecting, and managing areas containing trees, tree clusters, and forest-like landscapes, whether natural or artificially created, within or around urban areas. The first examples of urban forestry in Turkey can be traced back to the establishment of forested areas (korular) in Istanbul between 1450 and 1530 when exotic species such as Cupressus sempervirens and Pinus pinea, as well as local species like Aesculus hippocastanum, Salix vitellina, and Juniperus communis, were planted throughout various parts of Istanbul. Beginning in 2003, urban forest projects were initiated across many cities and districts in Turkey. By 2016, the number of established urban forests in the country reached 145, although this number has recently decreased to 134. With several different definitions, the aspects of trees and greenery across an urban landscape, and forests in surrounding urban areas are accepted. The objective of cultivation and management of trees for the well-being of urban society as a specialised branch of forestry and then the sustained management for ongoing well-being, requiring maintenance, care, planning and protection, are two overview definitions by Jorge Sen and Deneke which have been maintained from 1974 to 1993.

1.4. Urban Forests

Urban forests can be defined as networks or systems comprising all woodlands, groups of trees, and individual trees located in urban and peri-urban areas; they include, therefore, forests, street trees, trees in parks and gardens, and trees in derelict corners. Urban forests are the backbone of the green infrastructure, bridging rural and urban areas and ameliorating a city’s environmental footprint. More recent initiatives are for tree cities [9,10] planning for peri-urban and urban forests, and for global forest action [11,12]. They are a type of UGS, with various definitions, including urban greenery, urban tree canopy and individual urban trees, and surrounding forest and trees. They are considered complex, multifunctional, and to mitigate urban disasters, pollution, and health degradation and most conducive to taxa diversity and functional biodiversity. Planning and design for urban forests for long-term outcomes is therefore a significant consideration. The UGSs that are most like forest parks are not always the most preferred common, or functional for purpose of all UGSs but where suitable provide these protective and functional roles and factors being the most complex in ecological interactions and processes by stratification and depending on the forest type and diverse PTSG selections. The specifying of urban forests as urban trees of one tree variety or species, compared to a diverse range of tree varieties, and as compared to diverse stratified forest by the inclusion of PTSGs is a difference between urban trees as compared to tree stands and urban forests. UGS design is a significant aspect and opportunity for improvement in functional PTSG diversities that provide long-term outcomes.

Urban forests can be found in their own right, within or surrounding cities, and as part of residential areas, community gardens, and urban agriculture and as part of green corridors for urban landscape connectivity. In most cases they exist in their own right and in some cases as part of residential gardens. Urban green corridors are in most cases made up of ground-level PTSGs and of trees and could have stratification and ecological complexity. In most cases, the different UGS types that might have urban forests are most often of simplified trees, plants, and grass. While occasionally referred to as urban trees, urban forest by vegetative stratification and PTSG diversities are different. Urban forests are of different types, complexities, and definitions with urban trees often significant in defining them [13]. Tree cover in an urban landscape can be a determining and defining factor, with shade provision as tree cover and space between trees as density being measures, and then species and variety composition. The i-Tree tool [14] is an example of a tool for measuring or evaluating individual tree cover in urban landscapes and for implementation through design. This tool is very different to guidance for establishing and planning urban forests and provides examples of intended functions of urban forests compared to urban trees.

Urban trees are referred to as a nature-based public health intervention [15,16,17,18,19,20,21,22,23], with reducing harm, restoring abilities, and guiding capacity measures for human health benefits. They are also understood as a renaturing effort, with mitigative impacts occasionally assumed. They are seen as part of urban forests but are in urban landscapes as individual and designed or unorganised monoculture or diverse assemblages integrated into different built environments, including alongside roads, on footpaths, in residential gardens, and in parks. There is less consistent environmental benefit of urban trees and some negative impacts, depending on species, variety, and location. In public spaces, tree species selections can be more logical and influenced by environmental and human-level functions, as compared to residential and private selections which might be more influenced by aesthetics and personal preferences.

1.5. Refined Wilding

Biodiversity for refined wilding is functional for urban systems and landscapes, no matter the complexity of the natural-environment system. Function is defined in terms of ecological and human realities functions, and there is a reciprocal influence between these functions. More specifically, it is close to wild natural-environment systems which require less maintenance and have self-sufficiency from functional ecological interactions and processes. These functions are the result of wild PTSG selections which are encouraged and can be native and non-native. Functional biodiversity from refined wilding is therefore a function for human realities and for system and landscape levels by ecological interactions and processes. The functions for human realities of urban landscapes with significant human populations are various and influential to and influenced by societal and economic factors, as environmental factors influence human health. The ecological complexity of different refined wilding UGSs varies, depending on design and UGS type, and functional biodiversity is of varying ecological complexities. Urban forests are often complex, with other types of UGS integrating complexity. Refined wilding urban forests as compared to urban forests are determined by wild PTSG selections (native and non-native) and design and planning that are intended for advanced function for human health as well as other human realities and for ecological function that reaches a functional landscape connectivity level. For refined wilding and functional biodiversity, functional landscape connectivity reaches different UGS types and different urban open spaces (UOSs), transparent spaces, and grey spaces, with positive reciprocal influential flows between each space type, in each space type, and across a landscape. That is a positive influential flow to aquatic and air UOSs and to other UGS types. These positive flows to aquatic and air UOSs and to other UGSs have direct measures associated with human health and the natural-environment, which connect to economic factors and other societal factors. They also address mitigative functions and preventative and urgent responses that UGSs are established to achieve in an effort to address urgent sustainability challenges resulting from urban development. The consideration of grey spaces encourages a use and conversion of abandoned UOSs and of transparent spaces which address some recent urban development trends, including air quality and balance between positive and negative influences of UGSs.

Refined wilding is therefore a concept introduced to substantiate functional urban biodiversity as a theory. It is introduced as a guiding concept that can ensure an advanced interdisciplinary knowledge set is developed and referred to for UGS development. For this article, urban forest establishment, conservation, and maintenance and how refined wilding can provide consistent or improved outcomes as required are considered. How refined wilding could improve urban forests is listed here, as established and proven benefits of urban forests [1] and established and proven negative impacts of urban forests [1], then an initial suggestion for refined wilding analysis of urban forests, as indicators for measures, is made. These indicators are then used to compare with findings from a literature review. An example of novelty from refined wilding [1] is measuring and metrics, where four dimensional (4D) landscape connectivity is recommended which is different to Light Detection and Ranging (LiDAR), three dimensional (3D) connectivity, and other important measures.

Hemispheric imagery and analysis of solar radiation are examples of existing metrics that include the 4th dimension of analysis as elemental. Only one natural element is measured [24]. 4D connectivity for refined wilding measures any natural element that is impacted by or impacting on an urban forest, water, air, or solar radiation. Refined wilding also encourages dimensional measures past the canopy, as biotope metrics do, which leads to definitional discussions and how the canopy in a definition of an urban forest can encourage the overlooking of important elemental measures and layers on even an urban tree. Examples include air between cement and urban trees and shade.

1.6. Initial Comparison Between Urban Forest Quality and Refined Wilding

1.6.1. Established and Proven Benefits of Urban Forests

• Transparent spaces

Variable socialising benefits of urban forest and UGS despite recreational use.

Air quality regulation.

Water regulation where well designed by flow, movement, and pollution control.

Shade and temperature regulation.

Stormwater management and water purification and regulation.

Sound regulation.

• Health

Therapeutic benefits by sensescapes (hearing, sight, scents) and then by air quality regulation.

• Greenspace

Ecological complexities by taxa and PTSG diversities and vegetation and stratification. Then, wildlife friendly and conservation.

PTSG conservation.

Closer to natural-environment systems with self-regulation by ecological interactions and processes, particularly for stratified vegetation PTSG varieties and complexities. Mitigative benefits against climate variability, include Carbon Dioxide (CO2) emissions, air pollution, natural disasters, and urban heat.

Regulating soil ecosystem process and function, microbial activity, plant–microbe interactions, and organic carbon sequestration.

1.6.2. Established and Proven Negative Impacts of Urban Forests

Microclimates and habitats conducive to zoonotic and vector-borne disease.

Allergenic pollen-bearing PTSGs, particularly wind pollinated with negative human health impacts.

Particulate matter from different tree species, such as catkins and hairs.

Ground-level ozone (O3) formulation from trees emitting biogenic volatile organic compound (BVOCs) with exposure to light, affecting air quality.

1.6.3. Refined Wilding Analysis of Urban Forest Output, Outcomes, and Impacts

Optimal landscape configuration for functional biodiversity including human access, landscape connectivity, and functional influential flows between UOSs. Existing techniques for measuring urban forest quality, or techniques that can be used to measure urban forest quality are landscape measures with their own indicators. These indicators and comparisons with refined wilding are in Section 3.4.2 and are influenced by definitions of urban forests.

Refined wilding by conceptually substantiating functional biodiversity provides guiding indicators as a comprehensive concept for outcomes. Initial indicators for refined wilding are provided here. The results of the article further the initial example of indicators for urban forest quality, as the literature review furthers the understanding of urban forest quality in the literature and how refined wilding complements, can improve, and can be improved by urban forest definitions, practices, and knowledge sets from the published literature.

• Techniques for measures

Landscape measures.

Landscape monitoring network.

Biotope measures.

i-Tree for air pollution.

S-API.

• Indicators for refined wilding

Human impacts on forests, urban and peri urban.

Balance between negative and positive health impacts.

Air quality monitoring and pollen and air pollution measures:

Ecological studies of taxa diversities, wildlife distributions, and PTSG species and varieties, stratifications, and ecological functions at UGS, urban forest, and landscape connectivity levels.

Ecological and urban forest design recommendations.

PTSG selections for functional ecological interactions and processes and for human realities:

Long-term maintenance of and for selected wild PTSGs, particularly for trees.

Functional stability between UGS and transparent and grey spaces.

Strategically exclude allergenic PTSGs.

Strategically position urban forests and PTSG selections in the context of human activity by allergenic and non-allergenic PTSGs for lowered risk of exposure.

Optimise air pollution regulation and air purification function of urban forests.

Lower risk to urban forests of exposure to air pollution and human activity.

2. Literature Review

A more specific definition of urban forests and overview of different definitions lead to a quality definition and indicators for measure. The history and varying definitions of urban forests are overviewed in the Introduction, and from there the literature review uses search engines, Google Scholar and ProQuest, to review how the published literature organises and makes information about urban forests and urban forest quality available. Search terms are “urban forest”, “urban forests”, and “urban forest quality”. The literature review progresses as findings lead to further questions. There are no time limitations or parameters for the literature searches. The introductory information about definitions is purposely historic but recently published. Exclusion criteria include no relevance, with urban forests being UGS instead of standard definitions, or urban tree canopy, or urban forest parks, or stratified UGS with trees. Inclusion criteria include urban forest parks which are in surrounding areas. Quality measures for extracted data are including according to conceptual guidance and relevance, peer-reviewed or authoritative practical documents, methods used and intended audience.

The first findings list presents search results by the number for each search term as indicative of (i) frequency of terms relevant to urban forest quality, and (ii) how specifically urban forest quality is studied as compared to studies about urban forests with variable study focus. The findings in graphs and tables are analysed. They indicate how the quality of urban forests compared to urban forest as a search term is focal for different studies about urban forests. The finding leads to questions of how focused future articles should be in regard to quality, rather than just urban forest, with acceptance of urban forest articles as general studies leading to metrics. It is suggested that a focus on urban forest quality could better direct outcomes from and for urban forests. The second finding from the literature review discusses definitional variance of urban forests from the articles reviewed. These definitional variances come from the search results and the different numbers of results for each term. The third finding of the literature review is the presentation of a list of indicators of studies and definitions of urban forests. They are from a list of search term results from two search engines.

The considered results are not randomly sampled and instead are from the first page of search results. The first page of search results is an example of relevant articles, not representative of all search results, beyond how the search engines determine significance and relevance of the order of search results. These search results are not obviously year orientated and are geographically diverse. The difference in search results for urban forests and compared to urban forest quality is indicative of how specifically urban forest quality is studied and defined, rather than implicit and varying definitions, and then measures. This includes how urban forest measures are motivated by mitigating impacts on humans, as compared to forestry measures, that measure impacts of humans and focus on forest quality with further measures of benefits to humans integrated for more comprehensive and therefore more advanced outcomes. The aspects of an urban forest listed in the third method for use of the literature review are examples according to specific topics of each article. The importance given to each aspect of an urban forest listed in the articles reviewed is an indicator of quality.

The second and third methods of the literature review consider specific aspects of an urban forest for quality measures and definitions of urban forests, alongside the number of articles and differences between articles that focus on urban forest, urban forests, and urban forest quality as search terms. The fourth finding from the literature review is from reading the search results for urban forest quality, urban forest, and urban forests. It presents indicators of measures that are relevant to urban forest quality. The selected metrics are advanced examples from the reviewed literature and are considered next to refined wilding. The findings from the third and fourth methods for use in the literature review are comparative as qualitative or new measures, established measures by foresters, and newer measures for benefits and impacts on and of urban populations. The extraction method is different, with the first page of search results compared to identified relevant metrics from the literature review. The metrics eventually presented are extremely significant for the urban forest quality focus of the article and are selected by conceptual guidance and relevance. They provide a good basis for comparison with refined wilding to prove advances for and from the concept, and how existing measures intended for an outcome are aligned with functional biodiversity. They also prove an advance of understanding from initial urban forest quality and refined wilding indicators, given from this literature review and analysis. They are not exhaustive nor representative of all metrics for urban forests.

Research Question and Hypothesis

Urban forests are more supported and implemented as a reliable sustainable urban development strategy. It is hypothesised that:

• Urban forest quality is a needed focus for urban forest studies and practice.
• Urban forest as compared to urban forest quality as a focus for study implicitly defines and measures.
• Clarification of urban forest definitions leads to:
  • Specified and therefore improved defining, planning, and implementing.
  • Improved measures of quality.
  • Improved measures of quality can improve implementation and outcomes.
• The quality of urban forests could be more of a focus.
• Refined wilding can reach and improve urban forest quality indicators and outcomes.

3. Findings

Findings present the difference in the number of articles from different search terms and search engines, the definition of urban forests in contemporary literature, and a selection of topics from selected publications from search results as from reviewing articles from search results. The topics of articles reviewed from the search term results are presented as indicative of non-specified indicators of quality and indicative of understandings of urban forest quality. The different definitions of urban forests are also discussed regarding how and whether more consistent definitions are needed for improved quality. Refined wilding, the conceptual framing for literature review, is relevant and advances these findings. The comparisons with refined wilding are where the article proves how refined wilding can complement and encourage an improved definition, discussion, planning, study, and implementation of urban forests. A furthering and advancing of existing study framing, metrics, implementation, outcomes, and evaluation are therefore presented where compared with refined wilding.

Refined wilding provides a conceptual framing for the literature reviewed and for selection criteria for metrics. The conceptual frame also provides a categorising and frame for understanding topics of articles from search results. Section 3.4.1 and Section 3.4.2 present indicators of quality, and metrics and provide elaborated comparisons with the more general substantiating ESHR concept, and with refined wilding. These elaborations present interesting recognitions of advanced existing metrics, how these metrics need to be combined, and how they could advance. The first comparisons indicate quality measures as quite comprehensive across the two aspects of the concept. They are selections from the first page of search results and literature reviewed, rather than directed searches for metrics or quality indicators. Section 3.6 presents selected metrics for urban forest quality which are guided by the conceptual frame. It is suggested that the initial basis of improved definition and study of urban forests and of urban forest quality can more easily lead to advanced functional biodiversity through an improved basis or foundation for refined wilding guidance for implementation of long-term outcomes and evaluation.

3.1. Qualifying Information

Google Scholar year-specific search results can change for first and second searches, and ProQuest searches are not responsive to search terms in inverted commas. The results as compared between the search engines are therefore different in number of searches and search results. This means that search terms and search engines determine the articles found, reviewed, and cited. In some circumstances, this could influence the understanding of urban forest definition, quality, and state of the art through advanced findings and recommendations. The search results listed as article title, and key information were the first search results displayed and are not representative of the most studied countries nor a random sample. There were three or four examples of the same articles in results across search engines. Section 3.4 shows a summary of first page of search results for each search term. For search term results in the thousands, a proportion are expected to be the same articles. This repeat result is not expected to significantly influence the search results discussion as the proportion of total results by search terms is presented. Repeat articles are expected across results for each search term.

3.2. Search Results

Table 1. Search results leading to literature review.

Google Scholar
	Search Terms
Total Results	“Urban Forest Quality”	Urban Forest Quality	“Urban Forest”	Urban Forest	Urban Forests	“Urban Forests”
	114	4,320,000	151,000	4,690,000	82,300	57,5000
Year
2025	4	16,600	1890	16,700 *	15,500	1760
2024	18	75,000	7620	97,600
2021–2023	23	69,600	163,000	66,500
2020	3	163,000	5,440	229,000
2017–2019	8	96,600	13,400	188,000
2015–2016	10	83,200	7,380	86,300
2011–2014	15	196,000	11,100	203,000
2005–2010	20	128,000	9,250	135,000
2000–2004	9	119,000	3450	232,000
2000–2009	25	885,000	10,600	170,000
2010–2019	36	194,000	19,100	485,000
2020–2025	48	143,000	17,900	101,000
ProQuest
	Search Term
Total Results	Urban Forest Quality	Urban Forest	Urban Forests
	33,870	1,528,828	1,530,404
Year
2025	10,491	16,977	16,980
2024	42,340	65,696	73,365
2021–2023	224,584	307,784	307,800
2020	56,451	78,861	78,882
2017–2019	127,266	187,810	187,225
2015–2016	69,713	105,111	105,087
2011–2014	121,087	182,156	182,415
2005–2010	115,123	192,798	192,884
2000–2004	54,785	107,701	107,708
2000–2009	145,232	262,392	262,487
2010–2019	342,741	512,554	512,562
2020–2025	333,870	469,810	471,294

* 22,000 results on second search.

,

Table 2. Number of results by search terms with colour code for Figure 1.

Google Scholar
Search Terms	Total	2000–2004	2005–2010	2011–2014	2015–2016	2017–2019	2020	2021–2023	2024	2025
“Urban forest quality”	114	9	20	14	10	8	3	45	18	4
Urban forest quality	4,260,000	118,000	155,000	182,000	71,800	122,000	156,000	114,000	81,100	16,700 *
“Urban forest”	163,000	3450	9260	11,100	7400	13,400	5460	17,200	7680	1940
Urban forest	4,750,000	172,000	127,000	137,000	101,000	153,000	246,000	94,800	107,000	16,000
Urban forests	4,600,000	85,900	19,400	46,200	21,000	25,800	155,000	18,000	85,800	15,500
“Urban forests”	57,700	1670	4420	5440	4180	8270	3460	16,700	6260	1870

* 22,000 results on second search.

and

Table 3. Number of results by search terms with colour code for Figure 2.

ProQuest
	Urban Forest Quality	Urban Forests	Urban Forest
Total	33,870	1,530,404	1,528,828
2000–2004	54,785	10,778	107,701
2005–2010	115,123	192,884	192,798
2011–2014	121,087	182,415	182,415
2015–2016	69,713	105,087	105,087
2017–2019	127,266	187,225	187,810
2020	56,451	78,882	78,861
2021–2023	224,584	307,800	307,784
2024	42,340	73,365	65,696
2025	10,491	16,980	16,977

present search term results by number and year range. Urban forest and urban forests have five times the results or hits compared to urban forest quality in ProQuest. In Google Scholar, inverted comma search terms include “urban forest” with three times the results of “urban forests”. And “urban forest quality” has 0.08% of the search results of “urban forest” and 0.2% of the search results of “urban forests”. These results are presented by search engine and graphed in Figure 1 and Figure 2.

3.3. Definitional

Urban forest for this article and review is defined as a stratified forest with vegetative layers as a standalone urban green system. It can be a UGS or part of a residential garden, green corridor, or park. Existing literature presents urban forests differently and with different definitions. Some articles assume a reader’s understanding of what an urban forest is. An urban tree canopy across an urban landscape can be a starting measure for landscape distribution and quantity, and even for quality of urban forests with a clearly defined description of an urban forest. This measure is the most common amongst the articles reviewed. Meanwhile, some articles provide further specification such as UGS that are connected to forest reserves [14] or forest parks. In some cases, urban forests are defined as forested areas in urban landscapes. In most cases, urban forests, while with varying and non-specific definitions in most articles, are not measured or defined for the human impact on them [25] as they were originally defined and instead are established and maintained for the service provided to human populations [26] by mitigative and other multifunctions provided for urban landscapes [27].

For peri-urban or urban forests, such as forest parks in close proximity to urban landscapes, forests in urban landscapes, different UGS, or urban trees, individuals or a tree canopy across an urban landscape, every definition is published and discussed as a service for human urban populations. This function for human populations is variably discussed. The variable and multiple functions as indicators of an urban forest do require further defining and comprehensive addressing. A forest ecosystem structure is more complex and multifunctional for taxa and PTSG diversities and, by stratification and vegetative structure, eventually provide more diverse and advanced functional biodiversity as compared to street-lined trees and other UGS types. The function of urban tree canopies and UGS types for landscape connectivity gives relevance to forests, forest parks, and urban forests but is different to a traditional definition of forests. All used definitions require urban landscape design which factor in interdisciplinary factors [28,29,30].

The impacts of human populations, particularly urban landscape populations, on forests in close proximity to urban landscapes is another measure and influential to the type of forest an urban forest refers to. As urban forest in most cases experience human impact and have humanrelated functions, the measures of quality can be different [31] and are almost always relevant, see Section 3.4.

The different numbers of search results for urban forest and forests by search engine, as compared to urban forest quality, in Table 2 and Table 3 and Figure 1 and Figure 2, show that general rather than directed studies about urban forests as a topic are performed. While urban forest quality still has a significant number of results, they are small in proportion compared to urban forest search results. While urban forest articles do include measures of quality, articles that intend to measure quality can more adequately address the specific metrics of quality and definitions of urban forests for measures. They also put focus on the quality of urban forests. Different urban forest types have different intended functions and benefits. They must be classified according to their benefits as quality metrics to ensure comparisons between UGS types that are referred to as urban forests are not referring to a simplified urban forest type or what a more complex traditional forest can functionally provide. Urban forest quality will, therefore, indirectly address the definition of urban forest, maybe more than the general topic of urban forest.

3.4. Urban Forest Quality Measures

While the definition or concept of urban forests varies from measuring and considering human impacts on forests, as compared to how urban forests benefit human populations, built environments, and infrastructure across an urban landscape, the measures or aspects of an urban forest that are shown from the selected articles give indications of measures of quality. The key words and search results indicate aspects of an urban forest that are (i) considered most significant, (ii) measured for quality, or (iii) ensure that urban forests are serving a long-term function. The selection of results for measures of quality, definition of urban forests, and indicators was carried out with the first pages of search results and the results are listed in

Table 4. Selected search results from Google Scholar and ProQuest with quality indicators.

Quality Measures	Number of Search Results from First Pages of Results	From 62 Articles. Some Articles Have More than One Measure of Quality or Indicator of Quality	Further Indicators	Refined Wilding	Articles
Aesthetics	Google Scholar	1		Human realities and urban landscape functions	[32,33,34,35]
	ProQuest	3
Trees	Google Scholar	12	Tree canopy, trees, and aboveground and ground biomass	PTSG selections and ecological sensitivity	[36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55]
	ProQuest	8	Diversity, ecology, canopy
Air quality	Google Scholar	5	Reducing air pollutants and human health	Human health and limiting negative impacts of air pollution on existing forests and naturalenvironment	[56,57,58,59,60,61]
	ProQuest	1
Biotope	ProQuest	1		Extent, canopy, and forest structure, ecological complexities as similar to naturalenvironment systems	[62]
Carbon storage	Google Scholar	3	1 with air quality	Mitigation, human health and ecological sensitivity, and human realities	[63,64,65,66,67,68,69,70]
	ProQuest	5
Provenances	Google Scholar	2	1 UHI mitigation	PTSG selections and ecological sensitivity. Refined wilding PTSGs as native and non-native	[71,72]
	ProQuest
Sustainability	Google Scholar	9	Equity and human welfare Human health.	ESHR and functional biodiversity and environment able to reach societal and economic outcomes	[8,26,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88]
	ProQuest	8
Taxa	Google Scholar			Ecological sensitivity
	ProQuest	1	Provenance		[89]
Between water and forests	Google Scholar			Landscape-level function across UOS types	[90]
	ProQuest	1
Post-visit behaviour	Google Scholar	1		Human realities and value of human use, recreation, health, economic outcomes	[91]
	ProQuest
History and land use change	Google Scholar	1		Quantity, land coverage, and quality changes over time	[92]
	ProQuest
Total		62

.

3.4.1. Topics from a Selection of Reviewed Articles as Quality Measures

The indicators presented in findings here are from the first page of search results, they are not randomly sampled. The explanation of the literature review furthers this explanation. Indicators are identified from the first page of each search term result for each search engine, of which there are 62 articles, and nine searches have 125 results. Sixty-two of the results are articles already listed on the first page of results. These repeat results are most frequent in ProQuest searches. The indicators are listed under quality measures and are aesthetics, soil, trees, air quality, biotope, carbon storage, provenances, sustainability, taxa, between water and forests, post-visit behaviour, and history and land use change as an indication of quantity and coverage. Some aspects are not specifically listed as quality measures, but can be understood as quality measures, including provenances, taxa, history and land use change, and aesthetics. Between water and forests and air quality and forests are not specified as urban forest quality aspects but are extremely relevant. Figure 3 graphs these main themes of articles with Table 4 presenting connected themes as additional quality inidicators.

3.4.2. Specific Indicators, Metrics, and Measures for Urban Forest Quality

Further measures for urban forest quality combine these aspects and can be found in specific software, and analytical programmes. i-Tree software, and analysis of various tools and versions, Urban Ecology Research Learning Alliance (UERLA) and Species-specific Air Purification Index (SAPI), LiDAR, and Google Earth are software and programmes that provide surveying and analysis to measure urban forests by tree canopy measures. LiDAR is higher-quality software than Google Earth, and both provide 3D imagery and depth in measures that allow their data to be used as an indication of urban forest quality. The analytics and measures found in articles were reviewed. What they measure, how refined wilding is relevant, additional measures that are encouraged by refined wilding, and recommendations are provided in Table 1. These are selections of measures and metrics from the literature reviewed and are not extensive or inclusive of all measures for urban forest quality that exist. Examples of how these measures and software are used are summarised here.

I-Tree tools include:

• MyTree
• i-Tree Design
• i-Tree Eco
• OurTrees
• iTrees Landscape
• iTree Canopy
• iTree Planting
• iTree Species

i-Tree reports include:

• Urban forest structure (e.g., species composition, tree health, leaf area, etc.).
• Amount of pollution removed hourly by the urban forest, and its associated percentage of air quality improvement throughout a year.
• Total carbon stored and net carbon annually sequestered.
• Effects of trees on building energy use and consequent effects on carbon dioxide emissions from power sources.
• Structural value of the forest, as well as the value for air pollution removal and carbon storage and sequestration.
• Potential impact of infestations by pests, such as Asian long-horned beetle, emerald ash borer, gypsy moth, and Dutch elm disease.

S-API metric

Sun et al. [93] use this metric to maximise air quality and minimise disservices of 73 urban trees used for urban greening. Their recommendations for S-API are likely to provide very relevant data for refined wilding response, tree biological traits, maintenance cost, and adaptability to urban conditions.

3.5. Four Urban Forest Types

Some specific articles found in the search results and literature review do provide further definitions of urban forests with the aim of providing specific targets for forests in urban landscapes and provide measures that indicate typical definitions of urban forests and reasons for specific measures like LiDAR 3D. For example, the variable cooling effect of different species leads to significant differences in cooling intensity. Leaves’ morphological and physiological characteristics and physical structure of the canopy, as visual measures of tree species, are valuable for urban forest quality measures. Barron et al. suggest scenario planning with four different types of urban forests, which gives defined categories as a basis for understanding urban forest types, and examples in an effort to improve urban forest coverage and quality. These definitions or categories of urban forests are for scenario planning and recognise a need for coverage and quality of UGSs and urban forests in particular, as UGS types that contribute significantly to mitigative and human health outcomes.

3.6. Findings Compared with Refined Wilding

Table 4 and

Table 5. Examples of software and analytical programmes that measure forest aspects and functions.

Software	Measures	Refined Wilding Relevance	Additional Measures Encouraged in Refined Wilding	Recommendations *
S-API metric [94]	Metric for air pollutant risk assessment and selecting appropriate species. Urban greening by tree species and species-specific air purification index. (1) Ability to remove main air pollutants (PM2.5, PM10, O3, and NO2); (2) Ecological adaptability of O3 and NO2; (3) Allergenic effects.	Monitoring and responsive planning according to advanced and relevant measures of air pollutant risk assessment, including allergenic effects, and selecting appropriate species. Requires advanced focused knowledge sets to inform planning, design, and implementation [94]. For tree species and variety selections.	PSG varieties and diversities, vegetative stratification and similar measures of influence, and taxa diversities. Refined wilding measures for negative impacts of urban forests. Microclimates and zoonotic disease. Needs further improvement and validation in the future, including the incorporation of additional criteria such as tree biological traits, maintenance cost, and adaptability to urban conditions [54,95].	All measures focus on trees and canopy, do not provide impacts over time of entire urban forests, by age of trees, by different urban forest types, or by PSG varieties and ecological function across stratification or vegetative layers and for taxa and PTSGs. Measures of maintenance requirements and how new trees and/or urban forests survive over time, including their impact on human health, other UOSs, and on the built environment as grey urban spaces. These impacts can partly rely on these analytics but require further data and study methods. Taxa diversities and population distributions require different infield measures. Optimise and utilise data provided by this software. Add data and measures from other indicators for urban forest function from the software examples provided or from infield measures. Use examples from foresters to ensure urban forests as traditionally defined, rather than as just trees, are adequately evaluated, measured, designed, and maintained. Infield measures for taxa and vegetative layer data, including ecological functions. Infield or secondary data for human measures of activity and health benefits. Three-dimensional tree canopy measures can also provide extremely relevant measures for refined wilding responses and evaluations of different urban landscapes and/or urban forests. Past assumptions associated with tree varieties and species, geographic locations, climate, and human population data.
i-Tree analysis [14]	Local hourly air pollution and meteorological data to quantify urban forest structure and its numerous effects.	Produces reports for responsive planning, design by evaluation for landscape and urban forest systems and for improving existing urban forests.	PSG varieties and diversities and vegetative stratification and similar measures of influence and taxa diversities. Refined wilding measures for negative and positive impacts of urban forests. Microclimates and zoonotic disease.
UERLA i-Tree analysis [96]	Calculation of air pollution removal by national park and first coverage measures. These parks are in close proximity to urban landscapes, and some are referred to as urban forests. Their measures are tree density, size and variety.	For responsive urban planning, design, and evaluation of urban forests, for improving urban forest structure, monitoring long-term maintenance needs, and for establishing new urban forests from measures over time. For tree variety selections and local conditions as suitability measures.	PSG varieties and diversities and vegetative stratification and similar measures of influence and taxa diversities. Refined wilding measures for negative and positive impacts of urban forests. Microclimates and zoonotic disease.
LiDAR [97,98,99]	Three-dimensional aerial imagery of tree canopy. The variable cooling effect of different species leads to significant differences in cooling intensity [100]. The leaves are categorised by morphological and physiological characteristics and physical structure of the canopy [101].	For responsive urban planning, design, and evaluation of urban forests, for improving urban forest structure, monitoring long-term maintenance needs, and for establishing new urban forests from measures over time. For tree variety selections and local conditions as suitability measures. Use of imagery of tree canopy as a measure of urban forest quality, where canopy density and tree varieties are the measure of quality.	Additional imagery of PSG varieties and diversities and vegetative stratification under tree canopy and similar measures of influence and taxa diversities. Growing stages and impacts of different urban forests. Air pollution and mitigation impacts. Influences on different UOSs and functional connectivity across urban landscape.	Use S-API and i-Tree analysis for additional measures. Use infield measures for taxa and vegetative layer data, including ecological functions. And infield or secondary data for human measures of activity and health benefits.
Google Earth	Three-dimensional aerial imagery of tree canopy.	As above with limited function as compared to LiDAR [102,103].	PSG varieties and diversities, vegetative stratification under a canopy, and similar measures of influence and taxa diversities. Refined wilding measures for negative and positive impacts of urban forests. Microclimates and zoonotic disease.	Infield measures for taxa and vegetative layer data, including ecological functions. And infield or secondary data for human measures of activity and health benefits.
Skyward (hemispheric) [104]	Imagery from ground of tree canopy and coverage which can be used to analyse canopy structure.	Tree variety, species, leaf dimensions, thinning, and tree trunk measures with additional analytical measures.		Infield measures for taxa and vegetative layer data, including ecological functions. And infield or secondary data for human measures of activity and health benefits.
Biotope Mapping [105,106,107]	Tree canopy and forest structure of vegetation in urban landscapes. Integrate biotic and abiotic information about a site, including (1) land characteristics (i.e., land cover, land use), (2) ecological site potential (i.e., degree of green spaces, the intensity of human impact, soil characteristics), and (3) biotic attributes (i.e., urban forest and vegetation structure, composition, physiognomy, etc.), among others [105]	Ecological measures.	For spatial planning and measuring urban forest quality with in-depth ecological measures.	Biotope mapping can also be used to inform urban forest and green infrastructure planning. Mapped biotopes allow the assessment of urban forest distribution, composition, and structure and its functions within specific biotopes. They also help determine priority areas for tree planting, set tree diversity targets, and support the development of comprehensive urban forest management or spatial plans at different scales [106]. The biotope data for an urban landscape can be used for refined wilding, as further data about allergenicity, function for air purification, strength against air pollution, and other human realities are factored in.

* Ground inventories and infield measures are costly, with some software measuring vegetation densities and taxa diversities.

summarise some comparisons between refined wilding and indicators found in the selected literature reviewed and four analytics and software programmes used to measure urban forest quality by tree species, air pollution control, and other measures.

Table 6. Urban forest categories as scenarios compared to refined wilding.

Urban Forest Categories	Scenario Variable *	Refined Wilding
No policy change	Physical access to nature	Looks to plan, design, and implement combinations of climate retrofit, habitat, and suburban savannah where aesthetically and functionally appropriate according to urban landscape design for public urban greenery. The scenarios and categories of urban forests could address some of the human realities presented by having dense forest and habitat in all urban forests. However, the different forest types could be further combined, with defined categories as a basis for understanding urban forest types. At minimum the negative impacts of urban forests must be mitigated. Refined wilding encourages quality by advanced function and coverage and encourages forest canopy alongside forest structure by vegetative layers and stratification and taxa diversities, while addressing human realities of health and aesthetic preferences.
Climate retrofit	Canopy cover
Habitat	Habitat
Suburban savannah	Visual access to nature Near home greenspace Urban heat mitigation Growing space Carbon sequestration Stormwater control

* Scenario variables are rated by urban forest scenario in Barron et al. [108].

summarises how refined wilding compares with a four-scenario planning approach for increasing urban forest coverage. Measures of urban forest quality can inform planning for urban forests across an urban landscape and improvements in existing urban forests.

Monitoring of surrounding forest parks and peri-urban forests can inform functional connectivity between urban landscapes and surrounding forest landscapes. Urban forests as compared to urban trees is a notable trend and a distinct measure, as are scenarios for urban forests, which indicate a need for improved understanding of options for urban forests, as compared to urban trees, to increase and improve inclusive planning. The impact of human urban populations on forests as compared to the benefit of forests and trees to humans in urban landscapes is a recommended focal point. It can assist to determine urban forest quality measures, as causal to high or low quality. Urban forests, forest parks, and urban trees are often referred to as urban forests but are quite different. As urban forests are limited in quantity across an urban landscape, the analysis of the definition leads to the term urban forest being an encouragement of urban trees. Peri-urban forests seem most likely to be of a more ecologically complex structure and function, with some forests like UGSs located in urban landscapes.

As metrics for urban forests of these different definitions advance, the example of S-API as compared to i-Tree, with measures of allergenicity by tree species, instead of air pollution and regulation service, valuable metrics, and measures of quality from i-Tree, is furthered. With 3D connectivity, biotope metrics, and 4D connectivity, the definition and use of the term urban forests and urban trees across an urban landscape can improve, as can expectations of function. From these improvements, which are trends indicating advanced understandings of function for and of urban trees and forests, planning and management of urban forests and functional urban biodiversity outcomes can be furthered. SAPI is one of the most relevant to pressing or advanced knowledge sets, with adaptability and allergenic effect and four main air pollutants measured. SAPI is a specific, relevant, and advanced index for PTSG selections and requires further indicators of measure for design, by spatial distribution and vegetative layers and other stratifications, taxa diversities, habitat provisioning, and other design for human use factors. As PTSG selections are significant for refined wilding, they are considered an advanced metric and substantiate definitions of urban forest compared to urban trees. As ecological complexity of urban forests is relevant for ESHR and refined wilding, urban forests compared to urban trees and scenarios of urban forests are supportive of refined wilding directions. Biotope metrics and 4D and 3D connectivity metrics encourage a focus on ecological complexities of urban forests and improved measure of functions. Human realities are also addressed by these improved metrics and an improved use of them. Urban forest quality could, if search results are considered a reliable measure, be more focal to urban forest studies. An improved measure of PTSG selections by function and ecological complexities could more accurately inform measures of human realities, as limitations or supported and supportive factors.

4. Discussion

The definition of urban forests is not frequently explained or defined as a forest in an urban landscape. The definition is often reliant on an idea of an urban tree canopy and tree-lined streets or traditional definitions of boulevards, cours and promenades. Whereas the definition of a forest often includes ecological complexity from soil, stratification, canopy, and under-canopy dynamics. Urban forests have significant differences not only for different ground covers, between cement and streets compared to soil, and vegetative layers of stratification. There is consistently a difference between a forest and an urban forest and a forest park, which is often a forest within close proximity to an urban landscape, referred to as peri-urban, or a forest-like system in an urban park. The differences in historic and geographic definitions are notable, with urban forests most defined for measuring human impacts on established forests, which considers the impacts of human populations and activities on forest ecosystems, normally on forest parks or peri-urban forests. This compares to urban forests that already exist in urban landscapes or are recommended for urban landscapes for the benefit of human populations.

The history of urban forests provided by Koch [7] gives a reason for the different definitions, in that UGSs and urban trees are referred to as urban forests. Then the American and Canadian history of the concept starts with the human impact on forests, particularly peri-urban forest parks. The most notable difference in definition is then the focus on trees and mitigative function, as compared to a forest structure and ecologically complex UGS, with landscape-level measures relevant to both definitions. The reference to urban tree canopy is an example, which is quite different to a forest park, with street-lined trees measured as part of a landscape canopy. More recently and with an increase in implementation and establishment, urban forests have international definitions and local or country-specific and even city-specific definitions and uses. These definitions, aspects of importance, and quality measures can be determined by national and or local policies, strategies and regulations [109] and influenced by international guidelines, policies, or goals and targets [9,10,24,110] or by indicators and measures like those listed in Table 5.

An urban forest can be differentiated from an urban park, from an urban green rooftop, from a residential garden, and from a community garden. It can be referred to as a landscape of UGS connected by trees and canopy. Or it can be a UGS with forest-like stratification, vegetation, and canopy, as European urban forestry most often refers to [7,111]. The scenarios of urban forests [1] prove the recognised need for further and more specific defining. The difference in the definition of urban forests is therefore due to historic differences in concept development influenced by geographic differences and a recent promotion of UGS. The term urban forests could be seen as an emotive or inspiring term which could encourage introduction, establishing, and maintaining of urban greenery. Meanwhile, other definitions of the concept promote measures of the human impact on forests and measures of forest parks outside of the urban landscape. This leaves urban trees within an urban forest concept, without being of a traditional forest structure. As urban greenery is more accepted, implemented, and recognised to need improvement, urban forests could be more unified and specifically defined, with urban trees and urban tree canopy developing as their own concepts. As it stands, the literature on urban forests is about any urban greenery with trees, tree stands, and a forest-like structure, with some articles not clearly defining the concept. With a focus on quality, urban forests would have to be clearly defined. The metrics and indicators of quality found in the sample of search results indicate advanced and ranging metrics of quality that do lead to specified definitions of what an urban forest is. Finding balance between how urban forests and forest parks mitigate and remove air pollution, compared to air pollutants from urban forests and forest parks, is significant for review and future studies. European histories of urban forests, as public and private urban greenery, are of trees and urban greenery in general, whereas American and Canadian histories are of forests and impacts on them from urban populations and activities.

European and American and Canadian histories have similarity in Industrial Revolution experiences where urban landscapes were not expected to or did not include greenery. In recent literature from 2000–2025, there is a significant difference in search results by italicised words as compared to non-italicised words and by quality added to the search terms. Most articles in search results refer to individual trees or tree canopy and/or tree or forest stands. The measures of quality indicate some additional consideration of aesthetics which do have therapeutic benefit implications and prove a knowledge set of foresters which might improve how urban forest stands are measured, increased in quality and number or size, and improved in location. Urban forests as tree-lined streets or individual trees provide an urban canopy that suits aspects of a forest structure but do require further defining and categorising to ensure an urban plan considers more complex and sustainable options for UGS. Search results for just “urban forest” and “urban forests” do give indications of quality measures by the importance given to particular aspects of an urban forest and to how urban forests are defined. The definition of urban forests found in the literature reviewed is scant and variable.

The most common definitional point is of trees in an urban landscape, and then of forest parks located in the surroundings of an urban area. In some cases, urban forests are any UGS. Measures of urban forest quality found in the literature review prove advanced knowledge sets and software and analytics for facilitating an advanced dataset for informing planning, design, and implementation of urban trees across a landscape and urban forests. The quality indicators found in the search results provide a comprehensive range of past measures used in terms of metrics listed, aesthetics, water and forest interactions, provenance, and land use change over time. These indicators are complementary and within the refined wilding framing. Biotope is found in these articles and is then a referred to metric, giving more information than canopy measures, including about ecological and vegetative layers. Further specific categorising of urban forests is recommended and examples [3] for scenario planning suggested for urban forests can be furthered. How refined wilding can use, improve, or benefit from these measures is summarised, alongside additional measures that these datasets could be presented with, for a more comprehensive understanding of urban forest quality and planning and design approaches. The ability to maintain new urban forests and trees over time is an essential measure, alongside the additional measures recommended. The knowledge of trees in itself is multidisciplinary, with additional measures recommended for refined wilding and functional biodiversity of urban forests, and the interdisciplinarity of urban forests for sustainable urban planning and design is emphasised and of importance. The health impacts of urban forests by pollution removal, aesthetics, carbon stored, structural value, impact on infestations as related to zoonotic disease, leaf structure and color for therapeutic benefits, and cooling effects are highlighted. Measures for new forests in terms of life cycle, maintenance, and function for other UOSs, including the built environment, are recognised as needed, as well as indicators for measures, software or programmes that facilitate them, and use of these measures and adequate response to them.

Limitations

Search terms are limited to three terms and in future research could include terms like metrics and specific terms related to urban forests. Terms like air quality, water quality, therapeutic benefit, and microclimates are examples. The selections of measures and metrics from the literature presented in Table 3 and Table 4 are not extensive or inclusive of all measures for urban forest quality that exist. They are selected as a data extraction, from the first page of results, or selected relevant metrics by conceptual guidance. Future literature reviews could overview the different software and metrics used. The search results listed are from the first page of results and emphasise any measure that the article focuses on as an indication of quality. The terms are therefore interpreted as quality measures. They do provide an interdisciplinary range of measures that goes past the quantified and software metrics and measures listed in Table 2. The scenarios of urban forest categories are also a selection from past literature review search results and are a selection by relevance to refined wilding and functional biodiversity and to the defining of urban forests. They are not therefore exhaustive or representative of all urban forest scenarios. Future research could overview all urban forest examples and suggestions for increasing their coverage, with defined categories for different definitions of urban forest types.

5. Conclusions

Urban forests by different definitions are well supported and even resourced but with assumed definitions and compositions of urban greenery and trees. Their role in sustainable urban development is still a field for improvement. The definition of urban forest is different historically and geographically and needs to be clarified. The defining of an urban forest compared to an urban tree canopy does require differentiating for adequate measures of quality, as urban tree canopy is often implicitly referred to as an urban forest. This is a more specific and different point to how UGSs of different types are implemented and managed in urban landscapes. Planning must identify the intended function of any urban forest, tree, or canopy and work from local indicators and measures from combined metrics for a comprehensive response. Urban tree canopy could be mostly tree-lined streets and individual trees rather than tree stands or forest ecosystems of complex vegetative layers and taxa diversities. A canopy is therefore indicative of a valuable but limited measure of an urban forest, as compared to an urban tree canopy, which must also factor in aspects such as air quality measures of difference between different urban forests and UGS types. The functions of urban tree canopy, mitigative, aesthetic, microclimate, and cultural, as compared to the ecological complexity and human realities value and function of a forest, are further reasons for urban forests to be referred to as different to urban tree canopy while recognising the almost emotive use of urban forest and urban tree canopy. Under-canopy dynamics are an example of more comprehensive measures. Any tree in an urban landscape can be the start of a canopy measure which ESHR, refined wilding, S-API, solar radiation analysis for hemispheric imagery, and biotope measures recognise as only one aspect or layer of a measure. These measures must also be combined with ground and tree interaction measures for urban trees, tree canopy, or forests.

The impacts of humans and urban developments on forests as compared to the benefits of different forest types on humans also require differentiating and equal consideration. These findings and conclusions support the importance of the quality of urban forests and of urban tree canopy as an indicator that defines and measures quality. The quality of urban forests and urban trees is measurable and with conceptual guidance could be further standardised. With differentiated definitions between urban forests and urban tree canopy, measures of quality can align with intention and realistic function. Refined wilding promotes a semi-natural urban system of native and non-native wild PTSGs. It is a concept conducive to more complex forest ecological structures and to mimicked forest interactions and processes by PTSGs and taxa with a refined aspect that addresses aesthetics and urban aspects and influences of a significant human population. It is also relevant to urban trees and urban tree canopy. The wild semi-natural system, a refined wilding UGS, is proven and expected to require less maintenance [27] but is also restricted by human realities of aesthetics and safety, access to resources like PTSG varieties, capabilities, and knowledge sets, as do establishing and established forests. The importance and cost of maintaining urban forests and green spaces are significant considerations [54,96] and are determined and influenced by how an urban forest is defined, planned, and implemented by design.

Design approaches and evaluation for advanced functions are also essential [109,110,111]. These aspects of long-term urban forest outcomes are relevant for refined wilding and functional biodiversity, as they are concepts that can guide management, design, and evaluation. Urban forests are forest ecosystems or established forest-mimicking UGS with complex canopy and forest structure that are ecologically functional by taxa and PTSG selections and diversities and spatial distributions. The further functions from refined wilding, referred to as advanced functions, are for human health and also for forest health and for functional connectivity across different UOS types, grey spaces, and transparent spaces which leads to a functional biodiversity of urban forests supported by surrounding urban greenery. Urban forests can be in surrounding landscapes, whereas urban trees are across and in an urban landscape. The variable definitions of urban forests of individual trees and urban tree canopy can be, in the refined wilding concept, referred to as urban landscape connectivity functions and as UGSs that are influential to urban forest functions. The complexity of urban forests as compared to urban trees or urban tree canopy is also reached by refined wilding framing, with aesthetics, simplified greening compared to stratified UGSs, zoonotic, wildlife, and pollen risks, and capability for introducing and maintaining forest like UGSs compared to urban trees as typical landscape greening strategies. According to ESHR, the complexity of ecological interactions and processes of a wild functionally biodiverse system and landscape for advanced function are limited or facilitated by human realities of the urban landscape. These human realities include capabilities, knowledge sets, aesthetic preferences, access to PTSG selections, adequate planning for long-term outcomes, and definitions most used for urban forests.

5.1. Future Directions

Future directions here provide guidance for implementation with directed ideas and summative recommendations from the findings in this article. Refined wilding and functional biodiversity are included in the recommendations.

5.1.1. Implementation

Implementations include working with relied upon international, national, and regional urban resources to mainstream definitions and discussion around the meaning of urban forest and urban forest quality, compared to the quality of an urban green landscape; educating residents about the different biodiversity values of different UGS types and/or urban forests and urban tree canopy as an influential group for UGS establishment and maintenance; engaging with the various disciplinary knowledge sets required to establish, through planning, design, implementation, and evaluation, functionally biodiverse urban forests.

5.1.2. Guidance for Implementation

More defined categories for urban forests and better definition as compared to other UGS types are needed, as well as new categories of UGSs and urban tree canopy as different to an urban forest. Functional biodiversity for urban forests and substantiating the reason for urban forests as different to urban tree canopy are needed. See examples of different urban forest types, such as an UGS connecting to other UOSs.

Defining urban tree canopy as different to an urban forest is needed. Defining and understanding urban tree canopy as an extension of functionally connected urban biodiversity as urban trees are connected across a landscape supportive and conducive for urban forests and for grey and transparent spaces are needed. A measure of trees across a landscape and normally of canopy, instead of vegetation and stratification, and taxa measures of normal forest types are needed.

Refined wilding guidance can be followed to facilitate the use of advanced knowledge sets and advanced functions of urban forests, urban trees, and other UGSs. Examples include:

Referring to foresters and urban tree studies, knowledge sets, metrics, and indicators. Focusing on the human health benefits of different urban forest types.

Ensuring PTSG selections prevent proven health impacts of allergens combined with air pollution.

Optimising urban forest complexities with functional landscape connectivity for green spaces and taxa.

Comprehensively integrate ESHR and refined wilding assessment of urban forests and UGSs often referred to as urban forest or urban trees:

Ensure ecological studies and human realities assessments with use of S-API and combined metrics.

Ensure wild PTSGs that are non-allergenic and pollinator pollinated, rather than wind pollinated, and with limited human exposure.

Ensure combined metrics like S-API and hemispheric imagery and analysis for measures of natural elements, alongside LiDAR 3D to 4D to measure urban forest quality and to plan urban forestry for a landscape.

Consider biotope measures for more complex metrics for forests, rather than of trees, and combine with the above-mentioned metrics. These metrics can start to measure ecological indicators and under-canopy dynamics.

Responsive urban forest implementation, which ensures long-term outcomes by PTSG selections, and capabilities for maintenance.

Focus on higher-quality urban forests by advanced function according to the type of urban forest:

PTSG selections, design guidance, local factors to design and plan for, focus on quality then quantity, and location planning for accessibility combined with urban forest quality, alongside sustainable established forest use.

Tree selections informed by foresters, urban landscapers, arborists, ecologists, and disciplinary experts for transparent and grey spaces for system and landscape connectivity and function across UOSs.

Improving accessibility by increased quantity in square metres compared to quality and arranged access by transport and walking. Balance out distant urban forest with pollen exposures, mitigative benefits, and social benefits.

Ensuring urban forests are measured for impacts on human health, and how they are impacted upon by urban populations and development as a quality measure.

Functional urban forests are of high quality not only according to purification function but by limiting the need for purification.

Combine landscape planning of pedestrian and urban forestry to limit combined risk factor of air pollution and pollen exposures.

Future research:

Studies that focus on urban forest quality and quality measures of urban forests.

Defining quality measures of urban forest and advanced function for each study.

Resourcing interdisciplinary, micro, and advanced findings.

S-API measures for all urban landscapes.

Studies that adequately define urban forest.

Surrounding landscape forest park.

Urban trees, tree stand, tree canopy.

Urban forest system in an urban landscape.

Studies that measure land use by the different urban forest definitions, urban trees tree stands, and tree canopy.

Studies that use combined methods and advance measures for refined wilding, such as 4D connectivity, biotope metrics, and S-API.

Studies that find balance between urban forest quantity, quality, access, and advanced function.

Studies that continue to advance aesthetic, water and forest, and biotope measures of quality of urban forests.