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STOCKHOLM SVERIGE 2020,

Street Trees Across Culture and Climate:

A Comparative Analysis of Density and Distribution

NICHOLAS SMART

KTH

SCHOOL OF ARCHITECTURE AND THE BUILT ENVIRONMENT

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Table of Contents

Introduction ... 3

Background & Literature Review ... 4

Methodology ... 6

Study Areas ... 7

Data Collection ... 8

Data Filtration ... 9

Data Analysis ... 10

Discussion of Findings ... 11

Reflections ... 16

Conclusion ... 17

Reference List... 17

Appendix 1: Journal Article ... 19

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Abstract:

The positive relationship between humans and nature is manifest in the urban greening movement, which has taken root in cities around the world. Street trees are an essential component of urban design and have emerged from a variety of historic legacies, both human and environmental. While the growing body of research on street trees has considered street tree density and distribution across cities, it has not situated these metrics in the broader discussion on the historical legacies of urban greening. This study considers five capital cities (Ottawa, Stockholm, Buenos Aires, Paris, and Washington, D.C.) spanning two climate zones and three continents to analyze the density and distribution of street trees by asking two questions: (1) what is the density and distribution of street trees across a given city and its street hierarchy? (2) how do these metrics compare within and between cities by climate zone? Preexisting datasets from local authorities are used to execute a geospatial analysis of the street tree structure of the central zone of each city. The results of this study shed light on the importance of place-specificity in informing the street tree legacy of cities and questions the existing primacy of the city-wide canopy cover metric as a global norm in planning practice.

Sammanfattning:

Det positiva förhållandet mellan människor och natur är manifest i stadsförgröningsrörelsen (urban greening movement), vilket har etablerat sig i städer runtom i världen. Gatuträd är en essentiell komponent av stadsutformning och har växt fram från en mångfald av historiska arv, båda mänskliga och miljömässiga. Medan allt mer forskning om gatuträd har betraktat gatuträdtäthet och distribution tvärs över städer, har den inte placerat dessa mätmetoder i den större diskussionen om historiska arv av stadsförgröning. Denna studie betraktar fem huvudstäder (Ottawa, Stockholm, Buenos Aires, Paris, and Washington, D.C.) över två klimatzoner och tre kontinenter för att analysera gatuträdtäthet och distribution genom att ställa två frågor: (1) vad är tätheten och distributionen av gatuträd tvärs över en stad och dess gatunätverkshierarki? (2) hur jämförs dessa mätmetoder inom och mellan städer i samma klimatzon? Befintliga data från lokala myndigheter används för att utföra en georumslig analys av gatuträdstrukturen i centralzonen av varje stad. Resultaten belyser platsspecificitetens vikt att inverka stadsgatuträdsarv och ifrågasätter den befintliga dominansen av stadsträdkronstäckning som en global norm inom planeringspraktik.

Résumé :

La relation positive entre l'homme et la nature se manifeste dans le mouvement d'écologisation baine, ce i en acine dan le ille d monde en ie . Le a b e d alignemen on ne compo an e e en ielle de la concep ion baine e le o igine in c i dan ne a i de fac e d'héritage historique, à la fois humains et environnementaux. Bien que le nombre croissant de

eche che le a b e d alignemen ai p i en comp e la den i e la pa i ion de a b e a e le ille , la di c ion ne e pa en ichie a o de l h i age hi o i e de l' cologi a ion baine.

Cette étude considère cinq capitales (Ottawa, Stockholm, Buenos Aires, Paris et Washington, DC) co an donc de one clima i e e oi con inen . Afin d anal e la den i e la pa i ion de a b e d alignemen dan ce ille , ce e de po e de e ion : (1) elle e la densité et la di ib ion de a b e d alignemen a e ne ille e a hi a chie de e ? (2) comment ces mesures se comparent-elles au sein des villes et entre elles par zones climatiques ? Des ensembles de données préexistants provenant des autorités locales sont utili afin d e c e ne anal e g o-

pa iale de la c e de a b e d alignemen de la one cen ale de cha e ille di e. Le

résultats de cette étude ont mis en lumière l'importance de la spécificité du lieu qui ainsi, renseigne sur l'héritage des arbres en milieu urbain. Ces résultats réexaminent aussi la primauté existante de

l indica e de co e e a bo e l' chelle de la ille en an e no me mondiale dan la p a i e de la planification urbaine.

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Introduction

Cities around the world are exhibiting interest in the practice of urban greening, defined as the introduction or conservation of outdoor vegetation in ci ie (Eisenman 2016). Street trees are an important part of the urban greening practices, and an important component in cities today, though this has not always been the case. In fact, the systematic introduction of street trees in North American and Western European cities did not become a common practice until the 19th century when it first emerged as a model fo he o ld (Lawrence 2006).

Nonetheless, there exist isolated examples of the planting of street trees prior to this time (Nadel et al. 1977; Lawrence 2006). This historical legacy of street trees suggests that the presence and the extent of such a presence may be contingent upon local context and culture and would therefore benefit from international comparative analysis.

To date, there exist little comparative research on the status of the structure of street trees in cities around the world, nor the contextualization of differences that may exist from a historical legacy perspective. To address such a gap, this study undertook a GIS-based

analysis of the density and distribution of street trees in five capital cities: Ottawa, Stockholm, Buenos Aires, Paris, and Washington, D.C. As per the Köppen-Geiger climate zone

classification system, the first two of these are Dfb cities that are characterized by conditions of snow, fully humid, and warm summer, while the latter three are Cfa/Cfb cities, that are described as warm temperate, fully humid, and hot/warm summer, respectively (Kottek et al.

2006). By providing a comparison of cities in the same climate zone, it is possible to control the climatic variables that would influence street tree structure, thereby allowing for the comparison of cities from a sociopolitical perspective.

The purpose of this study is to clarify similarities and differences in contemporary street tree structure between cultures due to historic legacies. The methodology developed for this study can be replicated in other cities and study results can serve as a baseline for future findings.

The study as a whole contributes to the burgeoning discourse of street trees as cultural artifacts.

Caution should nonetheless be exercised when generalizing the findings of this project beyond the scope of the study areas, namely beyond the five study cities and the two climate zones taken into account. The results of this study are contingent upon the accuracy of the data compiled by local municipalities, and the methods employed in this analysis are replicable only in cities with a similar endowment of data.

Thi ma e level kappa supplements a submitted journal article, Street Tree Density &

Distribution: An International Comparative Analysis that was produced through a collaborative research project between the KTH Royal Institute of Technology and The University of Massachusetts at Amherst that took place between August 2019 and May 2020.

The author therefore encourages readers to begin by reading the article provided in Appendix I. The remainder of this kappa includes a brief literature review on urban greening and street trees, an expanded discussion of the methods developed to conduct the spatial analysis, a short discussion of the historic legacies of the five cities as they pertain to their street trees, and some reflections by the author on the collaborative process that produced the journal article.

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Background & Literature Review

The Biophilia Hypothesis, describing the innate affiliation that humans have with nature (Kellert and Wilson 1993; Beatley 2017), lays important groundwork for the introduction of nature in urban environments. This urban greening movement is a trend that has taken hold of cities around the world (Eisenman 2016; Beatley 2017). Urban greening has emerged

alongside the concept of ecosystem services (or nature-based solutions, or green

infrastructure), which has been used as a justification of the advancement of urban greening practices (Young 2013; Seamans 2013; Escobedo et al. 2019).

The human nature-relationship is a multidisciplinary perspective that involves the related disciplines of evolutionary biology, social economics, evolutionary psychology, and

environmentalism (Seymour, 2016). The Biophilia Hypothesis is an evolutionary psychology hypothesis that concerns the emotional connection that human beings have with other living organisms (Kellert and Wilson 1993). This hypothesis was first supported by the research of Ulrich (1984), which showed that patients who had a view of nature were able to recover from surgery earlier than those who had a view of a wall. Additional studies on the effects of human exposure to nature have demonstrated that environments rich in vegetation can impart direct and observable benefits for physical health (van den Berg et al. 2007; Park et al. 2010;

Shanahan et al. 2016) and mental wellbeing (K. L. Wolfe and Flora 2010). This is significant because regular experience with nature is not the norm amongst urban populations (Cox et al.

2017), which are projected to comprise 68% of the o ld pop la ion b 2050 (United Nations 2018).

Such benefits are an example of so-called ecosystem services, which along with urban

ecosystem services, are a subject that has seen a rapid increase in discussion in peer-reviewed literature since the 1990s (Ernstson and Sörlin 2013). Ecosystem services are defined as natural goods and services with a direct or indirect ability to fulfill human needs (de Groot, Wilson, and Boumans 2002). These may fall into discrete functional categories, including the regulation of air contaminants, water flow, noise, and ambient temperature (Gómez-

Baggethun and Barton 2013). While the functional type is important, the focus of this research lies in the sociocultural dimensions of ecosystem services.

Urban stakeholders today are exhibiting widespread interest in urban greening, defined as the introduction of vegetation in outdoor urban areas (Eisenman 2016). Urban greening initiatives are often focused on the topic of trees (Bentsen et al. 2010), and particularly the establishment of the so-called urban forest (Konijnendijk 2005), which has been critiqued as a human- centric prescription of nature (Pincetl 2015). Of particular note is the urban tree canopy (UTC) assessment that was established in 2006 by the United States Department of Agriculture (USDA) as a universalized means of quantifying the extent of ground cover attributable to foliage. UTC assessments utilize land cover data from satellite imagery to inform planning initiatives (USDA 2019) and this approach has been widely used in a range of settings for research (Nowak and Greenfield 2012; Banzhaf and Kollai 2015; Krafft and Fryd 2016; Nowak and Greenfield 2020) as well as by numerous municipalities to measure urban trees and establish policy goals (City of Montréal 2012; District of Columbia 2013;

City of Melbourne 2014; City of San Diego 2015; City of Madrid 2018; City of Buenos Aires 2019) even in cities located in arid climates (City of Phoenix 2010; City of Tempe 2017).

These real-world initiatives are the result of the mainstreaming of street trees (Seamans 2013) as an established approach to greening cities and an important component of urban forests and urban environmental movements. In concert with other forms urban nature, street trees (in their ecological sense) have been framed as a tool for sustainability in urban environments in

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that they render cities more suitable for human health and mitigate climate change in the process (van den Berg, Hartig, and Staats 2007; Duinker et al. 2015; Salmond et al. 2016).

Nonetheless, the framing of street trees in this way has been critiqued as a panacea (Cohen 2004; Davies 2019), while the ecosystem services approach that has bolstered the planting of such trees has been critiqued as a value prescribing norm (Ernstson and Sörlin 2013) that lacks sufficient attention to contextual conditions and sociocultural factors (Salmond et al.

2016).

Street trees play an important role in the fabric of cities. They define the space of a street, delimit the pedestrian realm, calm traffic, filter sunlight, promote visual order, soften the streetscape, and introduce beauty in the form of nature (Massengale and Dover 2014). Street trees also offer a sense of human scale to the urban dwellers of modern cityscapes (Nadel et al. 1977). In addition to their more obvious benefits, street trees are complex artifacts of identity and politics (Dümpelmann 2019). Though street trees have been observed to comprise a larger portion of canopy cover in historic cores (Welch 1994; Maco and

McPherson 2003; Pham et al. 2013) they typically comprise a small amount of the total urban trees in the United States (Dwyer et al. 2000; Kielbaso 1990; McPherson et al. 2016). Despite their minority status in the USA, the dollar-value of municipal tree management budgets spent on street trees is approximately 2.7 times that spent on park trees (Hauer and Petersen 2016).

Trees have been planted along streets since long before the normalization of their use in cities.

For example, street trees were planted in China at least as early as the Tang Dynasty

(Lawrence 2006), while trees were valued for their role in indicating the course of roads in the Roman Empire (Nadel et al. 1977). Americans planted Lombardy poplars in streets as a symbol of independence at the end of the 18th century (Lawrence 2006). Modern urban environments and their concomitant poor air quality, imperviable surfaces, and poor soils are unnatural habitats for trees (Nadel et al. 1977). Nor were trees favorably viewed by urban residents prior to the 19th century, when the organized practice of planting street began its domination of the Euro-American urban land cape, po ing a a model fo he o ld (Lawrence 2006, 282).

Essential to street design, street trees are closely related to the streetscapes that they occupy.

An important tenet of this study is therefore that street networks, and thus urban form, inform street tree density and configuration. Urban form varies widely between cities and across cultures (Berghauser Pont et al. 2019; Huang et al. 2007), and the structure and composition of urban trees varies across geographic scale (Yang et al. 2015) and may be informed by local environmental context (Avolio et al. 2015; McPherson et al. 2016; Mcbride 2017). Despite this, precisely which human and natural legacies are the chief determinants of urban street tree structure remain unsettled. These legacies have been categorized as biophysical (including extreme weather events, fires at wildland urban interface, and pest and disease outbreaks) and human (including those of historical periods, and neighborhood and community change) (Roman et al. 2018).

The advent of publicly accessible street tree inventories has popularized the comparison of street tree inventories on neighborhood, city, region, and national scales. Cowett and Bassuk (2014) collated street tree inventories from 123 communities to compare street tree density across USDA hardiness zones in the state of New York, USA. McPherson et al. (2016) analyzed street tree inventories from 40 communities to show the macro-level decrease in street tree stocking across the state of California, USA and to quantify its economic and environmental cost. These studies are only a select few of the increasingly geographically and

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scientifically robust research that takes advantage of urban tree inventories (Nielsen et al.

2014), as is done in this study.

Street tree literature to date has also considered the metrics of density and distribution, producing a handful of relevant examples. In Bangalore, India, Nagendra and Gopal (2010) analyzed the distribution of street trees across narrow, medium-width, and wide roads, and concluded that wider streets were more street tree dense than narrower ones. In the Eastern Cape, South Africa, Kuruneri-Chitepo and Shackleton (2011) determined street tree density using 200m transects. Their study revealed distributional disparities between towns of varying economic status. In Sylhet City, Bangladesh, Deb et al. (2013) compared street tree density on main roads and link roads, finding that the former had more trees than the latter. Gwedla and Shackleton (2017) computed street tree density in multiple towns of the Eastern Cape, South Africa using 200m transects and found that towns marginalized during apartheid had lower street tree density and diversity than their non-marginalized counterparts. Most recently, Shams et al. (2020) collected street tree data in Karachi, Pakistan using 100m transects and analyzed density across three discrete road width categories and found that wide roads had the highest number of trees.

Beyond these examples, there has been relatively little comparative analysis of street tree density and spatial distribution, nor have results been situated in the broader discussion of legacy effects. As such, there has been a lack of emphasis on the sociocultural mechanisms that inform urban tree structure. This is important because geographic, temporal, and cultural context are important determinants of urban tree legacies (Lawrence 2006; Dümpelmann 2019; Keller and Konijnendijk 2012; Shackleton 2012; Mcbride 2017). This study engages with the underlying sociocultural mechanisms of street tree density and distribution across international boundaries by posing the following questions: (1) what are the density and distribution of street trees across a given city and its street hierarchy? (2) how do these metrics compare across a given city and between cities in the same climate zone? In this study, street tree density is defined as tree count per street length, designating 100 meters as the basis for international comparison. Street tree distribution builds upon street tree density and is defined as the relative street tree count per street length across hierarchical classes.

Methodology

The initial method proposed for this study consisted of superimposing a grid over each study area using ArcMap to produce 100 sets of coordinate points. These coordinate points would then be analyzed using Google Street View, wherein 50m of street in opposing directions would be virtually traveled to collect data. This original plan would have therefore

encompassed 10km of roadway for a proposed group of 15 cities around the world. The street trees on each segment were to be counted manually to produce a street tree density metric and each street segment was to be labeled as a hierarchical class. This initial approach was

abandoned in favor of a streamlined approach that involved the use of existing street tree datasets that allowed for a more efficient comparison of cities. A key contribution of this thesis was the development of a robust and replicable research methodology that was used to produce the attached research article. This methodology is described in the ensuing section.

Executing an international comparative analysis of the density and distribution of street trees across cultural and climatic boundaries under the chosen method required access to spatial data on cities located in diverse settings that represented trees and street networks. The collection and processing of such data, in turn, required interpretation of local standards in their corresponding languages (English, French, Spanish, and Swedish) and experience with

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basic geospatial data processing and analysis methods. Processing of data was performed in ArcMap while data analysis was performed in Excel and MATLAB. The interpretation of the results, in turn, was performed from a perspective based on social constructivism, which assumes a critical position on normative social structures and views institutions as products of sedimented social norms (Alvesson and Sköldberg 2009). This theoretical perspective laid the groundwork for an investigation into the sociocultural legacies that may have influenced differences in street tree density and distribution across the cities.

Street tree point data, street network polyline data, and polygon data representing jurisdictional and water boundaries were processed in ArcMap to model the spatial di ib ion of a ci hie a chical cla es and to calculate a street tree density for all

segments of he ci ee ne o k. Data were then exported to Excel and used to calculate a weighted mean street tree density based upon the length of a segment relative to that of its respective hierarchical class and to the street network of the entire city. Street segment and study area data were then exported to MATLAB to produce two types of graphs: a box plot of the statistical distribution of street segments by city, class, and climate zone and a scatter plot of street tree density against street density. The remainder of this section will outline the data flow and decision-making process used to produce the street tree profiles of each city.

Study Areas

The criteria used in selecting cities for this study was based upon the existence of

comprehensive geospatial data prior to December 2019, as well as a desire to geographically and culturally stratify the cities while maintaining relative similarity in local climatic

conditions. Therefore, cities located in similar climate zones according to the Köppen- Geiger climate classification system (Kottek et al. 2006) but on different continents were selected. Ottawa and Stockholm are located in the Dfb climate zone (snow, fully humid, warm summer), while Buenos Aires, Paris, and Washington, D.C. are located in the climate zone group Cfa/Cfb (warm temperate, fully humid, and hot/warm summer, respectively).

Finally, the five cities in this study each occupy the seat of its respective national government, which is a characteristic that has been selected to ensure that the cities exemplify their

national cultural legacies. Indeed, capital cities perform exemplary roles in their national cultural context as sites of display, places of tourist pilgrimage, and hosts to diplomatic quarters (Gordon 2006).

Because each city lies within a greater urban region and an administrative hierarchy, it is important to specify the boundaries of study used for each city. The study area of each city was limited to a zone that encompassed the most central streets, which are generally

characterized by diverse land uses, medium to high density, and high frequency of use (Hillier et al. 1993). In doing so, the study areas could be classified as central zones. Controlling the centrality of the study ensures that the study areas are relatively urban and eschew potential anomalies resulting from a rural-urban divide. The full extents of Washington, D.C. (District of Columbia), Paris (Intra Muros), and Buenos Aires (Ciudad Autónoma de) were used in this study, while the boundaries of Stockholm and Ottawa were limited to the the innerstan (inner city) and the urban wards, respectively. These study areas are displayed in Figure 1 of the attached journal article. Throughout this article, the aforementioned study areas are referred to by the names of the five cities.

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Data Collection

In the case of all cities except for Paris, all street tree inventory and street network data were obtainable from local authorities, as outlined in Table 1 of the attached journal article. A concerted attempt was made to locate official geospatial data containing a hierarchically categorized street network for the city of Paris, though the most relevant source proved to be open-source data originating from OpenStreetMap. The decision to use preexisting data on street trees and street networks means that the replication of these methods is not possible in cities without spatial street tree inventory datasets and hierarchical street categorizations.

While local standards for data in each of the cities varied, the terms used in the retrieved street tree and street network datasets were comparable enough to permit the distillation of

standards into comparable formats for cross-comparative analysis. This is to say that street networks in each city were categorized according to local standards, and a distillation process was performed to clarify relatively equivalent standards across all cities. For example, the street network in Ottawa was graded into 14 subclasses; in Stockholm, the street network was graded numerically into 10 classes; in Buenos Aires, five hierarchical network categories were used; in Washington, D.C., seven functional labels were used; and in the open-source data used in Paris, 32 roadway type labels were provided. Street tree data was obtainable with varying degrees of detail. In the case of Washington, D.C. and Ottawa, inventory datasets provided information on whether or not a given datapoint corresponded to a tree that was dead, nonexistent, or a duplicate record. In Buenos Aires, Ottawa, and Stockholm, street tree data did not contain data labels requiring attention, and the data was therefore accepted as accurate in its present form.

There were a number of differences in the definition of the urban core and street hierarchies across the cities. For example, the urban core of Stockholm, which was derived from four inner city districts, covered 36 km2. On the other hand, the urban core in Ottawa, which was derived from 12 urban wards, covered 323 km2. The urban cores in the remaining cities comprised the full extents of their respective municipalities and covered 204 km2 in Buenos Aires, 103 km2 in Paris, and 158 km2 in Washington, D.C. These spatial differences are visible in Figure A.

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Figure A. Proportionately scaled study areas

For this study, a three-class street hierarchy consisting of local, collector, and arterial streets was selected to distill the local standards provided by each city into a consistent and

comparable format. While competing structures of street network classification exist (Massengale and Dover 2014), this study assumes the commonly used local, arterial, and collector classes (USDOT 2013; Europa Commission 2020). Selective ground truthing in Google Maps was performed in each city to ensure that this system was compatible with the

e l ing di illa ion of each ci ee ne o k da a e .

Both attempts to communicate with local authorities and the revision of online documentation allowed the author to confirm the definition of a street tree in each city, as shown in Table 2 of the article. When available, these definitions are relatively consistent. Communication with local authorities in Ottawa and Stockholm on the definition of a street tree was performed with relative ease. Authorities in Washington, D.C. were less detailed in their communication, redirecting attempts to communicate to other public departments, which have not responded to date. Multiple communications to authorities in Paris received no response.

Data Filtration

Because highways and tunnels are typically not planned with street trees, all street network segments labeled as such in ArcMap were removed from the datasets before further

processing. In addition to this, the aforementioned street network categories were distilled into three to improve the compatibility of the study areas, as shown in Table A. These criteria elicited the removal of a portion of street network categories from each city and the

distillation of the remainder. Namely, 10 street categories were removed in Ottawa, while four were removed in Stockholm, two in Buenos Aires, three in Washington, D.C., and twenty-

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three in Paris. The result of the distillation process was that each street network data file contained local, collector, and arterial street hierarchy classes. In the case of Paris, open- source street network classifications included the labels primary, secondary, and tertiary. The first of these two categories were made analogous to arterial and collector streets,

respectively, whilst the latter, in tandem with all segments labeled as pedestrian and living street were interpreted as local streets. All street segments lacking a value or label for the

elec ed field e e emo ed f om hei e pec i e ci ie ee ne o k and were not included in the analysis.

Table A. Street and Tree Datasets & Fields used for Distillation

City

Street Dataset Tree Inventory Dataset

Dataset Name Field(s) Used for

Data Cleansing Dataset Name Field(s) Used for Data Cleansing

Ottawa Road Centrelines SUBCLASS Tree Inventory Flag

Stockholm Funktionell Vägklass KLASS Baskarta N/A

Buenos Aires Calles red_jerarq; tipo_c Arbolado Público Lineal N/A

Paris Carte des Départements type Les arbres domanialit

Washington, D.C. Street Centerlines FUNCTIONAL Urban Forestry Street Trees TBOX_STAT

(27) TREE SIEVE: The objective for all tree datasets was that they included exclusively actual, living street trees because some street tree inventory data contained data marked as dead or non-existent. Observation of street tree point data against their corresponding street network layers and comparison with Google Maps imagery further revealed a need to limit street tree data to those located within 30 meters of their corresponding roadway centerlines.

This value was chosen as a compromise between the inclusion of point data that was too far away from the middle of the street and the necessity to retain point data representing street trees on very wide roads.

Data Analysis

All imported and produced shapefile data were stored using featured datasets and separated into geodatabases created for each city. The geographic coordinate system (GCS) for all featured datasets was set to WGS 1984 Web Mercator Auxiliary Sphere to ensure that all exported coordinate points were compatible with Google Maps. For the purpose of calculating land areas within the bounds of study for each city, alternative, local geographic coordinate systems (GCS) were used to reduce projection distortion. The local GCS used to calculate the study area for each city is as follows:

Ottawa: NAD 1983 CSRS UTM Zone 18N Stockholm: SWEREF99_18_00

Buenos Aires: POSGAR_2007_Argentina_Zone_6 Paris: NTF_Paris_Lambert_Nord_France

Washington, D.C.: NAD 1983 UTC 18N.

ArcMap was used to assign trees to their nearest street segments. Using the Join and Relates tool, each street tree datapoint was partitioned among the segments based upon spatial

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proximity. The resulting number of trees nearest a segment was assigned to the segment as a record in a new field of each street network attribute table. In order to geographically locate each segment using coordinate points, a random point was generated within the spatial bounds of every segment. The latitude and longitude points of the random point were then assigned to their respective street segment in additional columns in each street network attribute table.

The street tree count was divided by the automatically calculated length of each street segment using the ArcMap Field Calculator tool to produce a street tree density metric, additionally displayed in each street network attribute table. This attribute table was then exported to an Excel spreadsheet file using the Table to Excel tool.

With all data available in a spreadsheet format, Excel was used to determine median and mean street tree densities. Because the unit of analysis is a segment of varying lengths as defined by local authorities, taking the arithmetic mean of ee ee den i ac o a ci street network would result in a misrepresented city-wide street tree density. Each egmen length was therefore used as a normalization factor for calculating city-wide and hierarchical class weighted mean values, which are graphed in Figure 2 of the attached journal article.

The gradation of street tree density by hierarchical class allowed for the analysis of the distribution of street trees across and within cities.

These weighted mean street tree density values were used to select typical segments. One segment was chosen on the basis of its density to represent each city-wide street tree density as well as the hierarchical class street tree densities of each city. Using the latitude and longitude of this segment, typical street view images were selected as an illustrative aid to represent street tree density as e pe ienced b he pe ipa e ic bjec (Hillier et al. 1993).

Weighted street tree mean values with typical images diversified the representation of the results of this study and allowed for qualitative interpretation as a supplement to the quantitative findings.

Because the number of street segments in each city varied, the visualization of each ci statistical distribution was analyzed using MATLAB. Data was thus compiled into a format legible for vector-based analysis and subjected to a script to produce a box and whisker plot to display the range of street tree densities using the street segment as the unit of analysis (see Figure 3 of the journal article).

These methods require the use of existing, publicly available data from local authorities which is not available for many cities. Because of this, this methodology is only applicable in cities with existing geospatial data on the local street network and street trees. Relying on such data as the input of this study additionally places the accuracy of street tree inventories in the hands of local authorities in addition to requiring that data labeled as inaccurate or extraneous be removed during the data filtration process. This study does not unpack the expansive body of research on urban deforestation and the urban heat island (UHI) effect (Brown et al. 2018), which urban trees have been shown to counteract (Loughner et al. 2012; Wang and Akbari 2016).

Discussion of Findings

The results of this study demonstrate that there are distinct differences in both the density of street trees (the number of trees per 100m of street) between and within climate zones, as shown in Figure 3 and Table 3 of the attached journal article. City-wide street tree density ranged from 1.0 to 3.5 trees/100m in the Dfb climate zone (the cooler of the two) but was much higher in the Cfa/Cfb climate zone (the warmer of the two), ranging from 4.9 to 9.9

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trees/100m. Within the Dfb climate zone, city-wide street tree density was 3.5 times larger in Ottawa as in Stockholm, while in the Cfa/Cfb climate zone, city-wide street tree density was 2.0 times larger in Buenos Aires as in Paris.

Similar differences in the distribution of street trees in cities in the same climate zone were observed, as shown in Figure 3 and Table 3 of the attached journal article. Within the Dfb climate zone, Ottawa exhibited a decreasing density along its street hierarchy (from 4.3 trees/100m in its local class to 1.1 trees/100m in its arterial class), while Stockholm exhibited an uneven distribution: its local and arterial class exhibited densities of 0.8 and 1.0

trees/100m, respectively, while its collector class had a density of 2.1 trees/100m. Within the Cfa/Cfb climate zone, street tree density in Buenos Aires decreased along its street hierarchy (from 10.6 trees/100m in its local class to 7.3 trees/100m in its arterial class). In Paris, street tree distribution was skewed toward the collector class (9.2 trees/100m) while local (3.6 trees/100m) and arterial (7.5 trees/100m) classes were less tree dense. Finally, street tree distribution in Washington, D.C. was fairly consistent across all street classes (7.5, 7.9, and 6.6 trees/100m in local, collector, and arterial, respectively)

While density and distribution were normalized to the length of individual street segments, the segment-based statistical distribution of data across and within cities provided a new perspective on street trees. Figure 4 of the attached journal article includes box and whisker plots of the segments taken directly from their respective sources. The number of segments

ed in each ci da a e in addi ion o he ppe and lo e bo nd of he in e a ile ange of data is presented in Table B.

Table B. Segment Based Statistical Distribution of Density by City

City Number of Segments Quartile 1 (trees/100m)

Quartile 3 (trees/100m)

Ottawa 29502 0.0 6.5

Stockholm 6672 0.0 0.0

Buenos Aires 29502 4.9 13.7

Paris 13100 0.0 5.9

Washington, D.C. 21799 4.1 10.6

In general, Buenos Aires had street segments with the highest street tree density of the five cities, with 50% of its segments falling between 0.05 and 0.14 trees/100m. It is closely

followed by Washington, D.C., for which the middle 50% of its street segments had street tree densities falling between 0.04 and 0.11 trees/100m. Ottawa and Paris had very similar data distribution profiles, and the lower 25% of the segments studied in each city did not have any trees. The middle 50% of the 29502 segments in Ottawa ranged from 0.0 to 0.65 trees/100m,

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and that of the 6672 segments used for Paris ranged from 0.0 to 0.06 trees/100m. Finally, the data distribution of Stockholm was overwhelmingly dominated by tree-less streets, with 76%

of sample segments containing no street trees. MATLAB boxplot formula treats any

datapoint located beyond a distance of (1.5*IQR = Interquartile Range) below the 1st quartile or above the 3rd quartile as an outlier. The formula therefore categorizes 1.0% of sample data in Ottawa, 23.6% of sample data in Stockholm, 0.11% of sample data in Buenos Aires, 6.90%

of sample data in Paris, and 0.89% of sample data in Washington, D.C. as outliers.

The statistical distribution of street tree density may be further divided by hierarchical class within each city (as shown in Figure B) and aggregated by climate zone (see Figure C). This serves to highlight those street classes composed of treeless streets. While the arterial streets of Ottawa were relatively treeless, the local streets of Paris were mostly treeless. More than half of all street classes in Stockholm were treeless, while in Washington, D.C. and Buenos Aires, the median was well above 0 trees/100m, indicating that there were fewer treeless streets by proportion. Likewise, the difference in street tree density across climate zones is readily apparent in Figure C, where the median street tree density in Cfa/Cfb cities is much greater than that of Dfb cities.

Figure B. Statistical distribution of street tree density by street segment (street class)

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Figure C. Statistical distribution of street tree density by street segment (climate zone) The outcomes of this analysis are contingent upon their local contexts and thus, it is helpful to present a baseline comparison of each of the study areas and the extent of their respective street networks. Figure D includes a scatter plot of the street tree density and street density of the five study areas. Here, street density is defined as the street length in meters per unit area study area in square meters. This scatter plot is not intended to show a correlation or the lack thereof. Rather, it provides a compact comparison of several characteristics (street

compactness, surface area, and street tree density) of each of the study areas. Ottawa, for example, is the largest study area and has the lowest street density and the lowest city-wide weighted mean. Stockholm is the smallest study area and exhibits a street density and an even lower city-wide street tree density. Buenos Aires, in turn, has a lower street density and a much higher street tree density than Stockholm, while Washington, D.C., and Paris exhibit similar tendencies. The diversity of local urban form and definitions used to describe its boundaries are evident when compiled into one graph. This adds an additional layer of richness to the analysis of these study areas.

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Figure D. Scatter plot of street tree density versus street density and relative study area size This analysis has allowed for a comparison of cities across international, continental, and climatic boundaries to show significant differences in street tree density and distribution that are likely produced by a combination of environmental and human (cultural and historical) legacies (Roman et al. 2018). Of note in informing this investigation are place specific legacie . Fo e ample, S ockholm lack of ee ee ma be a ib ed o i hi o icall centralized urban planning approach (Andersson and Bedoire 1988) or its tradition of using architecture and open squares to embellish streets instead of trees (Lawrence 2006). In contrast, the first street trees in Ottawa were planted by residents (Dean 2005) and in the USA, street tree planting is often executed by various actors not in the public sector

(Campanella 2017; Lawrence 2006; Konijnendijk 2005). Buenos Aires, inspired by Parisian planning (Gutiérrez 2002), lacks trees on the narrow streets of its historic core (Márquez and Fiorentino 2007), and Paris did too before its large-scale structural overhaul in the 19th

century (Laurian 2019). The findings of this study also contribute to the expanding critique of the ecological role of street trees (Ernstson and Sörlin 2013) in a globalizing world. That UTC is a sound metric for use in all cities has specifically been placed into question, as regional climate and cultural standards can vary considerably. Further discussion of the sociocultural implications of the study findings are provided in the attached journal article.

The findings of this study have implications for policy makers and urban stakeholders.

Specifically, the multifaceted and multidimensional role of the street tree should be considered as to not mistakenly commend street trees for feats than they are not able to accomplish in their local contexts. Ever present constraints on municipal sustainability goals are the financial barriers standing in the way of accomplishing them. Municipal investments in urban greening practices, such as the planting of street trees, should therefore be weighed against measures that are potentially more substantive as to avoid a false sense of security.

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Important to note is that the short anecdotes provided here and in the attached journal article do not do justice to the rich histories of the places in this study (Wolfe 2019), which would benefit from further investigation into the sociopolitical histories of each city in search of explanatory mechanisms. Specifically, archival research that employs qualitative historical analysis would serve to complement and enhance the findings of this study. Additionally, the methodology of this study could be repeated for the expanding list of cities that have street tree inventories and open access data. In doing so, a control of not only climate but other, potentially sociopolitical variables, would lend itself to a deeper conceptualization of the sociocultural legacies of street trees in multiple contexts.

Reflections

An idea conceived by visiting Professor Theodore Eisenman, this project originated as a collabo a ion be een ma e den and planning p ofe o o compa e he ee ee profile of fifteen cities across cultural, continental, and cultural boundaries. Eisenman has conducted research on the practice of urban greening and the scientific, historical, cultural, and design bases that it is grounded in (Eisenman 2016; Eisenman et al. 2019; Horte and Eisenman 2020) and his interest in the international dimension of greening practices inspired this collaboration. In total, this research project was carried out over the course of 10 months, from August 2019 to May 2020. The summer of 2019 consisted of a preparatory literary review, and one of the two ma e students chose to discontinue. The remaining research team therefore included Nicholas Smart, Theodore Eisenman, and Andrew Karvonen. The collaborative process officially began on August 15th, 2019, and, to accommodate for the reduction in contributors, the scope of the project was narrowed to three cities (Buenos Aires, Paris, and Washington, D.C.) in one climate zone, each supplemented with a unique historical context that would serve as the basis for exploring the sociopolitical factors that inform present street tree conditions. In doing so, the research focus aligned with the proposed book project resulting from the 2019 conference Street Trees and Politics at the University of Sheffield, and the researchers were invited to contribute a chapter.

Throughout the Autumn semester at KTH, the research team continued to grapple with the research design, shifting the scope of and methods used in the study to account for new information. During this time, I carried out an internet-based collection of spatial data on Stockholm, Ottawa, and the three aforementioned cities. The decision to include Stockholm and Ottawa in the list of cities we studied was based upon a concern that data would not be available for the other cities. In doing so, we expanded the scope of the study to include a total of five cities. Around December 2019, both the collection and processing of data was complete, and, in light of an invitation to publish a journal article in a special edition of Frontiers in Ecology and Evolution, the project was expanded to encompass two publications.

The first of these publications was the journal article, which would encompass the results of the quantitative analysis on our five cities, while the second of these publications was the book chapter, which would build upon the first with a historically oriented investigation into the sociopolitical dimensions of each of the cities. The latter of these two publications was eventually deemed unfeasible under the given timeframe and resource constraints, though the attached journal article that was submitted for review offers a brief inquiry into the place- specific legacies that may inform our findings in each city.

After early encouragement from both Theodore and Andrew, I took on the role of lead author for our study, spearheading the process of spatial data collection and processing in ArcGIS, Excel, and MATLAB. Because of this, I was most familiar with the data we were analyzing and was therefore well posed to author the first draft of our article. Subsequent drafts of the

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article were produced from weekly collaboration between all three authors, and the draft submitted to Frontiers in Ecology and Evolution is the result of the iterative writing process that took place. I led on the writing of the subsection Place-Specific Street Tree Legacies, while the other section, Street Trees in a Globalizing World, was written by Theodore Eisenman, who had more experience in the subject. Much of the background literature

pertaining to the universalization of the ecological role of street trees is attributed to Theodore as well.

Having the opportunity to collaborate with experienced researchers and incredible authors has helped me learn a great deal about the collaborative process in an advanced academic setting.

The iterative writing process that we undertook taught me a great deal about the craft of writing a structured and targeted narrative, which involves a delicate dance . Finally, I feel as if I have learned an incredible amount about street trees, which hold a position in society that is far more complex than I could have ever imagined. I look forward to having the

opportunity to make use of my acquired knowledge in the future and to the remainder of the journal review process with Theodore and Andy.

Street trees have been important contributors to urban environments. It is well known that they serve a number of functions in modern cities. Whether or not their presence is a

significant contributor in the fight against climate change remains, to date, a contested topic.

Going forward, I believe that street trees will and ought to continue to remain an important part of the built environment, so long as available resources permit their sustenance in their local contexts. An implication of this is that resources may not always be available to plant and maintain street trees, which is especially true in light of the urgent climate crisis that the world is facing today. As far as urban heat islands are concerned, municipal budgets may be better spent on producing and implementing policies that reduce greenhouse gas emissions, which have a negative and direct impact on local climate. The urban greening movement and its concomitant employment of street trees are here to stay. To what extent the embodied policies of such a movement are sustainable and therefore contribute to the fight against climate change remains to be answered.

Conclusion

Street trees are now ubiquitous elements in the fabric of cities today. While urban tree and forestry scholars have lauded them for their contributions to sustainability, street trees have historical roots in politically and socially contested territory. The street tree is part of the broader urban greening movement taking place in cities around the world, but its role has not been contextualized in the larger conversation of historical legacies factors. Bo h hi ma e thesis and the attached journal article contribute to the growing body of research that places the ecological role of the street tree into question, stressing the importance of place-specificity in a globalizing world. The work points to the need for further research to investigate the human factors that inform street tree legacies in cities and to inform future urban greening activities.

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Appendix 1: Journal Article

The article that follows on the next page has been submitted to Frontiers in Ecology and Evolution and is currently under peer review. With the exception that the figures and tables have been included in the body of the text, no changes have been made to the original.

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Street Tree Density and Distribution: An International Comparative Analysis of Five Cities

Nicholas Smart1*, Theodore Eisenman2**, Andrew Karvonen3***

1KTH Royal Institute of Technology, School of Architecture and the Built Environment, Stockholm, Sweden

2Department of Landscape Architecture and Regional Planning, University of Massachusetts- Amherst, Amherst, MA, USA

3KTH Royal Institute of Technology, Urban Planning and Environment, Stockholm, Sweden

* Correspondence:

Nicholas Smart nsmart@kth.se

** Correspondence:

Theodore Eisenman teisenman@umass.edu

*** Correspondence:

Andrew Karvonen apkar@kth.se

Keywords: street trees1, legacy effects2, urban greening3, comparative analysis4, globalization5, urban history6.

Abstract

To realize ecological, economic, and aesthetic benefits, cities around the world are

demonstrating significant interest in urban greening. The urban greening toolkit often includes street trees as a prominent type of flora. Street trees are an essential component of urban design and have emerged from historic legacies of both human and environmental factors. To date, there has been little comparative analysis of street tree density and distribution across international and intercontinental settings and these analyses have not been situated within the broader discussion on historical legacies of urban greening. This study focuses on five capital cities (Ottawa, Stockholm, Buenos Aires, Paris, and Washington, D.C.) situated in two climate zones and addresses two principle questions: (1) what is the density and distribution of street trees across a given city and its street hierarchy? (2) how do these metrics compare within and between cities by climate zone? The analysis draws upon preexisting datasets from local authorities and includes geospatial analysis of 100m segments of street trees across hierarchical street classes within the central zones of each city. The results show clear differences in street tree density in cities across and within climate zones as well as in street tree distribution in cities within the same climate zone. This illustrates the importance of place-specific cultural and environmental legacies as determinants of street tree density and distribution, and it problematizes citywide canopy cover as a global norm for planning and designing urban landscapes.

Word Count: 5906 Tables & Figures: 7

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1 Introduction

Urban greening is a common practice in contemporary cities around the world to realize ecological, economic and aesthetic benefits. Urban greening involves organized or semi- organized efforts to introduce, conserve, or maintain outdoor vegetation in urban areas (Eisenman 2016; Feng and Tan 2017). Such efforts take on a multitude of material expressions, municipal policies, and incentives (Beatley 2017; Tan and Jim 2017). This includes large-scale urban tree planting initiatives in which street trees figure prominently (Young 2011; Roman et al. 2015; Breger et al. 2019). Of note, the systematic planting of trees across the urban fabric and along streets was not common in many European and North American cities until the late 19th and early 20th centuries (Campanella 2003; Lawrence 2006; Dümpelmann 2019). Reflecting on practice, there has likewise been substantial growth in chola l e of e m deno ing ban ee plan ing ini ia i e o e he pa decade ( ee Figure 1). Scholars have described these campaigns as an urban forestry movement

(Campbell 2017) and a popular trend (Pincetl et al. 2013).

Today, street trees are a prominent type of flora in the urban greening toolkit, and they are an essential component of urban design. They define the space of a street, delimit the pedestrian realm, calm traffic, filter sunlight, promote visual order, soften the streetscape, and introduce beauty in the form of nature (Massengale and Dover 2014). They are also an important component of urban forestry practice. In the United States, expenditures on street trees account for the largest portion of municipal tree management budgets, eclipsing the amount spent on park trees by a factor of 2.7 (Hauer and Petersen 2016). Street trees are also the primary focus of many urban tree inventories (Keller and Konijnendijk 2012). Yet, while street trees in some older neighborhoods may comprise a large portion of urban canopy cover (Welch 1994; Maco and McPherson 2003; Pham et al. 2013), they generally constitute a minor portion of total urban trees in the United States (Dwyer et al. 2000; Kielbaso 1990;

McPherson et al. 2016).

Current patterns of urban tree distribution (or structure) and species composition are a legacy of both human and environmental (or biophysical) factors (Roman et al. 2018).

Environmental legacies include extreme weather events, wildland urban interface fires, and outbreaks of pest and disease. Human legacies include those of historical periods such as national and regional identity, colonial history, species symbolism, and urban park and city beautification movements as well as long-term changes in neighborhood form and

socioeconomic demographics. These legacies are set within a bioregional context native biome, climate, topography, and preexisting vegetation and land use that establishes the environmental conditions for the development of cities: socio-ecological systems that are built b and fo h man (G offman e al. 2014). A ci ban fo m ma , in n, e pond o both environmental conditions such as topography and landscape setting, as well as cultural drivers such as military defense (e.g., road widths, medieval moats and walls), political and economic control (e.g., the grid), periodic trends (e.g., baroque street diagonals, freeways to-

greenways), public policy (e.g., urban renewal), and technological and socio-demographic change (e.g., automobile infrastructure, suburban expansion) (Kostof 1991; Birch 2009; Horte and Eisenman 2020). Because of this, urban form varies widely across geography and culture (Huang et al. 2007; Berghauser Pont et al. 2019). This suggests a need to understand cities as distinct biomes that can be classified by typology to better inform urban greening aspirations (Pincetl 2015).

It is not clear, however, which human and environmental legacies are predominant for urban tree composition and distribution in a given place (Roman et al. 2018). This study does not

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address the species composition of street trees, but instead focuses on density and distribution as indicators of environmental and human legacy effects. There have been relatively few studies on street tree density and distribution to date. Kuruneri-Chitepo and Shackleton (2011) calculated street tree density in the Eastern Cape, South Africa using 200m transects to

highlight distributional disparities between different towns. They found that relatively more affluent suburbs in these towns had larger mean street tree densities. Gwedla and Shackleton (2017) also calculated street tree density in multiple towns of the Eastern Cape using 200m transects and found that both smaller towns and those that had been marginalized during apartheid had significantly lower street tree density and diversity. Nagendra and Gopal (2010) sampled 200m transects across Bangalore, India to analyze the relationship between street tree density and narrow, medium-width, and wide roads, while Shams et al. (2020) sampled 100m transects to do the same in Karachi, Pakistan. Both studies found that narrower roads had fewer street trees than their wider counterparts. Deb et al. (2013) studied street trees in Sylhet City, Bangladesh to compare density and distribution between main roads and link roads, and found that, on average, the former exhibited higher tree density than the latter. In these studies, street tree density was defined as the measure of trees per unit distance

(Nagendra and Gopal 2010; Shams et al. 2020) whereas street tree distribution was defined as the measure of such trees across space (Nagendra and Gopal 2010), and, more specifically, across street types.

The aforementioned research illustrates the influence of cultural variables such as economic factors, development history, and street type on street tree density and distribution. This literature has, in turn, assessed street tree density and distribution in individual cities, or cities within the same region of a country. In other words, research has considered street tree density and distribution as an outcome unto itself but has not distinguished between environmental and cultural legacies that may explain street tree density and distribution.

Moreover, there has been little comparative analysis of street tree density and distribution across international and intercontinental settings; nor have these metrics been included in broader discussions of legacy effects. This is noteworthy because both national and continental contexts inform urban tree discourse, practice, and preferences (Fraser and

Kenney 2000; Campanella 2003; Lawrence 2006; Konijnendijk 2008; Keller and Konjijnedijk 2012; Shackleton 2012; Dümpelmann 2019), as well as urban ecology writ large (Ernstson and Sörlin 2019).

Place-based research and comparative analysis is especially important in a globalizing world that is characterized by rapid and widespread diffusion of information, values, and norms (Castells 1996). In Grounding Urban Natures: Histories and Futures of Urban Ecologies, Ernstson and Sörlin (2019, 4) situate urban environmental discourse in a globalizing context and raise conce n abo ni e ali ing f ame o k o hink abo and ac pon all ban landscapes. Universal metrics and models, they argue, privilege certain expertise and disciplinary perspectives that risk producing an ahistorical city which ignores indigenous spatial form and socio-environmental context. This is supported by Sandberg et al. (2015, 4), who posit in Urban Forests, Trees, and Greenspace: A Political Ecology Perspective, that

ni e al echni e and di ciplina hegemon i k homogeni ing he p rpose and presence of trees in cities while erasing local values, knowledge, and management practices.

One example of a universal metric in urban forestry is urban tree cover (UTC), generally depic ed a he pe cen of a ci land co e ed b ee hen viewed from above. Created in 2006, UTC assessment methods use remote sensing (e.g. satellite imagery, aerial photographs, LIDAR) to calculate the amount of tree canopy that currently exists and the amount that could potentially exist at multiple scales (USDA 2019). Over the past decade, UTC has emerged as

References

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