spatial distribution of urban greenery in ......statistical and spatial analysis green areas as an...

SPATIAL DISTRIBUTION OF URBAN GREENERY IN WARSAW. A QUANTITATIVE APPROACH

Elzbieta Bielecka, Beata Calka, Agnieszka Bitner

Prof., Elzbieta, Bielecka; Military University of Technology, Faculty of Civil Engineering and Geodesy; 2 Gen. Witolda Urbanowicza St., 00-908 Warszawa 46, Poland; [email protected]; Dr, Beata, Calka; Military University of Technology, Faculty of Civil Engineering and Geodesy; 2 Gen. Witolda Urbanowicza St., 00-908 Warszawa 46, Poland; [email protected]; Dr, hab., Agnieszka Bitner; University of Agriculture in Krakow, Department of Agricultural Land Surveying, Cadaster and Photogrammetry; 253a Balicka St., 30-198 Krakow, Poland; [email protected];

Abstract The aim of the study is a profound spatial and statistical analysis of urban greenery in Warsaw and its availability for the citizens. By means of the Average Nearest Neighbour analysis, Moran's I, we proved that the spatial distribution of greenery in Warsaw is clustered, irregular and not spatially autocorrelated. Parks and gardens are located in the central part of the city, while forests dominate in the suburbs. OLS regression shows that the urban greenery area significantly depends on the district area (R2=0.96). The relationship between the area of urban greenery and the number of inhabitants depends on the location of a district. For districts located close to the center, Pearson's r is 0.96, while for the peripheral ones - only 0.26. 74% of residential area is located within 1 km from recreation and leisure green areas, and 90% within 2 km. Green space allocation per capita is 121,7 m2 but varies significantly between the districts (from 3 to 602).

Keywords: spatial analysis, urban greenery, statistical analysis, spatial distribution

INTRODUCTION

Urban greenery, also known as green infrastructure or urban green space, is an extremely important element of the urban landscape. It fulfils important ecological, technical and health functions, such as: reducing the heat island effect, infiltration of rainwater, or noise suppression (Czerwieniec and Lewińska, 2000; Dige 2011, Hudeková 2011). The presence of green areas has a positive effect on the aesthetics of a place (Łukaszewicz and Łukaszewicz, 2009). The analysis of urban greenery allows for a better understanding of a city structure (Fialkowski and Bitner 2008) and functions (McDonnell et al. 2009, Niemelä 2011). An accurate estimation of green space coverage and an assessment of the type of green space system facilitate city planning (Breuste et al. 2008). The benefits and functionality of urban green spaces are broadly discussed in the literature with regard to their social, economic, cultural and environmental aspects of sustainable development. Fuller and Gaston (2009) documented, on the basis of 386 European cities, that a city shape and size affect profoundly the proximity to green space outside the city boundaries. They also found that small, densely populated cities show very low per capita green space allocation. Moreover, the analysis of green space coverage shows very high diversity: from 1.9% (Reggio di Calabria, Italy) to 46% (Ferrol, Spain). Poland and Warsaw fall below the average values. It could be partially explained by the rough data used, e.g. Urban Atlas and CORINE Land Cover with a minimum mapping unit of 25 ha.

This paper seeks to show that Warsaw is a green city, not only in the minds of its residents or tourists, but also according to the results of a quantitative study. The study aims at a profound spatial and statistical analysis of urban

Proceedings, 7th International Conference on Cartography and GIS, 18-23 June 2018, Sozopol, Bulgaria ISSN: 1314-0604, Eds: Bandrova T., Konečný M.

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greenery in Warsaw, paying particular attention to its availability for the inhabitants. It also explores the relationship between the population of Warsaw and the amount of green spaces, using the green space coverage and green space per capita indexes. Although there are some studies of greenery in Warsaw (Degórska, 2004; Degórska, Degórski, 2017). this work focuses on a quantitative analysis of spatial data collected in the national topographic database at a scale of 1:10,000.

Study area

Warsaw is the capital and the largest city of Poland. It stands on the Vistula River in the east-central Poland and covers an area of 517.24 square kilometers. Its population is estimated at 1.7 million. Warsaw is made up of 18 districts which play a major role in defining the character of the city: Bemowo, Białołęka, Bielany, Mokotów, Ochota, Praga Południe, Praga Północ, Rembertów, Śródmieście, Targówek, Ursus, Ursynów, Wawer, Wesoła, Wilanów, Włochy, Wola, and Żoliborz (Figure 1). According to the 2016 Polish statistical data (GUS, 2016), the population distribution in the study area varies considerably from the densely populated Ochota (8,600 person per square kilometer) to the sparsely populated district of Wawer (900 person/sq.km). Moreover, the size of the districts is heterogeneous, and varies from 8.47 to 79.90 km2, in Żoliborz and in Wawer, respectively. Both the city government and the residents perceive Warsaw as a green city. In 2017 Warsaw applied for the European Green Capital Award, and reached the semi-final.

Figure 1. Study area location

Data

Information on the type, area and location of urban greeneries comes from the National Database of Topographic Objects (thereafter referred to as BDOT10k). BDOT10k is a seamless vector database with the level of detail corresponding to 1:10,000 civilian topographic maps (Bac-Bronowicz et al., 2010) and with geometrical accuracy varying from one to several meters, depending on the type of features and the source of their acquisition (Doskocz, 2016; Ławniczak, Kubiak, 2016). Its thematic scope covers nine classes, among which land cover and protected areas contain information on urban greenery (Regulation of 2011). The pivotal objects of the study are listed in Table 1. BDOT10k was also a source of information on residential buildings, which was used for computing the accessibility of green areas. District borders were derived from the National Register of the Territorial Division of the Country, while the population density - from the Basic Urban Statistics (GUS, 2014). All data are listed in Table 1.


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Table 1. Data used in the study

Source name Class name Object types Data custodian Spatial

resolution Temporal

scale

BDOT10k Land cover Forest and tree-cover areas, shrub and bush Surveyor General 1:10,000 2010

BDOT10k Buildings and constructions Buildings Surveyor General 1:10,000 2010

Register of Territorial Division Units

Administrative division

Districts, fifth level administration division Surveyor General District 2016

Demography Population Population density Central Statistical

Office (GUS) District 2012

Statistical and spatial analysis

Green areas as an element of urban greenery were defined in two legal acts: the Act of April 16, 2004 on Nature Conservation (Journal of Laws 2004 No. 92 entry 880) and the Act of January 31, 1980 on the Protection and Shaping of the Environment (Journal of Laws, 94.49.196), while the more comprehensive definition, listing various forms of green areas, is in the Nature Conservation Act. This study, in general, follows the definition given by the Nature Conservation Act. The analyzed urban greenery consists of: city parks and gardens, forests, tree-cover areas, groves, and protected area, including the Natura2000 sites.

Green space coverage, expressed as a percentage, is the quotient of green spaces in a district and the total area of a district. Green space per capita shows the surface area of green spaces (in meters) per one inhabitant in the districts and in the entire city.

Inferential statistics were used to reach conclusions that extend beyond the immediate data alone. The Average Nearest Neighbor (ANN) and Global Moran’s spatial autocorrelation tools demonstrated the spatial distribution pattern of urban spaces in Warsaw. The Average Nearest Neighbor tool measures the distance between each geographical feature centroid and its nearest neighbor's centroid location and averages all these nearest neighbor distances. When the average distance for a hypothetical random distribution is below average, the distribution of the features being analyzed is considered clustered. If the average distance is greater, the features are envisaged as dispersed. The average nearest neighbor ratio, calculated as the observed average distance divided by the expected average distance, less than 1 highlight the clustering pattern, greater than 1- dispersion (Mitchell, 2005). The Global Moran's I statistic measures spatial autocorrelation as the similarity between values of an area of urban green features as a function of spatial distance. The Moran’s I Index varies between − 1.0 and 1.0 for maximum negative and positive autocorrelation, respectively. Non-zero values of Moran’s I indicate that richness values in quadrats connected at a given geographical distance are more similar (positive autocorrelation) or less similar (negative autocorrelation) than expected for randomly associated pairs of quadrats. Statistical significance of the Index is expressed as a z-score and p-value (Getis, Ord, 1992).

Ordinary least-squares (OLS) regression was chosen to model the relationship among urban green space (dependent variable), district surface area and population density (independent variables). By OLS and the coefficient of determination (R2) the fraction of variance of urban green space in districts was explained by the total district area and population density in the districts of Warsaw.

The accessibility of urban green spaces was computed in a two-step analysis. Firstly, buffers of 100, 500 1000 and 2000 m were created around recreational green areas (parks, gardens) and natural green areas such as: forest, tree-covers, scrublands and protected areas. The buffers size were justified by research conducted by Panduro (2013). Moreover, van Herzele and Wiedeman (2003) or Cvejić et al. (2015) assume that the minimum walking distance should be of 100 m to the nearest green space (door-to-door distance) while the maximaum distance - about 2000 m. Secondly, all residential buildings within the buffer zones were selected and their percentage share in the district was calculated.

The results of the investigation are presented in the form of a choropleth map according to the rules established by Dukaczewski (2016), Koch (2016) as well as Horbiński and Medyńska-Gulij (2017), graphs and tables.


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RESULTS AND DISCUSSION

General characteristics of urban greenery

Green areas in Warsaw comprise almost 25% of the city surface area. It is one of the few European capital cities where green spaces comprise not only parks, gardens and other green leisure areas but also forests and a nature reserve (Ciołkosz, Bielecka, 2005). Forests occupy 52.39 km2 and account for a high percentage (42%) of green space in the city. They are located mainly on the fringe of Warsaw and form a green belt around the city (Figure 2). Together with the tree-cover area they constitute 13.6% of the total surface are of Warsaw. The Kampinoski National Park, located in the near vicinity of Warsaw covers a small part of the Bielany district (the Bielany Wood). It is protected as a UNESCO World Biosphere Reservation. The green bank of Vistula River is the habitat of wildlife, mainly birds, and belongs to the Natura 2000 sites. Other protected areas are small spaces scattered all over the city. Protected green space takes up 14% of urban green space. There are 79 parks and gardens in Warsaw, they cover about 9% of urban green space and 2% of the total surface area of the capital. Some of the city parks are historic objects and are located near a former royal residence (Wilanów, the Łazienki Park). Many parks are accompanied by sport and leisure areas that make them favorite places of relaxation.

a)

b)

Figure 2. Warsaw urban green area a) spatial distribution; b) percentage share of urban green space

Spatial pattern analysis

The visual analysis of Figure 2a indicates clustered and uneven spatial distribution of urban green spaces. Parks and gardens are concentrated in the central part of the city, while forests - on the outskirts. This was confirmed by the ANN analysis. The Nearest Neighbor Ratio equals 0.754562, which indicates clusterization. The z-score of −29.308 shows that this clustered pattern of urban green areas is not a result of random chance (with the level of significance over 99%). The analysis of spatial autocorrelation between acreage of urban green space, by means of the Global Moran’s Index (equals 0.01029) evidently indicates that the null hypothesis of complete spatial randomness cannot be rejected. The pattern formed by urban green spaces is not significantly different than random, the value of a z-score is 0.953.

The uneven pattern of spatial distribution of urban green space is also highlined by the percentage share of green area in the total acreage of the districts (Figure 3a). Wesoła, Rembertów and Wawer are the districts with the highest green space ratio, amounting to 63%, 47% and 44%, respectively. These districts are located on the right bank of the Vistula river, on the outskirts of the Masovian Woods. In Bielany and Ursynów, the Bielany Wood and the Kabaty Woods (a common weekend destination for the inhabitants of Warsaw) have the largest influence on the share of green areas. The smallest values of the green space ratio are characteristic for two peripheral districts of Warsaw: Ursus and Włochy, 2 and 3% respectively. The average green space ratio for Warsaw is 20.5%. The standard variation equaling 16.28% and the coefficient of variation (CV) equaling 79% confirm a substantial dispersion of green space in the districts of Warsaw.


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a) b)

Figure 3. Warsaw a) –- green space ratio b) – green area per capita [in m]

Green space allocation per capita in Warsaw is 121.7 m2 but varies meaningfully between the districts of Warsaw (Figure 3b). The disparity is indicated by the coefficient of variation CV=148% and the standard deviation SD=181.2. The largest number, as many as 603 square meters of green space per capita is in Wesoła, a sparsely populated, fringe district. The smallest number, 3 sq. meters per person, is in Ursus, which is an industrial and densely populated district of Warsaw.

Statistical analysis

The statistical analysis of the relationship among population density in districts, urban green spaces and district areas revealed a significant difference between the districts located in the centre and its immediate vicinity (central districts) and the peripheral districts directly bordering the administrative boundaries of the city. The central districts include: Mokotów, Ochota, Praga Południe, Praga Północ, Śródmieście, Wola, and Żoliborz. The peripheral districts comprise: Bemowo, Białołęka, Bielany, Rembertów, Targówek, Ursus, Ursynów, Wawer, Wesoła, Wilanów, and Włochy.

The central districts are very similar in terms of their green space coverage. An average of 10% of their space is green space with a 17.58% margin of error (coefficient in simple linear regression = 0.0995±0.017). The coefficient of determination is equal to 0.87. The correlation coefficient is 0.93. These districts have similar density of population. There is a strong linear relationship between the surface of a district and the number of its inhabitants. The correlation coefficient is 0.96. This gives an average of 63 inhabitants per hectare. The coefficient of determination equals 0.93. Thus, there is a linear relationship between green space coverage and the number of inhabitants. There are 567 inhabitants per one hectare of green space. It gives 15 m2 of green space per inhabitant. The coefficient of determination is equal to 0.86, while the correlation coefficient is 0.93.

In the peripheral districts average green space coverage is substantially higher compared with the central ones and amounts to 36% with a 24% margin of error. The coefficient of determination is equal to 0.65. These districts are characterized by a higher level of diversity of the spatial distribution of green spaces. There are districts where green spaces comprise approximately one half of their surface area, and also districts where only 2-3% of their surface area is green space. The correlation coefficient is equal to 0.81. The peripheral districts are heterogeneous with regards to population density. There is no linear relationship between the surface of a district and the number of its inhabitants. The correlation coefficient is only 0.26. In the peripheral districts there is no linear relationship between green space coverage and the number of inhabitants. The correlation coefficient is barely 0.04.

Urban green space availability

Green spaces in Warsaw are quite well accessible. 74% of residential area is located within 1 km from green recreation and leisure parks, and 90% within 2 km. More than 7% residential buildings are in the near vicinity (up to 100 m) of parks and gardens, 47% - not farther than 500 m (Figure 4).


412

Figure 4. Percentage of residential buildings and the distance [in m] from green areas

The availability of green areas is different for inhabitants of detached or semidetached houses and multi-family homes. The residents of Ochota, Śródmieście and Żoliborz have the best access to urban greenery. On average 15% of multi-family buildings are located very close to parks (not farther than 100 m), and for 72-75% buildings distance to parks is not greater than 500 m. For example in Śródmieście, one of the central districts, more than 61% of family houses are situated next door to parks and gardens, as much as 97% - 500 m away parks and gardens.

Figure 5. The proximity of multifamily buildings to urban greenery, percentage of buildings at distances of 100, 500, 1000 and 2000 m a) the proximity of parks and gardens, b) the proximity of forests and landscape parks

The availability of parks and forests is the worst in Bemowo, Białołęka, Rembertów, Wawer and Wesoła, the fringe districts. Only 2 to 5% of multi-family housing is located within a 500 to 1000 m distance from urban greenery. However, it is compensated for by very good access to forests and landscape parks. The percentage of multi-family houses located within a 500 m distance from forests is 72% for Białołeka, 82% for Rembertów and over 95% in Wawer and Wesoła. Inhabitants of detached and semi-detached houses have similar access to forests. The inhabitants of Ochota have to cover the greatest distance to get to a forest. Only 20% of residential areas are within a 30-minute walk to a forest.

CONCLUSIONS

Urban greenery is highly diversified both in terms of spatial distribution and the types of green areas. The analysis revealed substantial differences between the central and peripheral districts. Drawing a distinction between the types of districts was an important element of the analysis. The two types of districts differ with respect to the average surface area occupied by green spaces. Linear relationships between the surface of a district and the number of inhabitants and between green space coverage and the number of inhabitants are found only in the central districts. The central districts are homogeneous with regards to population density. If all districts were analyzed together, information about the relationships taking place in the central districts would be lost. The high value of urban green ratio (20.5%), green space allocation per capita equals 121.7 m2 as well as satisfying green area accessibility prove that Warsaw is perceived as a

a) b)


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green city. However, it is important to be aware of some threats linked to rapid urbanization of peripheral districts and densification of sparsely built-up areas that could diminish urban greenery area and cause its highest fragmentation (Bober et al., 2016).

The study results provide a reference to urban planners as well as local authorities for future urban greening practices. They are also helpful for people searching for apartment buying or renting. Different types of urban greenery have different spatial distributions and diverse associations with districts population and area. In Warsaw urban greenery is clustered and evenly distributed. Parks and gardens are mainly located in the central part of the city, while forest at the outskirts. The neighborhood of green areas can sometimes be perceived by residents as unfavorable, especially when it comes to transport accessibility. Large, fenced parks and gardens are a significant obstacle when one needs to reach some destination quickly (Moscicka et al. 2016; Pokonieczny 2018).

It is worth to mention that the proximity of green space, expressed as a buffer zone, is not exactly equal to its accessibility. The buffer distance does not fully reflect the visiting distances. Future studies should take into consideration park size, park quality, and different visiting distances to better quantify the potential benefits of urban parks.

ACKNOWLEDGMENT

The research was conducted under financial support of statutory research PBS/23-933/2016 at the Institute of Geodesy, at the Faculty of Civil Engineering and Geodesy Military University of Technology in Warsaw and statutory research DS 3366/KGRKiF/2018 at the University of Agriculture in Krakow, in the Department of Agricultural Land Surveying, Cadaster and Photogrammetry.

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BIOGRAPHY

Prof. Elzbieta Bielecka

Elzbieta Bielecka is a professor at the Faculty of Civil Engineering and Geodesy at the Military University of Technology, in Warsaw where she heads group on geographic information systems and science. She holds a graduate degree in geodesy and cartography and a PhD in geography form Warsaw University, Poland. She has nearly 40 years of experience in education, research and consulting in the field of GIS and cartography. In her research she focuses on the theoretical issues of GIS, especially data quality and uncertainty, spatial modeling as well as national SDI. She is the author of many research publications, consultant in the implementation of GIS in public administration. She was a member of TWG INSPIRE for land cover theme. Currently, she is editor-in-chief of the Geodesy and Cartography, the journal of Polish Academy of Sciences.


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Dr eng. BeataCalka

Beata Calka is a graduate of the Faculty of Geodesy and Cartography at Warsaw University of Technology. She completed doctoral studies at Military University of Technology, the Faculty of Civil Engineering and Geodesy, and obtained a PhD degree in 2014, in the discipline of Geodesy and Cartography (speciality: spatial planning and GIS). Since 2014 she has been working at Military University of Technology in the Department of Geographic Information Systems as an Assistant Professor. In 2015 she did an internship at Stanford University in the Silicon Valley, the United States, in the framework of the program "Top 500 Innovators" organized by the Ministry of Science and Higher Education. Her research interests include geographic information systems, spatial data modelling, spatial analysis, the quality of spatial data, and property management. Since 2006 she has been a member of the Association of Polish Surveyors, since 2015 a member of the Association of the Top500 Innovators, and since 2016 a member of the Polish Association for Spatial Information.

Dr hab. Agnieszka Bitner

Agnieszka Bitner obtained: a master’s degree at the Faculty of Mathematics and Physics of the Jagiellonian University, her Ph.D. in Agricultural Sciences in the field of Environmental Management, her D.Sc. in Geodesy and Cartography in the field of Technical Sciences, and a real estate appraiser license. Her postdoc in 2005-2006 at the Northwestern Institute on Complex Systems (NICO), Northwestern University, Evanston, USA turned her research interests toward morphological analysis of the GIS cadastral maps and cartographic-mathematic methods of analysis of spatial phenomena. She is an assistant professor at the Department of Agricultural Land Surveying, Cadaster and Photogrammetry, Faculty of Environmental Engineering and Land Surveying, Agricultural University of Cracow.


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