Green Materials in Sustainable Urban Planning: History
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Contributor:
Isidoro Fasolino
,
Federica Cicalese
,
Alessandro Bellino
,
Michele Grimaldi
,
Rosario M. del Caz-Enjuto
,
Daniela Baldantoni

Urban green planning is crucial in promoting sustainable urban ecosystems through the mindful use of vegetation, but few approaches are currently able to account for the ecosystem services provided by urban green planning in ex ante planning applications. Indeed, by estimating the functions exerted by different vegetation elements in urban ecosystems through a purposely developed set of equations, the procedure allows for the optimization of the development of urban plans by maximizing the contribution of vegetation to ecosystem dynamics. Specifically, the proposed methodology is articulated in two phases, i.e., the functional role of vegetation is firstly modeled through simple geometric features and specific ecological traits accounting for plant interactions with the environment, and then the selected vegetation traits are used in guiding the choice of the species. The approach has been exemplified through case studies, thereby highlighting its ability to guide planning decisions based on the type, abundance, and spatial organization of vegetation to promote the sustainability of urban development.

  • urban sustainability
  • urban landscape
  • vegetation functions

1. Introduction

Urban sustainability defines a conceptual framework for the development of urban ecosystems satisfying the fundamental principles of economic efficiency, social equity, and environmental integrity [1][2][3][4]. Green infrastructures play a crucial role in promoting urban sustainability by supporting the ecological functioning of the urban ecosystem [5][6], with efficiencies that are dependent upon the species assemblages, their spatial configurations, and the adoption of adequate planting and maintenance techniques [7][8]. Specifically, urban green areas act as reservoirs of biodiversity and support processes such as matter cycling, climate mitigation, environmental remediation, soil protection, and improvement of the aesthetic–social–cultural–spiritual spheres of citizens [9][10][11][12]. These contributions are usually classified into six groups of functions determining the provision of ecosystem services [13]:
  • Ecological: supporting biodiversity and sustaining ecosystem processes;
  • Protective: protecting soil in degraded or sensitive areas (riverbanks, embankments, landslide areas, etc.) and mitigating the effects of land degradation and environmental pollution due to anthropogenic activities;
  • Hygienic–sanitary: improving the integral health of citizens and promoting recovery during illness [14];
  • Social and recreational: supporting recreational and social needs, thereby making the city more comfortable;
  • Cultural, educational, and scientific: providing cultural and educational references that promote the harmonious entanglement of people and nature, as well as foster the scientific understanding of the environment;
  • Aesthetic–architectural: improving urban landscape structure and scenery.
Considering the crucial role exerted by the spatial configurations of urban green infrastructures, the principles of landscape ecology should arguably guide their planning. Similarly, species ecophysiology should guide the selection of the species and of the associated soils; however, in general, the inclusion of ecological criteria in urban planning is still challenging, and the ecological role of green infrastructures is usually evaluated in ex post contexts only. Such a strategy hinders the optimization of the urban plan aimed at maximizing the ecological efficiency of green infrastructures and, therefore, limits the development of sustainable urban environments. Indeed, urban green planning is mainly managed on a technical prescriptive level as a strategic resource guiding the quality and resilience of the urban environment, which is an approach related to structural limitations in the current legislative reference context [15][16]. However, the urban project must be understood as an inescapable link between urban planning and the environment and, as such, must embrace the ecological dimension in its functional role.

2. Methodological Background

The ecological role of green infrastructures in urban ecosystems can be evaluated in terms of quantifiable functions such as climate mitigation (rainfall interception, evapotranspiration, soil structuring and permeability, etc.), air quality improvement (CO2 absorption, O2 release, pollutant trapping, etc.), ecological connectivity enhancement, and biodiversity conservation (ecological corridors, habitat formation, etc.), as well as social benefits (shading, visual and acoustic insulation, wind attenuation, etc.).

3. Methodology

The proposed approach relies on identifying a suitable set of indices for the different, quantifiable functions exerted by vegetation in urban ecosystems and on defining a suitable normalization measure to make the results commensurable. In order to guarantee a large leeway in optimizing the structure of urban green areas, the indices mainly rely on simple geometrical measures such as plant number, as well as size or area occupied, thereby allowing for the identification of shapes and their spatial arrangement to maximize ecosystem services provided by vegetation. In addition, morphological and physiological attributes can be used to associate particular characteristics (e.g., broadleaved/coniferous, clumped/regular, deciduous/evergreen vegetation, etc.) to the shapes and finely tune the choice of green elements. In this context, the leaf area index (LAI), defined as the ratio of total leaf area to ground area [17], appears in most of the proposed indices. Indeed, LAI relates to several processes at the interface between the active photosynthesizing surfaces of plants and their surrounding environment, such as shading, CO2 absorption and storage, pollutant absorption, climate mitigation, and rainfall interception. Morphological and physiological parameters allow for associating shapes to particular species, with an additional layer of details introduced later in the planning process. The maximization function relies on the weighted average of the indices, which are grouped into different classes in relation to the specific functions that the different indices are meant to measure. Such groups are defined as the weighted average of particular indices and allow for differentially weighting the desired ecological functions in relation to urban lot destinations. Ultimately, the method involves three information layers at different levels of detail/synthesis, with a weighted average function allowing for moving across the layers.

4. Concluding Remarks

Overall, the proposed methodology bridges the gap between classical urban green planning approaches, thereby ignoring the ecological functions exerted by vegetation and ex post modeling of vegetation roles in determining the dynamics of urban environments. Indeed, the procedure can be viewed as a coarse modeling of vegetation functionality based on simple physical and ecological considerations, which requires far less input data (in terms of quantity and quality) than other modeling approaches (e.g., i-Tree Eco [18]), which makes it usable in ex ante applications. Models such as i-Tree Eco are actually able to provide more accurate estimates of pollution removal, carbon sequestration, plant effects on hydrology, and building energy than our equations, but their complexity requires high quality input data that usually need to be collected in situ, thereby restricting their practical application mostly to ex post analyses. Although the developed indices (SGs) provide only gross estimations of the respective ecological functions, the proposed equations are based on sound assumptions and can be fruitfully applied in comparative approaches to guide the choice (and/or the development) of urban green plans to maximize their ecological efficiency. Moreover, the modularity of the approach, thus allowing for defining custom sets of equations and different weighting values for the different functions exerted by the vegetation, fosters the adaptation of the procedure to a broad spectrum of applications.
The adaptation of the methodology to different contexts can be further promoted by the inherently simple calculations involved, which can be straightforwardly vectorized and automated to provide planners and landscape architects with easy and efficient tools to quickly evaluate the ecological efficiency of their plans. In this context, object-oriented languages such as Java, Python, C++, or R are primary choices, thereby allowing for the representation of each green element as an object with associated parameters, including their spatial coordinates. In turn, such a representation would provide a straightforward means of interfacing the proposed methodology with geographical information systems, thus further promoting its adoption.
As a final remark, it should be noted that the proposed methodology actually splits the planning of urban green planning into two consecutive phases. Indeed, the elements of vegetation can firstly be modeled as simple shapes with specific attributes describing their interaction with the environment, and the attributes can then be used in guiding the choice of the species and the environmental conditions that match the simulated scenarios. On its own, such an approach not only simplifies the overall planning process, but also provides ecological criteria for the selection of the species used in urban plans, thereby promoting the realization of sustainable urban ecosystems.

This entry is adapted from the peer-reviewed paper 10.3390/su152216038

References

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  3. Ostrom, E. A general framework for analyzing sustainability of social-ecological systems. Science 2009, 325, 419–422.
  4. Geissdoerfer, M.; Savaget, P.; Bocken, N.M.; Hultink, E.J. The circular economy—A new sustainability paradigm? J. Clean. Prod. 2017, 143, 757–768.
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  10. Dierna, S.; Orlandi, F. Buone Pratiche Per il Quartiere Ecologico; Alinea Editrice: Firenze, Italy, 2005.
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  13. Bovo, G.; Miglietta, P.; Peano, O.; Vanzo, A. Manuale Per Tecnici del Verde Urbano; Città di Torino: Torino, Italy, 1998.
  14. Kaplan, R. The nature of the view from home: Psychological benefits. Environ. Behav. 2001, 33, 507–542.
  15. Kapoor, R.K.; Gupta, V. A pollution attenuation coefficient concept for optimization of green belt. Atmos. Environ. 1984, 18, 1107–1113.
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  17. Fang, H.; Baret, F.; Plummer, S.; Schaepman-Strub, G. An overview of Global Leaf Area Index (LAI): Methods, products, validation, and applications. Rev. Geophys. 2019, 57, 739–799.
  18. Nowak, D.J. Understanding i-Tree: 2021 Summary of Programs and Methods; Technical Report; USDA Forest Service: Madison, WI, USA, 2021.
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