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ABSTRACT
Recent research has proposed a GIS-based methodology to map a regional green infrastructure (RGI) by assessing patches’ suitability to be included in the RGI on the basis of four components as follows: natural value, conservation value, landscape value, and recreational value. This study builds upon such research with the aim to identify planning policies that can foster the enhancement of the RGI by increasing one or more of its components at the sub-regional scale. To this end, the RGI suitability map is overlaid with the planning schemes of the municipal master plans of three towns belonging to the Metropolitan City of Cagliari (Italy), and multiple linear regressions are performed. Results from this analysis show to which extent the zoning types identified in the city masterplan are related to high or low RGI suitability values, hence allowing for detecting those zoning types that should be targeted by the metropolitan city plan, if the RGI is to be improved, and for identifying appropriate planning actions to pursue this goal. The outcomes of the study imply that the eligibility of a land parcel to be part of the RGI depends on a number of factors strictly related to planning policies entailed by the zoning schemes of the municipal masterplans, such as presence and spreading of conservation and safeguard areas within the urban fabrics, improved accessibility of historic and natural landmarks, planned use of nature-based solutions within the regulating codes of municipal masterplans, improvement of habitat quality in the spatial context of rural areas. Main limitations of the proposed methodology can be recognized in the fragile theoretical foundations concerning the assessment of the value of recreational areas, and in the need for structured integration of nature-based solutions into the assessment of eligibility of land parcels to be included in the RGI.
KEYWORDS
Green Infrastructure; Ecosystem Services; Natura 2000 Network; Environmental Planning How to cite item in APA format:
Lai, S., Leone, F., & Zoppi, C. (2019). Municipal masterplans and green infrastructure. In C. Gargiulo & C. Zoppi (Eds.), Planning, nature and ecosystem services (pp. 488-501). Naples: FedOAPress. ISBN: 978-88-6887-054-6, doi: 10.6093/978-88-6887-054.6
a Assessorato della Difesa dell’Ambiente,
Regione Autonoma della Sardegna, Italy e-mail: slai@regione.sardegna.it
b Department of Civil-Environmental
Engineering and Architecture University of Cagliari, Italy e-mail: federicaleone@unica.it
zoppi@unica.it AN ASSESSMENT RELATED TO THE METROPOLITAN AREA OF CAGLIARI, ITALY
SABRINA LAIa, FEDERICA LEONEb
Municipal masterplans and green infrastructure
PLANNING, NATURE AND 489 ISBN: 978-88-6887-054-6
ECOSYSTEM SERVICES DOI: 10.6093/978-88-6887-054-6
© 2019, FedoaPress
1 INTRODUCTION
The concept of green infrastructure (GI) arises within the international debate at the end of the 1990s as a distinctive approach to landscape planning (Mell, 2016). GI is considered as a reference category in the contexts of several disciplines, e.g., landscape ecology (Jongman & Pungetti, 2004), greenway planning (Fábos, 2004), and management of water resources (Ahern, 2007). Moreover, different functions of GI are identified, e.g., biodiversity conservation (Benedict & MacMahon, 2006), or benefits provided to local communities and to civil society as a whole (Kambites & Owen, 2006). Therefore, several definitions of GI are available in the literature. Among many, Benedict and McMahon’s (2006), Wright’s (2011), Weber et al.’s (2006) and the European Commission’s (European Commission, 2013) are the most relevant. Benedict and McMahon (2006) define GI as the ecological system that supports environmental, social and economic health, emphasizing the socio-economic approach to GI. According to Wright (2011), although connectivity, multifunctionality and green areas represent the core ideas as regards the category of GI, a deterministic definition is somewhat questionable because, on the one hand, such definition would be inconsistent with a progressively evolving conceptual framework concerning GI, and, on the other hand, its intrinsic interoperability would imply the opportunity of using the GI conceptual framework in a number of research and technical fields related to environmental and spatial studies, which would entail a preference to a flexible, non-deterministic definition. Weber et al. (2006) stress the environment-related character of the GI concept, conceived as a system of natural and semi-natural areas spread over the landscape. Broadly speaking, from the above-cited literature GI can be understood as a network of natural and semi-natural areas that play a key role in supporting ecological, social and economic activities.
Under this perspective, this study aims at proposing a methodological approach to include and implement GI within spatial planning at the city level, hence it addresses an outstanding gap concerning scientific and technical research on GI.
The study builds upon a few recent articles, related to Sardinia, concerning the identification of a spatial taxonomy of areas eligible to be part of a regional green infrastructure (RGI) (Cannas et al., 2018; Lai et al., 2018) on the basis of four factors, namely the natural, conservation, landscape and recreational values.
It aims at defining and analyzing the relationship between the RGI, identified through the implementation of the methodology proposed in the above-cited articles, and the rules of municipal masterplans (MMPs).
In order to achieve this goal, a methodology based on the overlay mapping of the spatial taxonomy of areas eligible to be part of the RGI and the zoning layouts of MMPs, and on the
PLANNING, NATURE AND 490 ISBN: 978-88-6887-054-6
ECOSYSTEM SERVICES DOI: 10.6093/978-88-6887-054-6
© 2019, FedoaPress
analysis of correlations between the spatial taxonomy and the zoning rules, is proposed. Correlations are identified through regression analysis. The methodology is applied to the MMPs of three municipalities belonging to the Metropolitan City of Cagliari (MCC; Sardinia, Italy). The outcomes of the study offer important suggestions as regards the definition and implementation of the planning policies of the MCC, based on the general goal of strengthening the GI-related characteristics of the towns located within the metropolitan boundaries, with a view to a future expansion of the RGI within the MCC.
This study is structured as follows. Section 2 describes the proposed methodological approach and the spatial context for the implementation of the case study, that is, the towns of Cagliari, Assemini and Capoterra.
The results coming from the regression analysis which explores and detects correlations between the RGI and the spatial zoning rules of the MMPs of the three towns are presented in Section 3. In Section 4, implications for spatial planning policies related to the urban contexts of the MCC are discussed. Finally, directions for future research and concluding remarks are proposed and discussed.
2 MATERIALS AND METHODS
2.1 CASE STUDY
Municipalities are, in Italy, in charge of programs and plans, ruling on land development and land-use changes, hence they draft, adopt and approve their own MMPs, which simultaneously lay down a strategic policy for the concerned territory and provide the setting for the management of small-scale land-use transformation (Commission of the European Communities (CEC), 2000).
Due to the hierarchic nature of the Italian planning system (CEC, p. 35), MMPs must conform to a number of higher-level plans, the most prominent of which are regional plans, and especially the Regional Landscape Plan (RLP).
This study takes the towns of Assemini, Cagliari and Capoterra, in Sardinia (Italy) as case studies. Each town is a municipality, with its own elected local government and mayor, and it is also part of the MCC, recently established under national law no. 2014/56 and regional law no. 2016/2 (Fig. 1).
Cagliari, with its approximately 150,000 inhabitants and 85 km2 in size, is the regional capital
and the metropolitan center; Assemini (having around 27,000 inhabitants and 118 km2 in size)
and Capoterra (with about 23,000 inhabitants and 69 km2 in size) are two medium-sized
Municipal masterplans and green infrastructure
PLANNING, NATURE AND 491 ISBN: 978-88-6887-054-6
ECOSYSTEM SERVICES DOI: 10.6093/978-88-6887-054-6
© 2019, FedoaPress
to the same travel-to-work area, in that a good share (approximately 30 percent (ISTAT, 2019)) of their populations commutes to Cagliari on a daily basis.
Fig. 1 The study area
Within both the municipalities of Assemini and Capoterra, an MMP recently approved and compliant with the Sardinian RLP is in force; their planning documents and zoning schemes, approved in August 2015 and May 2016, respectively, are available on the municipalities’ official web pages1,2.
As for the municipality of Cagliari, a much older MMP, dating back to 2004, is in force; such plan was approved under the former landscape planning system, hence the complex and conflictual process of adjustment to the RLP (Zoppi & Lai, 2010) has not taken place yet. The planning documents and zoning scheme for the municipality of Cagliari are available on its official webpage3 and geoportal4.
1 The MMP of Assemini is in force since 27 August 2018. The documents are available online at
https://comune.assemini.ca.it/amministrazione/amministrazione-trasparente/pianificazione-governo-del-territorio/piani-programmi-16.
2 The MMP of Capoterra was published on the Official Journal of the Regional Administration of Sardinia
on 26 May 2016. The documents are available online at https://www.comune.capoterra.ca.it.
3 Available online at https://www.comune.cagliari.it/portale/it/at18_puc.page. 4 Available online at https://sit.comune.cagliari.it/?filtro=puc#13/39.2238/9.0906.
PLANNING, NATURE AND 492 ISBN: 978-88-6887-054-6
ECOSYSTEM SERVICES DOI: 10.6093/978-88-6887-054-6
© 2019, FedoaPress
2.2 ZONING SCHEMES
For each of the three municipalities, the zoning schemes were retrieved and analyzed in the light of their respective technical implementation norms. Next, the schemes were simplified on the basis of the provisions contained in the norms, so as to reduce as much as possible the number of zone types, for instance, by joining together sub-zones belonging to the same zone type, or by merging zones with similar planning or building rules. This simplification led to identifying ten types of planning zones; out of the ten types, listed in Tab. 1, type “E” is not included in Cagliari’s zoning scheme, while types “GS” and “IC” are not included in Assemini’s and Capoterra’s ones.
ZONE TYPE DESCRIPTION
A Historic districts
B Residential completion zones C Residential expansion zones D Industrial and commercial zones
E Agricultural zones
G Collective service zones
GS Collective service zones: green parks significant at the city level H Conservation and safeguard zones
EZ Enterprise zones, named “IC” in the MMP of Cagliari
S Public spaces reserved for collective activities, green areas, or parking lots at the district level
Tab. 1 Homogeneous zones identified by the zoning rules of the municipal masterplans of Cagliari, Assemini and Capoterra: simplified zone types
2.3 METHODOLOGY
This study builds upon a methodology applied in previous studies (Cannas et al., 2018; Lai et al., 2018; Arcidiacono et al., 2016; Lai & Leone, 2017) where a potential RGI is mapped taking an Italian region as a case study: Lombardy in Arcidiacono et al. (2016), and Sardinia in Cannas et al. (2018), Lai et al. (2018) and Lai and Leone (2017). In the Sardinian case, the suitability of each patch of land to belong to an RGI is assessed based upon four factors expressing as many functions provided by a GI, as follows:
−
natural value (NatVal), which represents habitats’ quality notwithstanding pressures and threats exerted on biodiversity;−
conservation value (ConVal), which accounts for the fact that green infrastructures are, in the definition provided by the European Commission (2013) and quoted in Section 1, “a …. network of high quality natural and semi-natural areas”;Municipal masterplans and green infrastructure
PLANNING, NATURE AND 493 ISBN: 978-88-6887-054-6
ECOSYSTEM SERVICES DOI: 10.6093/978-88-6887-054-6
© 2019, FedoaPress
−
recreation value (RecVal), which provides an indication of the extent to which landscapes are attractive for recreational uses and hence provide recreational ecosystem services;−
landscape value (LandVal), which accounts for the quality of landscapes as implied in the RLP’s normative framework.The suitability of each patch of land to belong to an RGI is then assessed by summing up the above four values, which all vary in the range (0–1), and it is therefore represented by the total value (TotVal): the higher TotVal, the greater the suitability.
The suitability map representing the Sardinian RGI (Fig. 2) is next overlaid with the zoning schemes of the MMPs provided in Fig. 3. Through a spatial intersection between the two layers, for each resulting polygon a vector having components (Zone, NatVal, ConVal, RecVal, LandVal, TotVal) is produced, where “Zone” represents the zone type assigned by the MMP and can take one of the ten values listed in Tab. 1.
Next, for each of the three municipalities here taken as case studies a multiple linear regression is performed: TotValk = 0,k + 1,kA + 2,kB + 3,kC + 4,kD + 5,kE + 6,kG + 7,kGS + 8,kH + 9,kEZ + 10,kArea (1) where “k” is the municipality;
explanatory variables representing the zoning scheme (“A” to “EZ”, see Tab. 1) are dichotomous, or Boolean, variables; each dichotomous variable can take only two values, 1 or 0, according to the following rule: if a patch is classed under the A zone type, the variable A equals 1, otherwise it equals 0; if a patch is classed under the B zone type, the variable B equals 1, otherwise it equals 0, and so on; each coefficient estimated by regression (1), i, i
= 1, …, 9, identifies the change in TotVal related to a patch in case it is classed under the zone type identified by the variable associated to the coefficient i (i.e., A, B, etc.) with respect
to the basic condition that the parcel of land under consideration was classed as “S” zone type; the coefficients estimated by regression (1), i, i = 1, …, 9, define a taxonomy of the
zone types based on the quantitative contribution to TotVal expressed by the values of i, i =
1, …, 9;
“Area” is the size of the parcel of land under consideration, resulting from the spatial intersection between the zoning map and the RGI suitability map; results from the multiple linear regression are finally used to develop, for each municipality, an ordered list of the planning zones; for each municipality, the order depends on the value of the coefficients i, i
PLANNING, NATURE AND 494 ISBN: 978-88-6887-054-6
ECOSYSTEM SERVICES DOI: 10.6093/978-88-6887-054-6
© 2019, FedoaPress
Fig. 2 Map of the total value, which identifies the eligibility of patches to be included in the Regional green infrastructure
Fig. 3 The zoning layout of the MMPs of Assemini, Cagliari and Capoterra
3 RESULTS
The estimates of the regressions related to Cagliari, Assemini and Capoterra define the features of the effects of a zone type on the eligibility of a patch to be included in the RGI. Indeed, each coefficient of the dichotomous variables estimated in the regressions identifies the effect on the eligibility of a patch to be included in the RGI as a consequence of it being classified as a homogeneous zone type from “A” to “H,” or as “EZ” or “GS” (only for the MMP
Municipal masterplans and green infrastructure
PLANNING, NATURE AND 495 ISBN: 978-88-6887-054-6
ECOSYSTEM SERVICES DOI: 10.6093/978-88-6887-054-6
© 2019, FedoaPress
of Cagliari, which does not show any “E” zone type) types, with respect to the basic situation of a patch being classified as “S” homogeneous zone type.
This estimated effect equals the difference in TotVal, everything else being equal. Accordingly, a ranking of the homogeneous zone types can be defined, on the basis of the estimated effects, from the highest to the lowest.
The zone types which mainly help to characterize a patch as being eligible to be part of the RGI are (i) the “A” type, that is, historic and artistic center, featured by environmental values related to the built environment, with the exception of Capoterra, whose “A” zone is, by the way, less attractive and valuable than Cagliari’s and Assemini’s corresponding areas; (ii) the “E” type, which identifies rural and agricultural areas, characterized by the lowest levels of soil sealing and land take (this type of zone is not present in the zoning layout of the MMP of Cagliari); and, above all, (iii) the “H” type, which is characterized by patches which the MMPs identify as worth protecting because of their environmental and landscape-related features. The effect on the eligibility of the “GS” zone type, which identifies open spaces and recreational areas, that is, almost-totally unbuilt areas, and which is only included in the zoning layout of the MMP of Cagliari, is consistent with the effect of the “H” zone type as well. Tab. 2 highlights the ranking of the zone types as regards their influence on the eligibility of patches to be included in the RGI, and the corresponding means of NatVal, ConVal, LandVal and RecVal, in order to identify the factors’ influence in a comparative way.
With reference to the “A” and “H” (and “GS,” in the case of Cagliari) zone types, the average values of LandVal are comparatively high, since they are always higher than 0.6. The average values of NatVal of the “E” zones are lower than the “A” and the “H” zones’ values, even though they are higher than the remaining zones. Moreover, the “H” zones show the highest average values of ConVal in all of the three cases, although there is room for improvement, since they are never higher than 0.3.
On the other hand, the conservation value on average equals zero as regards patches located in the “A” zones, whereas it is very close or equal to zero in already-urbanized areas or in areas characterized by ongoing advanced urbanization processes, such as “B,” “C,” “D,” “G,” “EZ” and “S”, which is consistent with expectations, since it is very unlikely that habitats protected under the provisions of European Union rules can be found in these areas. The results of the regressions show that the “A,” “E” and “H” zone types are the most important in terms of impact on the eligibility of patches to be part of the RGI.
Moreover, Tab.2 stresses that there is still large room for improvement as regards all the zone types. For example, the almost-totally urbanized areas classed as “B,”, “C,” “D,” “G, “EZ” and ”S” zone types show non-null NatVal and RecVal, and often comparatively not so low, in each of the three MMPs, especially with reference to the recreational profile (RecVal), which gives
PLANNING, NATURE AND 496 ISBN: 978-88-6887-054-6
ECOSYSTEM SERVICES DOI: 10.6093/978-88-6887-054-6
© 2019, FedoaPress
credit to possible scope for improving RGI-related features of areas located in the three towns of the MCC. ZO N E TY PE CAGLIARI ASSEMINI CAP O TERRA Ra nk Av er ag e Va lu es Ra nk Av er ag e Va lu es Ra nk Av er ag e Va lu es Nat Val ConV al Land Va Re lV al Nat Val ConV al Land Va l Re lV al Nat Val ConV al Land Va l Re lV al A 2 0.432 0.000 1.000 0.573 4 0.000 0.000 0.722 0.087 NS B 6 0.030 0.000 1.000 0.261 6 0.038 0.000 0.200 0.065 5 0.049 0.000 0.027 0.068 C NS NS NS D 7 0.233 0.000 0.952 0.039 2 0.644 0.162 0.636 0.010 NS NS NS NS NS E NP 3 0.482 0.028 0.352 0.006 3 0.529 0.061 0.523 0.010 G NS NS 2 0.448 0.057 0.639 0.019 GS 3 0.607 0.024 1.000 0.262 NP NP H 1 0.675 0.204 1.000 0.195 1 0.748 0.187 0.647 0.005 1 0.696 0.282 1.000 0.038 EZ 4 NP NP S 5 0.101 0.001 1.000 0.225 5 0.316 0.000 0.258 0.030 4 0.288 0.022 0.513 0.034
Tab. 2 Ranking of the homogenous zones based on the contribution to TotVal implied by the regression results, and average values of the four factors which determine TotVal, related to each homogeneous zone (NP: the homogeneous zone is not present in the MMP’s zoning rules; NS: the regression p-value entails that the coefficient is non-significant)
Particularly relevant is the improvement margin related to agricultural areas (“E” zone type) and to the protection areas (“H” zone type) as regards all of the four values.
This implies that the ruling framework related to these zone types would be worth exporting to other parts of the municipal land in order to increase the eligibility of patches to be included in the RGI.
4 DISCUSSION AND CONCLUSIONS
The study analyzes the relations between the land uses, defined in the MMPs of three local municipalities included in the MCC, and the RGI whose identification is based on the methodology proposed by Lai and Leone (2017).
According to the results presented in Section 3, the “H” zones are the areas that mainly positively affect the eligibility of patches to be part of the RGI in the three study areas. In
Municipal masterplans and green infrastructure
PLANNING, NATURE AND 497 ISBN: 978-88-6887-054-6
ECOSYSTEM SERVICES DOI: 10.6093/978-88-6887-054-6
© 2019, FedoaPress
particular, in relation to “H” zones, the average values of the four factors show the following similar trends (i) NatVal is higher than 0.5; (ii) ConsVal and RecVal are lower than 0.5; and (iii) LandVal equals 1 (maximum value) in the case of Cagliari and Capoterra and is lower than 0.7 in the case of Assemini. As a consequence, there is plenty of room for improving two out of the four factors (ConVal and RecVal).
ConVal is mainly influenced by the presence of habitat of community interest. “H” zone types are conceived as areas of particular environmental and natural interest; thus, they may represent buffer zones to protect high-quality sites, such as Natura 2000 sites, or steppingstones along migration routes. A possible policy recommendation aims at extending the environmental protection regimes related to habitats and species beyond the boundaries of protected areas by identifying those patches that, in relation to their characteristics, could be suitable for species and habitats. Therefore, advancements of scientific knowledge related to habitats and species within “H” zones and awareness-raising activities are preliminary necessary steps in order to increase the size of protected areas. In line with this recommendation, Maiorano et al. (2007) suggest that integrated management of Natura 2000 sites and of their neighboring areas may improve the effectiveness of conservation measures within protected areas due to control over human-induced activities in the surrounding areas. Acting on elements that influence RecVal shows more room for improvement than ConVal due to its lower values in relation to “H” zones in the three study areas. RecVal is calculated on the basis of geotagged information retrieved from the social media Flickr, representing the attractiveness of a certain area to visitors in a defined time period. Several studies (Heagney et al., 2018; Amoako-Tuffour & Martinez-Espineira, 2007; Font, 2000) show that recreational attractiveness of an area, conceived of as the demand for recreational activities, is influenced by different factors, such as accessibility and accommodation availability. Therefore, a possible recommendation concerns making these areas more accessible through infrastructures that, on the one hand, support slow mobility (such as cycle and pedestrian paths) and, on the other hand, do not increase habitat fragmentation. In fact, increased fragmentation of habitats is likely to result in decreasing values of ConVal and NatVal. In relation to NatVal, although its average values are quite high (between 0.67 and 0.75) in all of the three case studies, there is still some room for improvement. NatVal is mainly influenced by land uses and threats to habitats, identified through standard data forms of regional Natura 2000 sites. From this standpoint, two types of policy actions should be taken into account as particularly effective: reduction of threat and mitigation of land-taking processes. Both these actions can include measures aiming at restoring ecosystems, also through the use of nature-based solutions (NBSs). The concept of NBSs was coined by the European Commission (2015) to define techniques and solutions based on the use of nature
