1. Introduction
Urban areas are confronting more social, economic and environmental pressures than in any other period of history [
1,
2]. Cities face challenges such as population growth, climate change, scarcity of resources, environmental degradation, contamination and increased hazards to human health [
1,
3,
4]. The global urban area represents less than 3% of the total world surface [
5]. However, cities consume around 60–80% of the world’s energy and contribute to more than 70% of the total global CO
2 emissions [
1,
6]. The current trajectory of expansion of our cities increases pressure on natural ecosystems and contributes to the loss of biodiversity, which is intensified by the impacts of climate change [
7,
8,
9]. The future well-being of human populations is closely connected to urban areas and their resilience to climate change. According to IPCC, 2014, it is crucial to act in urban centers in order to achieve global climate change adaptation and to improve the quality of life of future generations [
10]. In this context, a different approach is needed to guide the upcoming development of our cities [
4,
11]. There is increasing evidence of the benefits that nature provides for human environments [
12,
13,
14,
15]. The application of green infrastructure (GI) in urban planning provides the opportunity to design cities and urban areas as living systems that are more connected with nature, creating healthier, resilient and sustainable urban environments [
16,
17,
18,
19]. GI and its application in spatial planning is recognized as a successful strategy to support resilience in many cities around the world [
18]. However, in Uruguay, the term “green infrastructure” is not explicitly mentioned in existing planning policies and regulations. Although there is a growing interest in the promotion of natured-based solutions and in the protection of natural resources, GI has not been implemented as an integrated approach in urban planning yet [
20]. Nevertheless, initiatives such as “Montevideo Resiliente”, a strategy from the Municipality of Montevideo (IM) in collaboration with 100 Resilient Cities (Rockefeller Foundation) [
21], or “NAP Ciudades”, a National Adaptation Plan for cities and infrastructure adaptation, which is a work from the Ministerio de Vivienda Ordenamiento Territorial y Medio Ambiente (MVOTMA) and the United Nations Development Programme (UNDP) financed by the Green Climate Fund, include the concept of GI. The formerly mentioned plan aims to develop actions to adapt the city to climate change and reduce its vulnerability by encouraging sustainable initiatives such as green infrastructure development [
22].
Although there is no single definition of GI, it can be described as an interconnected network of natural, semi-natural and built green spaces, designed for multifunctional purposes. These purposes include supporting biodiversity, restoring natural ecosystems, improving human well-being and increasing the resilience of cities [
8,
16,
19,
23]. Additionally, it provides an increase in the ecosystem services available, supporting multiple social, environmental and economic benefits, and it contributes to the adaptation of urban areas towards the impacts of climate change [
24]. GI benefits provided to populations differ depending on the location, proximity to the population or area with needs and in the uniqueness of the resource [
16].
The term GI is used for different scales, from national or regional ecological networks, to urban green space networks and local projects for stormwater management [
25]. Urban green infrastructure (UGI) is referred to its particular application in urban environments. Urban areas are characterized by strong interactions between social and ecological systems and face complex social and environmental challenges [
26]. Social challenges include population growth, poverty, inequality and an increasing demand in the consumption of water, food, land and energy. Ecosystems support human well-being but at the same time, environmental challenges, such as climate change, loss of biodiversity, deforestation and air and water pollution, are exacerbated by social pressures. Because of the interconnectedness of social and ecological systems, addressing these challenges needs an approach that integrates the multiple interlinkages and dependencies between both systems [
27]. UGI planning is particularly appropriate for cities, as it is centered on a holistic understanding of the relations between both systems [
25].
UGI has the potential to forge new connections between the two systems, resulting in a more effective way to manage complexity than traditional planning does [
25]. According to Hansen et al. 2017, UGI planning is based on core principles: multifunctionality, integration, connectivity and social inclusion; and supporting principles: multi-scale, multi-object and multi-disciplinary [
24]. These principles can be combined in diverse ways to respond to particular challenges that different regions may face [
24]. In addition, the flexibility and diversity of UGI components allow different combinations to be tailored for different local contexts, spatial levels and issues, resulting in a potential adaptation strategy for planning resilient urban areas [
16,
17,
25]. UGI contributes to the adaptation of urban areas towards the impacts of climate change because of its capacity to: retain, store and reuse water later, reducing stormwater runoff and floods; increase permeable surfaces; regulate local temperature; improve water quality; increase buildings efficiency; and provide new habitats for species [
8,
28]. UGI is a potential tool to be used as an adaptation strategy for planning and designing resilient urban areas to combat the impacts of climate change [
16,
17].
International examples of UGI application, demonstrate how UGI can be successfully implemented in spatial planning to promote sustainable, resilient cities [
29]. UGI reconnects cities with nature and turns them into a more resilient system with the possibility to tackle multiple urban challenges [
30]. One of the core principles of UGI is the capacity to provide several benefits and to integrate different environmental, social and economic functions [
31]. In many cities, the development of UGI projects is promoted due to their potential to address a wide range of urban challenges and at the same time provide multiple benefits and functions. However, the location of such projects is often determined according to only a single potential benefit (for example, stormwater management) [
19,
32].
In this context, the aim of the research is to develop a model to identify priority areas for green infrastructure in Montevideo. The best sites for UGI should be those where benefits are maximized and respond to various prioritized challenges or functions. In this way, the investment in UGI is justified, the role it plays is strengthened and its implementation can be promoted within the region. This study, therefore, analyses the application of UGI as a planning approach and develops a model to identify potential localizations for within the case-study city of Montevideo. The model allows planners to guide the future development of candidate areas, increase their resilience and improve the quality of life of their populations.
3. Results
The GISM aims to identify priority areas in which to focus the development of Green Infrastructure (GI). The model is conceived as a first approach to the issue and as a primary stage in the identification of geographical locations in need of green areas. After this first analysis, and previous to GI implementation, a deeper examination at the local or neighborhood level should follow.
The results exposed show priority areas for GI localization in Montevideo; each suitability map (see
Figure 5) shows suitable areas in need of GI localization responding to one of the priority issues selected. Suitability values range from very low to very high suitability. The areas in blue represent the lowest suitability values, while the red ones represent the areas with very high need of GI.
3.1. Priority: Stormwater Management
High suitability values are associated with the presence of water elements, floodplains and natural drainage lines, which also correspond to the lowest topographic areas. This is related to the fact that these factors are assigned with the greatest weight among all the factors. Very high suitability values for GI localization can be seen in areas that correspond to two of the main watercourses and larger basins of the region. They are considered vulnerable areas affected by the increase in the intensity and frequency of precipitations related to climate change, whose impacts rise as a consequence of informal urban developments located in floodplain areas. Other sectors with a great concentration of high suitability values correspond to central areas of the city. Parts of these areas have been affected in some recent occasions when intense precipitation exceeded the urban drainage systems, resulting in severe urban floods. Furthermore, other sectors with high suitable values can be appreciated in areas that can be related to the location of former watercourses, which were channeled and remain under paved surfaces. As a consequence, when heavy rains happen, sewerage systems overflow, in the lowest points of the natural drainage lines water tends to pond and floods appear.
3.2. Priority: Population Inclusion and Proximity to Green Areas
High suitability areas for GI localization are concentrated within central sectors. This responds to the fact that the highest weight is assigned to the socioeconomic factors, in particular to populations lacking green areas and to populations with unsatisfied basic needs (UBN). High suitability values are distributed along the region, mainly concentrated in areas with populations lacking green areas and along main transport corridors. Changes in the weights assigned to individual factors modify the final suitability maps. Therefore, it is very important to define in advance the priorities to be addressed. For example, when a highest weight is assigned to UBN, high suitability values tend to decrease in central areas and increase in peripheral areas. On the contrary, as weight for population density and behavioral exposure are increased, central areas increase its suitability while peripheral areas decrease. Another tendency we can see is the maintenance of high suitability values along the main transport corridors.
3.3. Priority: Local Temperature Regulation
High suitability values for priority GI location for urban heat regulation correspond mainly to the areas currently defined as urban areas. Especially, they match to those areas with higher percentages of paved surfaces, greatest behavioral exposure and with less vegetation or fewer water elements. As suitability maps indicate, suitability values decrease in the presence of large green areas, main watercourses or close to the south, where temperature is influenced by the coast.
3.4. Priority: Biodiversity Increase
Most of the urban area is indicated as high suitability areas. There are some exceptions with lower suitability values within the urban area, which correspond to sectors where large green areas or watercourses are located. The suitability map obtained for this priority has numerous similarities with the map achieved for local temperature regulation priority. These results support the idea that the presence of green areas within urban areas has a great influence on the regulation of local temperature. Low suitability values mostly correspond to areas with existing biodiversity values. The reason for this is that the model prioritizes areas in need of natural areas. Consequently, areas with less or no existing vegetation are the highest weighted, whilst areas with existing vegetation are assigned with lower values. Nevertheless, this does not mean that areas rated as low and very low suitability values are not suitable for GI. On the contrary, existing biodiversity and natural elements in the whole region must be protected and enhanced.
Variations in the reclassification values of the biophysical factors result in different outcomes. For example, when considering the lack of vegetation as a priority issue, highest weights are assigned to areas lacking vegetation and biodiversity; on the contrary, highest weights are assigned to vegetation and ecological areas when considering the presence of high biodiversity values to protect and landscape connectivity. GI multifunctionality cannot always be successful at achieving all the benefits at the same time. Sometimes priority issues have no compatible locations. In these cases is important that stakeholders have clear objectives and evaluate different possibilities to make trade-offs when possible [
32]. Different areas within the region show different suitability values according to the priority that is evaluated. The four suitability maps shown in
Figure 5 provide a visualization of the least and the most suitable areas for GI implementation in the locations where GI is needed the most in Montevideo.
3.5. Selection of High and Very High Suitability Values
High and very high suitability values from each case are selected with the purpose to compare commonalities among the different priorities (see
Figure 6a). In addition, this allows for assessing the possibility of multifunctional GI localization in places that can be benefited the most. After high and very high suitability values for each priority are determined, they are intersected in a final suitability map using the overlay analysis tool from ArcMap 10.5.1 [
53]. This tool allows us to intersect the common values and to perform an overlay analysis (see
Figure 6b). The resulting map shows priority areas for localization of multifunctional GI.
According to the resulting maps and the different high and very high suitability values obtained, four major areas or sectors are identified. Each sector is grouped because of proximity and similarities in its characteristics (see
Figure 6c). These four sectors are: sector A (a central consolidated urban area), sector B (a complex area due to the coexistence of different land uses, such as rural production, industrial areas, consolidated urban areas and informal non-consolidated urban areas, particularly located in floodable areas. The presence of the Pantonoso basin contains significant ecological areas. However, these areas are affected by environmental damage, water and soil contamination, social vulnerability and the presence of precarious housing), sector C (an area that involves urban areas and urban-rural interface, with different land-uses, unconsolidated areas, precarious habitats and loss of environmental services) and sector D (a small neighborhood sector, located in the coastal consolidated urban area). The results obtained and the former sectors described, need to be validated with the current situation and analyzed at a deeper level directly in the field.
4. Discussion
The model was able to identify a number of areas within the case-study region that are suitable locations for the implementation of GI. The GISM model considers different socioeconomic, biophysical and environmental factors to assess the different areas within the region. Additionally, it considers the diverse priority issues to be addressed. As a result, spatially significant areas in need of GI localization were detected.
For example, according to the model results, sector A (see
Figure 6c) concentrates the most quantity of high and very high suitable values, therefore represents a clear area to start with the prioritization of GI localization. In fact, this is an important central urban area that functions as a centrality for the region. It is characterized because of the concentration of different social services and economic activities. In previous decades, the area suffered a process of abandonment and degradation. Nowadays, governmental plans aim to promote the recuperation of the area, of its infrastructure, services and environmental qualities, as well as to increase its population density, and reinforce its function as a centrality. GI implementation in this area can contribute to the government plans for recovering the role of the area and improve existing open public space, green areas and environmental qualities. In addition, it can help address issues such as stormwater management, lack of green space, local temperature regulation and increase of biodiversity.
The dominant urban morphology of buildings in sector A is considerably dense and closed with an intense occupation of the land with little green cover and large percentage of impervious surfaces. Areas such as existing green spaces, free open spaces, streets, public parcels and buildings, can be suitable for GI implementation. Existing open spaces in the area currently lack natural features; they are not able to provide any green or nature interactions as are mainly covered with impermeable surfaces and have little to no vegetation and the majority of existing vegetation are non-native species. In addition, they are generally designed as monofunctional spaces. Allowing more functions to happen can result in more benefits for the population.
Within the area, there are no large free spaces left for easy implementation of new green areas. Streets can be an opportunity to reintroduce ecological functions back into the built environment, as most of the streets in the sector are automobile-oriented, with large percentages of impervious surface cover. Existing open spaces represent a real possibility to easily increase the quantity and quality of nature in the area too. Public parcels and buildings represent another opportunity to find partner organizations for the implementation of GI. GI could be used by these organizations as opportunities to incorporate educational uses, recreational activities or ecological purposes, such as urban gardens for the community. Vacant parcels and abandoned buildings have high chances to provide available space for temporary or permanent use for the localization of GI. With the incorporation of GI, the area can improve its environment, increase its land value and increase the quality of life of its population.
If we consider sector B (see
Figure 6c) as another example, we notice that it is a very different sector to sector A. However, GI implementation in this area can be as important as in sector A. Sector B involves part of the Pantanoso basin, which is characterized by high social vulnerability, informal settlements and environmental degradation. Currently, there are existing municipality plans for this sector that aim to recover the area. GI implementation in this sector can help to promote the protection of existing natural areas and landscapes with high biodiversity values, which are contiguous to urban areas and threatened by urban activities. These areas need to be managed to incorporate different functions, such as land conservation, stormwater management and recreational uses. Particularly, natural areas such as riparian areas and wetlands should be prioritized for conservation, creating stream buffers and areas for native nature regeneration as well as stormwater parks.
The main purpose of this research, to develop a model to identify priority areas for GI in Montevideo, was accomplished and importantly it is a generally applicable model that could be used in any city. The parameters within the model are not specific to Montevideo and the model does not require detailed or rare data; therefore, we expect that it could be deployed anywhere in the world. The methodology developed has potential as a tool to support future planning for multifunctional green infrastructure (GI) and to assist policymakers in making the most appropriate choice to locate GI projects in places where benefits can be maximized.
One of the core components of suitability analysis is the generation of suitability maps. Suitability maps were generated according to different priorities. These maps show the least and most suitable areas in need of green infrastructure localization. The different resulting maps were combined in a final suitability map, which shows a high suitability area for the localization of multifunctional GI. The final map should be analyzed carefully in case it is used for actual policymaking and the participation of all stakeholders, decision-makers and involved population should be included.
The weighting process represents one of the most important steps of the process. It was done based on the literature review as well as on other similar case studies. Errors in relation to accuracy in the designated weights might occur. As variations in the weights assigned directly affect final results, prior to further studies, outcomes should be always checked and corrected by a group of experts, ensuring they correspond with the current situation and priorities sought. For this study, the identified areas recognized by the model were revised with the “Montevideo Resiliente” Strategy. As part of this strategy, a map was elaborated, locating the main impacts and tensions affecting the region, such as climate change impacts, ageing population, lack of social cohesion, inequity, poverty, housing issues, uncontrolled urban expansion, environmental degradation, infrastructure and inadequate transport systems [
54]. In general, the intersection of high and very high suitability values (see
Figure 6b) are within the spatial areas that the strategy recognizes as the area where the prioritized impacts and tensions are located and that need to be addressed.
Two important observations are drawn from the model and its results. Firstly, the model identifies potential areas for the implementation of GI as part of a region’s masterplan (at the strategic level). The next step should be a deeper examination of those areas at a higher resolution (at a smaller scale) for example at the neighborhood level (operative level). Secondly, it is essential to determine appropriate and clear priority objectives so that accurate results can be achieved and the most quantity of possible benefits can be provided to the region, particularly during the final step (site level or implementation level).
Priority areas for GI implementation were determined. Previous to GI localization, a further step should be to ensure a finer scale analysis. This analysis should be done at the neighborhood level and should prioritize site locations to maximize the benefits of GI implementation. The evaluation needs to detect the most suitable locations to get the best results, according to the priorities and with the least economic costs. For the third level of analysis (implementation), further studies should include the needs and perception of different actors involved and local communities’ participation.
5. Conclusions
The main purpose of the research, to develop a model to identify priority areas for GI localization in Montevideo, was achieved. Priority areas for the location of multifunctional GI were identified. These results contribute to future analysis on GI implementation in the region, especially for increasing its resilience and its capacity towards climate change adaptation.
The GISM can be adapted to changes in the context. The data and weights can be updated or substituted to respond to other challenges that the region may face in the future or to newly available information. Most significantly, the model developed can be adjusted to a different context. Therefore, the model developed is not limited to Montevideo and it can be extended to other regions.
Suitability analysis can play an important role as an effective decision tool in the policy-making process towards future driving forces such as climate change. The resultant suitability maps can be used as a tool to contribute to future plans or strategies for the development of the region. The areas rated as with high and very high suitability need to be studied at a closer level to be included in future plans for the development of GI in the region. If new green elements are implemented in connection with other existing green areas, they can become a network of GI that can help to restore natural ecosystems, support an increase of biodiversity and help to adapt the region to the impacts of climate change. In addition, it can provide ecological, social and economic benefits for the whole area.