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The capacity and ecological flows of ecosystem services as well as the demand for them are key areas of urban and rural ecological planning that have been studied using the spatial-explicit model as a decision support tool. This study develops a framework for mapping the relationships among the capacity of and demand for ecosystem services, ecologi...
Citations
... Whange et al. [30] assessed GIs based on bio-energy landscape connectivity. Ji et al. [31] and Soga et al. [32] conducted a network analysis to investigate spatial distance and the relation between the GIs' layout and the city's shape. Menconi et al. [20], in a review regarding the complex system approaches to urban green system design, highlighted that scholars and urban green planners frequently considered the urban green system as homogeneous without evaluating the heterogeneity of its variables. ...
... Following an ecosystem services approach, generally, urban green planners identify synergies and tradeoffs between services and assess the cooccurrence and overlap of hotspots between multiple services in green areas' design [28]. Scholars developed methods to balance ecosystem services' provision, such as multicriteria analysis [28] evaluation of the landscape structure [27], building connectivity between GIs [29][30][31][32], and function combination between types of urban green area [65]. Instead, using a performance-based approach, the choices regarding tree species and locations for GIs are based on the specific ecosystem service that the decision-maker needs to emphasize in each urban area, giving custom-fit solutions. ...
Reducing air pollution is a crucial challenge in urban areas. In this regard, urban green infrastructures could play a pivotal role. In the literature, scholars analyzed both the ability of species-specific and layout-specific green infrastructures to reduce air pollution and the best location sites of new green infrastructures to increase the provision of overall ecosystem services. There is a lack of studies helping green urban planners and designers choose where and which green infrastructure to implement based on vegetation species-specific performance and differentiated demand for the ecosystem services of city areas. This paper uses tree cadastre data from a medium-sized city in central Italy (Perugia) and the traffic open-layers of Gmaps to develop a spatial analysis of the urban trees’ performance in PM10 dust retention, and the PM10 produced by vehicular emissions, respectively. The method generates a spatialized balance between demand (air-polluted sites by traffic) and supply (PM10 dust retention by trees) to support local decisions about the best locations for new green infrastructures and the choice between species. The paper analyzed 6710 urban trees in an area of 42.62 km2 with a linear road density of 15 km/km2. Platanus hybrida Mill. ex Münchh, Celtis australis L., Ulmus carpinifolia L., Pinus pinaster Aiton, Quercus ilex L., Quercus robur L., and Tilia cordata Mill. are the resulting optimal species to reduce PM10, with median values of 219.62, 181.47, 166.67, 154.66, 143.90, 118.61, and 118.04 g tree−1 yr−1, respectively. The paper is a first contribution in developing GIS-based tools that vary the recommended location sites and species for new green infrastructures based on the demanded ecosystem service. Urban planners are called to dynamically use and integrate numerous tools, such as the one developed here, to seek complex solutions capable of increasing the sustainability of urban systems.
... Rational urban and rural land use structure and spatial distribution under multi criteria constraints is the best way and goal to seek and select land use. Only by forming a reasonable urban and rural land use structure and spatial layout, we can ensure a virtuous cycle of land use system in a certain region and coordinate the relationship between land, population, food, and ecology [13]. Based on the general theory of convex objective function and constraint function, the models with linear constraint and convex objective function and the models with special nonlinear correlation are discussed respectively, the corresponding solutions and programming implementation are provided, and various models are numerically tested or applied to oilfield development planning, e effectiveness of the model and algorithm is verified [14]. ...
With the development of the times, the rational use of land has become the focus of social and economic development. In order to make more efficient use of land value, this study analyzes the spatial layout of urban and rural buildings under multicriteria constraints. From 2016 to 2021, the city showed a stable growth trend, and the growth rates of the three showed obvious correlation. In 2019, the average growth rate of machine learning algorithm is 46.6%, the average growth rate of decision tree algorithm is 48.2%, the average growth rate of cloud computing is 51.8%, and the average growth rate of this method is 52.5%. It can be seen that in these four ways, it is based on this reasonable land distribution system that has promoted the process of urban modernization. With the rapid economic growth, the scale of urban and rural construction land has expanded rapidly. Only when the experience and decision-making ideas of planning decision-makers are effectively applied to the process of land use spatial layout, a scientific land use spatial layout scheme can be obtained.
... Indeed, authors have studied the relationships of the UGS with its environment in terms of distance from residences (Quatrini et al., 2019;Lahoti et al., 2019;Akpinar, 2016), care facilities (Artmann et al., 2019), roads Sacchelli and Favaro, 2019;Sever and Verbic, 2019;Bertram and Larondelle, 2017), public transport (Chen and Chang, 2015), city centers (Riechers et al., 2019;Zhu et al., 2020), poor and wealthy areas (Cilliers et al., 2013), points of interest (Sacchelli et al., 2018;Zhu et al., 2020), and other public spaces (Cilliers et al., 2015). Ji et al. (2020) and Soga et al. (2015) conducted a network analysis to investigate spatial distance and the relation between the UGS and shape of the city. All these authors considered the green areas of UGS as homogeneous variables without evaluating their heterogeneity. ...
... Most planners use the local community only as a source of information. They observe their behaviors (Tzoulas and James, 2010) and use their observations to evaluate people's needs (Ji et al., 2020;Lahoti et al., 2019). In other cases, planners organize focus groups and surveys to estimate CES demand in UGS (Artmann et al., 2019;Mahmoudkhani et al., 2020). ...
The urban green system is complex because it comprises heterogeneous small and large areas and linear elements connected to each other and with the city system with variable and non-linear rules. Every action in a green area changes the equilibrium of the system and can activate unpredictable synergies or conflicts with internal or external variables. Therefore, every action in a green area also changes the ecosystem services it provides to citizens. This paper focuses on cultural services and aims to evaluate the use of complexity science in their design and strengthening. After revisiting the main characteristics of complex systems thinking, the study performs a systematic literature review following a five-step process. Starting from an initial sample of 395 papers, 70 significant studies were selected. A descriptive and thematic analysis was then conducted of these to search for scholars familiar with complexity science or with one or more of its properties. Our results indicate this approach is lacking in the evaluation and planning of cultural ecosystem services. However, we discuss how urban green scholars apply the proprieties of complex systems in their studies, namely interactions, internal connections, emergence, non-linearity, resilience, and self-organization.
... Thus, SPAs are also regarded as the destination and sink of the ES demand delivery process. Similar to the process of spatial flow from the SPAs to the SBAs (Baró et al., 2016;Ji et al., 2020;Li et al., 2020), we assumed that the ES demands from the built-up areas can also be allocated and projected to the corresponding natural spaces depending on the movement of the spatial flow from the source where the demand is generated (SBAs) to the sink where the demands are satisfied (SPAs). The process of spatial flow to transport and delivery ES is used to simulate the implementation process of ES demand allocation from SBAs to SPAs and facilitate spatial mapping in terms of the type of natural spaces and the total amount and spatial distribution of demand in natural spaces to reflect the response of natural space systems to ES demand. ...
Co-urbanized areas around large cities in developing countries face the problem of spatial disconnection between supply and demand areas of ecosystem services (ES). To explore the reflection of human needs in the nonadjacent surrounding natural spaces and identify the response of the existing natural space system to the ES demand in terms of total amount and spatial distribution, a new method for ES demand mapping in co-urbanized areas was proposed. Based on the theory of the ES delivery chain, urban built-up areas are identified as service benefiting areas (SBAs) and the sources where demands are generated, natural spaces are regarded as service provision areas (SPAs) and the sinks and destinations where demands are satisfied, and ES spatial flow is considered as the delivery mechanism and ecological process that promotes the demand flow from sources to sinks. An indicator cluster composed of four multidimensional indicators, including flow quantity, flow boundary, flow direction and allocation mode along the distance, was used to characterize the spatial flow and represent the four key links in the technical path of allocating ES demand from built-up areas to natural spaces with spatial flow to intuitively reflect the spatial characteristics of human social demands projected in them. We quantified and mapped the distribution of three ES demands in builtup areas and surrounding natural spaces. In the former, the high-demand spaces are concentrated in the areas with high population density or high aging degree; while in the latter, the high-demand spaces are mainly adjacent to the built-up areas or the large-scale natural paces. By controlling the flow quantity, expanding the flow area, increasing the flow directions and improving the ES supply capacity of SPAs within a given distance, the high ES demands in the above spaces can be effectively regulated.
... With increasing attention being paid to the relationship between ESs and human well-being, some researchers have evaluated the spatial matching of UGS ES supply and demand, which is helpful in urban planning [50,51]. However, most of these studies do not provide practical guidance for urban green space planning [52]. In this study, based on the results of the UGS ES supply and demand assessment at two scales, we provide specific theoretical optimization suggestions for administrative units with unbalanced ES supply and demand, including UGS optimization schemes and locations (see Section 3.4). ...
Assessing the supply and demand of urban green space (UGS) ecosystem services (ESs) can provide relevant insights for urban planning. This study presents an analysis method for the spatial distribution of UGS ES supply and demand at administrative unit and 1-m grid scales and directly compares the matches of ES supply and demand in spatially explicit maps at two scales. Based on the analysis results at administrative unit scale, administrative units with an unbalanced UGS ES supply and demand were divided into three types: (Ⅰ) lack of green space; (Ⅱ) unreasonable green space structure; (Ⅲ) comprehensive, and different optimization schemes were put forward. According to the analysis results at 1-m scale, the regions with an unbalanced ES supply and demand of an administrative unit were divided into the following: (1) severe ES shortage area; (2) moderate ES shortage area; (3) mild ES shortage area, and the severe ES shortage area was taken as the UGS optimization area. We take the UGS within the 5th Ring Road of Beijing as an example and propose suggestions for optimizing the UGS pattern based on the evaluation of the supply and demand of UGS carbon sequestration services and purification services for particulate matter with an aerodynamic diameter <2.5 µm (PM2.5). This study provides an easy-to-use evaluation method for the spatial distribution of UGS ES supply and demand and proposes different optimization suggestions for the unbalanced area, thus playing a role in UGS construction activities and green space structure optimization.
In the process of rapid urbanization, the need for green open spaces is increasing, predominantly that of parks. Parks play a vital role in the social, economic, and physical well-being of city dwellers. Park visitors often prefer to visit parks, which have good potential to accommodate the optimal number of visitors without compromising the quality of experience. Due to the lack of understanding of parks and visitors’ requirements, parks are either under-utilised or over-utilized. The optimal visitors carrying capacity is an important parameter to assess the optimal number of visitors an Urban park can accommodate in a given time. This study presents a method to calculate the optimal carrying capacity of visitors. For this purpose, a conventional three-level procedure of visitor carrying capacity for parks was considered in Korba City. In this regard, the physical, real and effective carrying capacity was estimated using “the Cifuentes method”. For this study, three parks from Korba City (C.G., India) were selected that are Silver jubilee park, Smriti nagar park and Vivekanand Udyan. The finding of research indicates that the mentioned three parks were working below the limit of carrying capacity, which means the facilities are underutilised. The outcome signifies may serve as a tool for the future planning of parks as well as other type of ecological environment such as national parks and zoo used for recreational activities. Hence, landscape architects, city planners and policymakers can work in the direction to derive significant information about the parks and park visitors for the optimal utilisation of the park
With modern industrialization and urbanization, air pollution has become a significant environmental problem in urban areas. The effective removal of air pollutants is crucial for improving air quality, maintaining human health, and achieving human well-being. As the most densely populated city in Taiwan, Taipei City faces a severe fine particulate matter (PM2.5) exposure problem. This study proposes a conceptual framework in response to urban PM2.5 pollution that adversely affects human health. The PM2.5 removal capacity provided by urban vegetation within Taipei City was first quantified, and its public health benefits were then evaluated. The optimal locations for different nature-based solutions (NBS) were also identified, which could be applied when forming urban PM2.5 pollution mitigation policies. The results revealed that the urban vegetation of Taipei City in 2016 contributed to reducing the health incidence change of premature death and certain diseases, equated monetarily to New Taiwan Dollar (NT$) 9.43E+08. In addition, as one of the four evaluated NBS, direct vertical greening presented with the highest benefit-cost ratio for Taipei City. Spatial mappings of the different NBS locations could guide the government in planning sustainable urban green infrastructure in the future.
Air purification service (APS) supply associated with urban green infrastructure (UGI) are limited in metropolitan areas, yet demand for APS to mitigate air pollution is growing. Consequently, quantifying the unrealized demand (UD) of APS (i.e., the demand exceeded the supply) and exploring its driving factors to maximize human well-being related to air quality from risk management perspective are becoming a new urgent task. Taking Beijing as a case, the study established a UDAPS assessment framework to identify the spatio-seasonal variations of UDAPS, analyze the impacts of socio-ecological factors on UDAPS and their responses to scales, and explore the main driving factors of spatio-seasonal UDAPS variations using Structural Equation Modeling (SEM). Results showed that: (1) UDAPS had distinct spatio-seasonal variations under the district and sub-district scales: central areas > suburban areas, southeast areas > northwest areas, and winter > spring > autumn > summer; (2) UDAPS decreased significantly as fractional vegetation coverage (FVC) and leaf area index (LAI) increased, while increased significantly with nighttime stable lights (NSL), building volume density (BVD) and temperature (T) increased under multiple spatio-seasonal scales; (3) the spatio-seasonal UDAPS variations were dependent on the interaction of socio-ecological factors and their different paths and various impacts: UDAPS variations in summer and autumn were major affected by the FVC and NSL, while by the NSL and T in winter and spring; additionally, the indirect effects of NSL, BVD, LAI and FVC on UDAPS by the mediation of T were identified. Our research is expected to deeply understand the APS and provide some guides on urban APS supply-demand balance.
Introduction. This paper presents the results of an assessment of the impact of fire on the bearing capacity of the ordinary concrete, to be taken into account in the rehabilitation of fire-damaged reinforced concrete structures in Burundi.
Materials and methods. Experimental samples of the ordinary concrete made respectively of coarse river aggregates and crushed coarse quarry aggregates were prepared and subjected to different heating temperatures (250, 350, 450, 600 and 900 °C) simulating the fire. After natural cooling, experimental samples were subjected to compression test; and diagrams showing the loss of the load-bearing capacity of the ordinary concrete used in reinforced concrete structures in Burundi were drawn.
Results. Negative impact of the fire on the load-bearing capacity of the ordinary concrete occurs above of 350 °C of heating temperature. Concrete made of crushed coarse quarry aggregates loses 50 and 78 % of its bearing capacity at around 525 and 900 °C of heating temperature, respectively. Similarly, concrete made of coarse river aggregates loses 50 and 70 % of its load-bearing capacity respectively at 600 and 900 °C of heating temperature. An evaluation curve of the after-fire bearing capacity of the concrete used in reinforced concrete structures in Burundi is established.
Conclusions. The negative impact of the fire on the load-bearing capacity of the ordinary concrete occurs above of 350 °C of heating temperature. Concretes made of crushed coarse quarry aggregates and concrete made of coarse river aggregates lose 50 % of its bearing capacity at around 525 and 600 °C of heating temperature respectively. Knowing the heating temperature that the fire-damaged reinforced concrete structure has undergone is indispensable in deciding on its demolition or rehabilitation.
