Ecological carrying capacity of public green spaces as a sustainability index of
urban population: a case study of Mashhad city in Iran
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DOI 10.1007/s40808-017-0364-2
ORIGINAL ARTICLE
Ecological carrying capacity of public green spaces
as a sustainability index of urban population: a case study
of Mashhad city in Iran
Mohammad Reza Mansouri Daneshvar1 · Fahimeh Khatami2 · Farzin Zahed3
Received: 6 May 2017 / Accepted: 4 August 2017 / Published online: 14 August 2017 © Springer International Publishing AG 2017
Introduction
Urban green spaces are important for the quality of life in increasingly urbanized regions. Urban green spaces domi-nantly include public parks as well as sporting fields, riparian areas and trails, private gardens, street trees and nature
con-servation areas (Roy et al. 2012; Wolch et al. 2014). Urban
public green space provides a wide range of ecosystem services that support the ecological integrity of cities and
urban population (Wolch et al. 2014). Therefore, physical
aspects on public green spaces are often mentioned to make
the sustainability aspects (Chiesura 2004). Urban
develop-ment and redevelopdevelop-ment plans with suitable encouragedevelop-ment must assign enough urban green areas with appropriate
loca-tion and design for human and natural biomes (Jim 2004).
Also, urban land-use planning procedures should include a systemic evaluation of the public green spaces to reach a
sus-tainable urban growth (Kong et al. 2007). New approaches
to the planning and management of urban regions, such as sustainable development and smart growth, are depend upon
patch-based landscape metrics (Herold et al. 2003), where
the patches are defined as homogenous regions of public green spaces.
Urban sustainability increasingly requires the abatement of pollution, plus the addition of positive features, notably green spaces, improve the new scarcity of healthy
environ-ment (Finco and Nijkamp 2003). Urban planners, designers,
and ecologists need to focus on urban green space strategies that are explicitly protecting social and ecological
sustain-ability (Wolch et al. 2014). Sustainable growth of urban
population and limitation should respect to all ecological footprints and landscape patches such as green spaces. In this regard, physio-ecological and spatio-temporal charac-teristics of green spaces in urban areas with respect to car-rying capacity procedure, which has been initially proposed Abstract Urban planners usually define carrying
capac-ity as the abilcapac-ity of a natural zone or a built area to absorb population or development without any risk for both zone and population. This research aims to expand a framework for investigation of urban carrying capacity, which can deter-mine a sustainability index of urban population based on public green spaces. For this purpose, a conventional three-level procedure of ecological carrying capacity for public green spaces was considered in Mashhad city, Iran. In this regard, the physical, real and effective carrying capacities were estimated for total public green spaces in Mashhad as about 68, 22 and 44% from total population, respectively. Furthermore, among Mashhad municipality districts, two districts represented the highest values of carrying capacity and high classes of ecological carrying capacity index over than 1 in Mashhad city due to accessibility to the natural patches and man-made gardens.
Keywords Ecological carrying capacity · Correction factors · Public green spaces · Sustainability index · Population · Mashhad city
* Mohammad Reza Mansouri Daneshvar
[email protected]; [email protected] http://www.researcherid.com/rid/G-2881-2012
1 Department of Geography and Natural Hazards, Research
Institute of Shakhes Pajouh, Isfahan, Iran
2 Department of Management, University of Turin, 218 bis,
Corso Unione Sovietica, 10134 Torino, Italy
3 Department of Urban Planning and Design, Mashhad
by Cifuentes (1992), may be provide a merit sustainability index of urban land and population growth.
The common methods of urban ecological carrying capacity represent characteristics of population and
ecologi-cal footprints (Xu et al. 2010). Ecological carrying capacity
of public green spaces is a specific type of carrying capacity and refers to the carrying capacity of the physio-ecological and social environment with respect to urban development. It represents the maximum level of visits as a certain
quan-tity measurement (Jiang et al. 2017), which an urban area
can support. As a measure of sustainability, urban carry-ing capacity is an important conceptual underpinncarry-ing that guides local governments and urban planners in promoting
sustainable urban development (Wei et al. 2015).
Carrying capacity is said to be the ability of natural and man-made systems to support the demands of users (Oh
et al. 2005). Several recent studies have reported
carry-ing capacity procedure as evaluation method of urban land
and population growth such as Oh et al. (2005) and Yishao
et al. (2013). As the urban population increases, practical
approaches, which incorporate the concept of carrying capacity into managing urban development, are needed (Oh et al. 2005).
According to Prato (2009), the literature on carrying
capacity distinguishes between ecological and social carry-ing capacity. Ecological carrycarry-ing capacity is the maximum population of an area that can be supported by a habitat area without damaging its function or reducing its supplementary capacity. But, social carrying capacity are defined as the maximum number of visitors without causing irreversible deterioration of the physical environment and appreciable loss of visitor satisfaction.
Ecological carrying capacity forms the basis for deriva-tive concepts such as urban carrying capacity (Wei et al.
2015). The urban ecological carrying capacity provides a
framework for integrating physical, socio-economic, and environmental systems during the sustainable urban
plan-ning (Bernadette et al. 2009). The ecological carrying
capac-ity as the maximum level or threshold limit of visiting, was
developed by Cifuentes (1992), and further explained and
applied by worldwide researches (Zacarias et al. 2011).
The Cifuentes (1992) procedure is the most suitable as it
integrates the dimensional parameters in a region compared
with other environmental methods (Rodella et al. 2017). Liu
and Borthwick (2011) have pointed that carrying capacity
provides a powerful tool for environmental planning and management.
The concept of carrying capacity was adapted from range management and was applied to recreation management in
the early 1960s (Wagar 1964; Farrell and Marion 2002).
This concept was developed by Cifuentes (1992) as
eco-logical carrying capacity procedure and was illustrated by
Ceballes-Lascurain (1996).
This procedure attempts to establish the maximum num-ber of visitors that an area can support based on the physical, biological and management factors, considering three main levels: the physical carrying capacity (PCC) that is the maxi-mum number of visitors physically fit into a region over a particular time, the real carrying capacity (RCC) that is the permissible PCC after the correction factors, and the effec-tive carrying capacity (ECC) that is the sustainable RCC
after the management capacities (Cifuentes et al. 1999).
Determination of carrying capacity requires natural data and the visitor characteristics, which is varied from a place to another place. Hence, procedures and parameters could change in different case studies according to the subject and priorities of the evaluation framework (Sayan and Ortaçeşme
2006).
In the present study, a conventional three-level procedure of ecological carrying capacity of public green spaces,
pro-posed by Cifuentes (1992), is considered in Mashhad city,
Iran. On this basis, we present a methodology of carrying capacity in order to evaluate the physical and ecological capability of public green spaces by definition of a sustain-ability index of urban population.
The importance of urban carrying capacity index is that it can be recognized as a sustainable threshold to measure the
condition of urban sustainability (Graymore et al. 2008). If
population growth and human activities exceed the thresh-old limit of carrying capacity, adverse impacts would occur and deteriorate function and resilience of a specified urban
region (Yue et al. 2008; Graymore et al. 2010). Carrying
capacity index serves as a measure to determine the optimal
population size and activity scale (Oh et al. 2005). Overall,
the main aim of the present study is to focus on a statistical procedure of carrying capacity for public green spaces with respect to reach a sustainable index of population growth in an urbanized region.
Study area
Mashhad city as the capital city of Khorasan-e-Razavi province, Iran, has amount of 2,766,300 population
(Statistical Centre of Iran 2011), which located in the
northeastern Binaloud elevations (36°37ʹ–36°58ʹN, 59°26ʹ–59°44ʹE) with mean altitude of 1100 m above sea
level (Fig. 1). This city is located in semi-arid region with
sensitive climate that experiences mean annual tempera-ture of 14 °C and annual precipitation of 260 mm. The surface area of urban restriction in Mashhad is recorded
as 29,200 ha (Mansouri Daneshvar et al. 2013), hence
the population density of Mashhad is 94.7 p/ha in 2011. According to the field observations in 2015 and related statistical results in GIS, the surface area of total urban green spaces (greater than 2 ha) in Mashhad is recorded
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as 3130 ha, which is divided into two classes of private/ non public gardens (787 ha) and public green spaces/ parks
(2343 ha = 23,430,000 m2). The main function of public
green spaces in the study area is recreation and social inclusion. General perspective of some foremost parks in Mashhad, which have the most social visitors, are shown
in Fig. 2 named as Khorshid, Kuhsangi and Mellat parks.
Also, distribution of all green spaces—categorized in to private and public spaces—in Mashhad is presented in
Fig. 3a. For this purpose, we consider Mashhad
municipal-ity districts. In 2015, Mashhad restriction is divided into 13-municipality district included a central business district
(CBD) (Fig. 3b).
Methodology
Physical carrying capacity (PCC)
To apply Cifuentes (1992) procedure, it is important to
con-sider the size of the area and the optimum space available for each user to visit. Hence, all major green spaces greater than 2 ha—with urban function—were considered into two classes of public spaces and private gardens in the study area. Thereafter, the public green spaces were selected to estimate of carrying capacity due to their public usage and managerial role in the urban planning. To apply three-level procedure of carrying capacity, three substantial equations
Fig. 1 General position and geographical location of the study area Fig. 2 General perspective of some foremost parks in Mashhad
are used to estimate of the physical, real and effective carry-ing capacities, which were relevantly resulted from several
studies like as Zacarias et al. (2011), Queiroz et al. (2014)
and Rodella et al. (2017).
The physical carrying capacity was determined by the
following Eq. (1) (Zacarias et al. 2011):
where, PCC is the physical carrying capacity, A is the
sur-face area of the public green space area in m2, Au is the area
available per user equal to 2.5 m2 and Rf is the rotation factor
(1)
PCC = A
Au×Rf ,
or diurnal rate of visit that is observed as 0.2 (~5-h from 24-h) through the fieldwork operations. According to carry-ing capacity literature, the Au value can be varied between 1
visitor per m² to walk comfortably (Queiroz et al. 2014) and
5–10 m² for tourists in coastal beaches (Zacarias et al. 2011).
In this study, based on recreational activity of walking and
resting of population in urban parks a value equal 2.5 m2 was
considered based on local conditions. Real carrying capacity (RCC)
The real carrying capacity was determined using Eq. (2)
(Zacarias et al. 2011):
where RCC is the real carrying capacity, PCC is the physical carrying capacity and Cf1 to Cfn are the correction factors,
determined using the Eq. (3) (Zacarias et al. 2011):
where Cfx is the correction factor of variable x, Lmx is the limiting magnitude of variable x and Tmx is the total mag-nitude of variable x. The correction factors are obtained by considering the environment, biophysical and social factors and these factors are closely linked to the specific condi-tions and characteristics of each region or activity (Queiroz et al. 2014).
Considering that green spaces is dependent on environ-mental attributes, eight correction factors were considered in this study as follows: Cf1 rainy days and Cf2 frost days data were obtained based on Mashhad synoptic station long-term climatic data during a time-period of 1951–2015
(Ira-nian Meteorological Organization 2015). On this basis, the
limiting magnitude for these factors were determined as 75 and 5 days per year, respectively, while the total magnitudes were the total assumed 365 days of the year. Therefore, the correction factors for Cf1 and Cf2 were determined as about 0.80 and 0.95, respectively in all municipality districts of Mashhad city.
Cf3 soil erosion factor was considered based on the exten-sion of geological units map (Geological survey of Iran
2010). Based on the local map data and fieldwork
observa-tion, the corrective factor for igneous rocks was assumed 1 (without limitation), while for sandstone, limestone, allu-vial and shale/marl units were considered as 0.9, 0.85, 0.8 and 0.75, respectively. The reasons for these corrective fac-tors related to the geological erodibility of each unit were extended over a region.
Cf4 earthquake hazard and Cf5 flood risk limitation data in two levels of 0.5 (with limitation) and 1 (without limita-tion) were considered based on vicinity to hazardous linear sources of seismic faults and stream channels. Also, Cf6 (2) RCC = PCC × (Cf 1 × Cf 2 × ⋯ × Cfn),
(3) Cfx = 1 −Lmx
Tmx,
Fig. 3 a Distribution of green spaces in Mashhad, b general position
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slope classes in two levels of 0.5 (with limitation) and 1 (without limitation) were considered based on a GIS-based topographical analysis to produce slope classes dominantly higher and lower than 5%. Topographical analysis of the study area was done based on a Global Digital Elevation Model (GDEM) from the Advanced Space-borne Ther-mal Emission and Reflection Radiometer (ASTER) on the National Aeronautic and Space Administration spacecraft
Terra (NASA 2011).
Cf7 pollution source and Cf8 traffic effect factors in two levels of 0.5 (with limitation) and 1 (without limitation) were considered based on field work operations and detec-tion of solid and water wastes, greenhouse gas emissions, acoustic pollution, traffic nodes and accessibility to tran-spiration systems. An expert-based decision was applied for this factor. To detect aforementioned correction factors, fieldwork observations were carried out through all the streets surrounded the green spaces in the study area during a weak time-period.
Effective carrying capacity (ECC)
The effective carrying capacity is a result of the combination of the real carrying capacity with the management capacity
of the area, as described by the Eq. (4) (Zacarias et al. 2011):
where RCC is the effective carrying capacity, PCC is the real carrying capacity and Mc1 to Mcn are the management capacities. Three management capacities were considered in this study: Mc1 environmental health, Mc2 accessibility to central business district and Mc3 social security.
Ecological carrying capacity index (ECCI)
Ideally, the carrying capacity of a region evaluates the level of supportable populations and their requirements
(Gray-more et al. 2010). In this regard, the ecological carrying
capacity index (ECCI) was developed after as a partial
sup-ply–demand balance method of Dong et al. (2011) in this
paper. The ECCI was estimated based on the ECC values. It means that the ECCI values dependent on a ratio of public green spaces’ ECC and municipality district’s population, as
described by the Eq. (5):
where ECCI is the ecological carrying capacity index and P is the population of a municipality district. The low and high classes of ECCI values were defined as <1 and >1, respectively. If the ECCI value of public green spaces was estimated greater than 1 in a district, then the mentioned
district has sufficient ecological footprint (Ress 1992) to
(4) ECC = RCC × (Mc1 × Mc2 × ⋯ × Mcn),
(5)
ECCI = ECC
P ,
support and locate any given population. But in vice versa (ECCI <1), the mentioned district has not enough ecological capacity for population.
Result and discussion
Estimation of physical, real and effective carrying capacities
The per capita public green space value in Mashhad is cal-culated as 8.4 m (23,430,000/2,766,300 = 8.4). However, to detect the sufficiency of public green spaces in each area, we need to examine their ecological carrying capacity based on an urban official division. According to GIS data, amount of 2343 ha of total green spaces (~75% from total areas) can be categorized as public spaces in Mashhad city with main
function of recreation use for citizens and tourists (Fig. 3a).
Daily PCC values were estimated for all public green spaces
in Table 1 and then annual results were considered based
on the municipality districts in Table 2 and Fig. 4a. On this
basis, five districts (2, 7, 9, 11 and 12) have a relatively high physical carrying capacity for public green spaces (>160,000 annual visitors), while seven districts (1, 3, 4, 5, 6, 10 and CBD) have a low value (<60,000 annual visitors).
To calculate RCC values, data for decreasing correction factors were obtained from several procedures for Cf1 rainy days (or cloudy days), Cf2 frost days, Cf3 soil erosion, Cf4 earthquake hazard, Cf5 flood risk, Cf6 slope classes, Cf7 pollution sources and Cf8 traffic effects. Then, all correla-tion factors based on municipality districts were extracted
in to Table 1.
According to PCC values and aforementioned correlation
factors, daily RCC values were estimated in Table 1 and then
annual results were considered based on the municipality
districts in Table 2 and Fig. 4b. On this basis, only district
9 has a relatively high physical carrying capacity for public green spaces (>160,000 annual visitors), while nine districts (1, 2, 3, 4, 5, 6, 8, 10 and CBD) have a low value (<60,000 annual visitors). Also to calculate ECC, three management capacities were considered including Mc1 environmental health, Mc2 accessibility to central business district and Mc3 social security. All these accelerating managing factors in two levels of 1.5 (with management) and 1 (without man-agement) were determined using urban infrastructure and future planning availability related to improve visitors’
per-ception (Table 1). According to RCC values and
aforemen-tioned managing factors, daily ECC values were estimated in
Table 1 and then annual results were considered based on the
municipality districts in Table 2 and Fig. 5a. On this basis,
three districts (2, 7 and 9) have a relatively high physical carrying capacity for public green spaces (>160,000 annual
visitors), while seven districts (1, 3, 4, 5, 6, 10 and CBD) have a low value (<60,000 annual visitors).
According to Table 2, all PCC, RCC and ECC values of
public green spaces’ carrying capacity were scaled
adjust-ing with population data in Fig. 6. Results revealed that the
PCC, RCC and ECC values for total public green spaces in Mashhad are amounts of 1,875,370, 600,564 and 1,223,628, respectively. Hence, the PCC, RCC and ECC values are con-tributed to about 68, 22 and 44% of total population. Among Mashhad municipality districts, two districts of 7 and 9 have highest carrying capacities in Mashhad city due to largest natural patches and man-made green spaces. In vise versa,
five districts of 4, 5, 6, 10 and CBD have lowest carrying capacities due to lack of urban green spaces.
The models outputs are assumed to be estimates of the carrying capacity, which give a set of apparent choices to decision-makers because they come from different equa-tions, yet the end product remains a single number. Hence, in order to present a more rigorous result, we need a likeli-hood approach. To estimate the likelilikeli-hood ratio, Chi-Square test was used in SPSS by crosstabs analysis. The results,
shown in Table 3, support our estimations for all PCC, RCC
and ECC values by significant likelihood ratio in regard the population of 12 valid cases.
Estimation of ecological carrying capacity index This section addresses to a sustainability index of urban pop-ulation growth, where the ecological patches and footprints can accommodate an appropriate population with determin-ing a reasonable number of uses. For this purpose, the ECCI values were estimated based on the ECC and population
data based on each municipality district in Table 4. Then the
classes derived from ECCI were shown in Fig. 5b. On this
basis, four districts of 7, 8, 9 and 12 were corresponded to high classes of ECCI. It means that aforementioned districts have a sustainable capacity to support and locate any given population. Conversely, other regions in Mashhad city have not an acceptable ecological footprint to support population.
Districts with high ecological carrying capacity index were demonstrated in southern and southwestern Mash-had city, where affected by natural enclaves of Binaloud elevations, catchments, woodlands and ecological biomes. These, natural enclaves, especially green spaces, with high
Table 1 Estimation of daily physical, real and effective carrying capacity values based on factors (Cf) and managing capacities (Mc)
Cf1 rainy days (or cloudy days), Cf2 frost days, Cf3 soil erosion, Cf4 earthquake hazard, Cf5 flood risk, Cf6 slope classes, Cf7 pollution sources and Cf8 traffic effects, Mc1 environmental health, Mc2 accessibility to central business district and Mc3 social security
District no. Park areas (ha) Daily PCC (p) Cf1 Cf2 Cf3 Cf4 Cf5 Cf6 Cf7 Cf8 Daily RCC (p) Mc1 Mc2 Mc3 Daily ECC (p)
1 20 47 0.8 0.95 0.8 1 1 1 1 1 29 1.5 1.5 1.5 97 2 221 484 0.8 0.95 0.8 1 0.5 1 1 1 147 1.5 1.5 1.5 496 3 90 197 0.8 0.95 0.8 1 0.5 1 1 1 60 1 1.5 1 90 4 57 125 0.8 0.95 0.8 1 0.5 1 0.5 1 19 1 1.5 1 29 5 53 116 0.8 0.95 0.8 1 0.5 1 0.5 1 18 1 1.5 1 27 6 43 94 0.8 0.95 0.8 1 0.5 1 0.5 1 14 1 1.5 1 21 7 421 923 0.8 0.95 0.9 1 1 1 0.5 1 316 1.5 1.5 1 711 8 139 305 0.8 0.95 0.9 1 1 0.5 1 1 104 1.5 1.5 1.5 351 9 747 1637 0.8 0.95 0.9 1 1 0.5 1 1 560 1.5 1 1 840 10 25 55 0.8 0.95 0.9 0.5 1 1 1 0.5 9 1 1 1 9 11 222 487 0.8 0.95 0.9 0.5 1 1 1 1 167 1.5 1 1.5 376 12 305 668 0.8 0.95 0.8 1 1 1 1 0.5 203 1.5 1 1 305 CBD 0 0 0.8 0.95 0.8 1 1 1 1 1 0 1 1 1 0 Total 2343 5138 – – – – – – – – 1645 – – – 3352
Table 2 Estimation of annual physical, real and effective carrying
capacity values based on Mashhad municipality districts
District no. Population PCC RCC ECC
1 176,104 17,155 10,430 35,405 2 485,833 176,660 53,705 181,040 3 322,018 71,905 21,859 32,850 4 244,944 45,625 6,935 10,585 5 168,876 42,340 6,436 9,855 6 253,963 34,310 5,215 7,665 7 206,968 336,895 115,218 259,515 8 94,040 111,325 38,073 128,115 9 300,246 597,505 204,347 306,600 10 264,523 20,075 3,433 3,433 11 192,223 177,755 60,792 137,240 12 39,636 243,820 74,121 111,325 CBD 16,926 0 0 0 Total 2,766,300 1,875,370 600,564 1,223,628
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ecological capacity and biomass should be incorporated into the urban environment. But, in recent years, physical devel-opments and redevelopment are severely in these regions are resulted to elimination of natural enclaves and ecological footprints especially in municipality districts 7 and 9. This trend is despite the fact that many cities earnestly provide greenery in new developments and preserve existing
green-ery in redevelopments and expansions (Beatley 2000).
Queiroz et al. (2014) have pointed that the carrying
capacity should facilitate the process of continuous moni-toring of visitors by adjustment to plans and to ensure that
development is carried out within the context of the opti-mum overall capacity level thus ensuring its sustainability
(Saveriades 2000). Recently, researchers have kept track of
the dynamic variation in urban ecosystem carrying capac-ity through calculating long-term time-series of ecological
footprint values (Huang et al. 2007). However, the breadth
and depth of research on urban carrying capacity are still
insufficient (Yishao et al. 2013). Current urban carrying
capacity assessments mainly focus on single factor analysis and little progress has been achieved on a comprehensive
study (Wei et al. 2015). Therefore, the ecological carrying
capacity procedure, as represented in this study, should be
Fig. 4 a Annual physical carrying capacity (PCC) and b real
carry-ing capacity (RCC) of public green spaces in Mashhad based on the municipality districts
Fig. 5 a Annual effective carrying capacity (ECC) and b ecological
carrying capacity index (ECCI) of public green spaces in Mashhad based on the municipality districts
considered during the temporal time-series for urbanized region of developing countries to represent the variations and degradations of increasingly developments.
Conclusion
The main aim of the present study was to investigate eco-logical carrying capacity of public green spaces in Mashhad city, Iran. On this basis, a methodology of ecological car-rying capacity in order to evaluate the functional capability of public green spaces was presented based on Mashhad municipality districts. A conventional three-level proce-dure to estimate of the physical, real and effective carrying
capacities were applied in Cifuentes (1992) procedure with
eight correction factors (Cf) and three management capaci-ties (Mc). According to the results, the PCC, RCC and ECC values for total public green spaces in Mashhad are amounts of 1,875,370, 600,564 and 1,223,628, respectively. Hence, the PCC, RCC and ECC values are contributed to about 68, 22 and 44% of total population of Mashhad. Among Mash-had municipality districts, two districts of 7 and 9 represent the highest carrying capacities (ECC greater than 260,000 visitors) in Mashhad city due to largest natural patches and man-made gardens.
Then, a sustainability index named as ecological carrying capacity index (ECCI) was developed with given popula-tion of each district. On this basis, four districts of 7, 8, 9 and 12 were corresponded to high classes of ECCI (greater than 1). Aforementioned districts with high ecological car-rying capacity index were demonstrated in southern and southwestern Mashhad city, affected by natural enclaves of Binaloud elevations, catchments, woodlands and eco-logical biomes. But in this time, the ecoeco-logical patches of these regions are seriously eliminated under physical
Fig. 6 Scaled adjusting population data with public green spaces’
carrying capacity values of annual a PCC, b RCC and c ECC in each municipality district
Table 3 Estimation of likelihood ratio based on Chi-Square test
Test Value Asymptotic
Sig. (two-sided)
Pearson Chi-square 1.320E2 0.23
Likelihood ratio 59.64 1.00
Table 4 Estimation of
ecological carrying capacity index (ECCI) and its classes based on Mashhad municipality districts
District no. ECCI Class
1 0.20 Low 2 0.37 Low 3 0.10 Low 4 0.04 Low 5 0.06 Low 6 0.03 Low 7 1.25 High 8 1.36 High 9 1.02 High 10 0.01 Low 11 0.71 High 12 2.81 High CBD 0.00 Low Total 0.44 Low
1 3
developments and their future ecological perspective is vague to plan.
The present study briefly concluded that the procedure of ecological carrying capacity could be adapted to urban outdoor areas especially green spaces. Among the existing green spaces, public green spaces could consider defining of a novel sustainability index to measure the population settlement in each region. In this regard, we can generalize ECCI application to compare the spatial–temporal popu-lation growth between different urban regions in order to detect their sustainability measurements.
Acknowledgements We thank anonymous reviewers for technical
suggestions on data interpretations.
Compliance with ethical standards
Funding This study was not funded by any Grant.
Conflict of interest The authors declare that they have no conflict
of interest.
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