A New Index for Measuring Urban Ecological-Environmental Spatial Inequality

A New Index for Measuring Urban Ecological-Environmental Spatial Inequality | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A New Index for Measuring Urban Ecological-Environmental Spatial Inequality Hamidreza Rabiei-Dastjerdi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8463200/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In recent years, the quality of the urban environment has received more attention in a variety of disciplines such as planning, geography, sociology, health sciences, and many others. In this paper, a new approach is proposed to measure urban environmental spatial inequality based on the geographical distribution of green spaces and the theory of urban political ecology. In this approach, ecological spatial inequality will be defined, modeled, and measured through green spaces extracted from satellite remote sensing observations. Urban political ecology provides a theoretical framework for implementing green spaces extracted from satellite images as a proxy for modeling the built environment conditions in urban areas. A greenness map, represented by the Normalized Difference Vegetation Index (NDVI), illustrates the highly uneven spatial distribution of green spaces, e.g., private, semi-public, and public. The proposed approach has been applied to study and map the urban ecological-environmental spatial inequality in Tehran, the capital city of Iran, and one of the fastest-growing cities in the world. The results show that most parts of the city and the majority of the population are suffering from spatial inequality in terms of Ecological-Environmental conditions. This new index has high potential to be applied in other cities with a similar socio-ecological context and spatial settings. Urban Studies City Management and Urban Policy Environmental Policy Geographic Information Systems Sociology Environmental Conditions Remote Sensing Spatial inequality Normalized Difference Vegetation Index Tehran Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction In recent years, the quality of life has received more attention in a variety of disciplines such as planning, geography, sociology, economics, political sciences, psychology, health sciences, and many other studies. It is also used as a significant index for policy evaluation, and rating places in planning (Kirby, 1999; Seik, 2000; Weng, 2007). There are some ranking systems for comparing cities in the world, such as Mercer[1] that covers 215 cities around the world; this ranking system uses 10 categories of indices for evaluating cities in terms of stable political, social environment, availability of housing, consumer goods, recreation possibilities, and a long list of public services, which are considered for quality of life. In this list, the rank of Tehran is 188 in 2012, and 187 in 2011, and in the Mercer infrastructure ranking list in 2012 is 146. Although these monitoring systems can be a tool for urban councils and municipalities, they are not perfect, and they do not provide any information about the quality of life in a city. On the other hand, quality of life is not constant all over the city; some parts definitely enjoy better conditions, while others suffer from problems associated with the quality of life. Recently, many cities have established monitoring systems for quality of life based on associated indexes. Urban Audit System[2] gathers information for cities on different components of quality of life, including more than 300 indexes in 357 European cities. Tehran has a monitoring system[3] as well; the indexes are limited, and the reports and indexes are mostly at the urban or district level. This means that the indexes are calculated for the whole city or at urban district levels (22 districts). In addition, quality of life has been defined from different perspectives on this topic. In the literature, it has been explained in both objective and subjective ways (Bauer, 1969; Ferriss, 2004). In an objective description, quality of life is actually the quality of living in a place, neighborhood, or environmental conditions of life. From a subjective point of view, quality of life is the satisfaction of people with their city and the place they live in, and the livability of the city (Pacione, 2003). On the other hand, quality of life is not constant all over the city; some parts definitely have better conditions, while others suffer from problems associated with the quality of life; in other words, urban spatial inequality in terms of Ecological-Environmental conditions. In this paper, an objective definition of the quality of environmental or ecological condition in the city, was used as an indicator of quality of life to introduce a new index for measuring urban ecological-environmental spatial inequality based on NDVI tailored for Tehran, an index that measures density and dispersion of green spaces in urban areas of remotely sensed data, and ecological conditions, environmental conditions and quality of the environment are used in the same meaning. [1]. See: http://www.mercer.com/home [2]. See http://www.urbanaudit.org/ [3]. See http://statistics.tehran.ir/ 2. Urban Green Spaces and Urban Political Ecology Green spaces and urban forests have various functions and values in a city (Carreiro et al., 2008 ; Van den Berg et al., 2010 ). From a functional point of view, they balance temperature, clean air, etc. They also have aesthetic values (Kong et al., 2007 ) and a privacy function (Tyrväinen & Miettinen, 2000 ) as well. Traditionally, urban green spaces bring public parks to mind, but there are other forms of green spaces. They include urban forests and greenness in the city, green spaces in semi-public spaces such as hospitals and governmental buildings, trees along the streets and boulevards, private gardens, small and limited trees, green spaces inside homes, etc. Van den Berg et al ( 2010 ) show that having a view of trees and forests (e.g., parks) reduces stress, and enjoyment of the landscape can decrease tension and anger, and increase concentration. Laumann et al ( 2001 ) explain that parks with various plant species cause relaxation in citizens (Chiesura, 2004 ). Seeing the trees and natural landscape has positive effects on people, including reducing stress, increasing happiness, and decreasing blood pressure (Hartig et al., 2003 ). An old garden with fruit trees and a variety of flowers can lead to mental concentration (Ottosson & Grahn, 2005 ). Another aspect of urban green space and urban forest regarding the complexity of power relations in the urban space is the spatially uneven distribution of these spaces in the city, which is related to urban socioeconomic inequalities (Mitchell & Popham, 2008 ; Wen et al., 2013 ) and spatial segregation (Abercrombie et al., 2008 ). Poor people, who do not have enough financial and credential resources to produce and maintain private green spaces, are often not able to gain access to healthy environments. Yet, investments for green space development depend on governmental and public resources, which in turn depend on taxes. In this sense, the ability of low-income people to have access to quality green space is limited. The lack of attention to investment in public urban green spaces in areas where low-income groups live is a source of environmental tensions, affecting their quality of life directly (Heynen, 2006 ). (Heynen et al., 2006 ), studied the unequal distribution of urban canopy cover in relation to social, racial, and ethnic inequalities. They consider the role of green spaces and urban forests in urban metabolism from a political urban ecology point of view. Moreover, green spaces have direct effects on the quality of the urban environment and the quality of life of urban populations. Their far-reaching effects in terms of mental, physical, and social domains can be described as stress and violence reduction (Astell-Burt et al., 2013 ; Fan et al., 2011 ), enhanced health (Oliveira et al., 2011 ), improved environmental conditions, improving air quality (Bottalico et al., 2016 ; Jayasooriya et al., 2017 ), reducing stress, and heat amelioration, increasing land and property values, etc. (Conway et al., 2010 ; Heidt & Neef, 2008 ). The role and effects of social and material production drew the attention of radical geographers (Castells, 2002 ; Castree, 1995 ; Gandy, 2003 ; Grundmann, 1991 ; Harvey, 1996 ; Hughes et al., 2007 ; Swyngedouw & Heynen, 2003 ). David Harvey argues that where society begins, nature ends (Harvey, 1993 ). Urbanization processes and their extensions towards the green space not only cause a social production of urban space, but also a reproduction of the natural space of the city (Fitzsimmons, 1989 ). The social production of the natural space of the city also creates specific social and ecological conditions in the city, thereby providing a battlefield for conflicts and competition (Heynen et al., 2006 ). These statements show how urban political ecology is formed. The social production of urban space explains the new dimensions of the production of social-spatial inequalities within cities. Urban political ecology, as an interdisciplinary area, has its roots in political economy and ecology (Osmond & Pelleri, 2017 ). It provides a framework for understanding the effects of social structure in an urban environment. This approach aims to consider and study power-laden social, ecological, and political processes that create an uneven social environment. More specifically, it considers social processes, material metabolism, form, and spatial structure of socio-ecological landscape in contemporary cities. These relations and factors are not constant; in fact, they change over scale and time because of their variation across different groups of people at various scales (Swyngedouw & Heynen, 2003 ). The relation between cities and nature became an arena for intellectual debate for social and environmental theorists (Bookchin, 1978 ). According to Lefebvre, urbanization causes the destruction of nature, the reproduction of nature, and the production of a somewhat second nature. “Nature, destroyed as such, has already had to be reconstructed at another level, the level of “second nature,” i.e., the town and the urban. The town, anti-nature or non-nature and yet second nature, heralds the future world, the world of the generalised urban. Nature, as the sum of particularities which are external to each other and dispersed in space, dies. It gives way to produced space, to the urban. The urban, defined as assemblies and encounters, is therefore the simultaneity (or centrality) of all that exists socially.” (Lefebvre, 1967 , P.15) Urban political ecology explicitly explains that physical conditions, including the urban environment, can be manipulated and controlled by urban elites and stakeholders in favor of their interests. Consequently, this action marginalizes some social groups by limiting their access to the urban natural environment. In the long run, both physical and social forms are combined with physical and social structures to produce the urban natural landscape actively. Therefore, each urban element (such as parks, skyscrapers, and natural heritage) is related to social and physical processes that define urban metabolism and social relations within a city (Heynen, 2016 ). The socio-spatial metabolism of the city, which produces a set of social and physical abilities and disabilities, leads to the formation of regions with opposite tendencies. This issue causes inequalities in different parts of the city. In addition, quality of life, in both physical and social terms, presents relevant disparities across different regions, and consequently. In addition, it causes a deterioration of social and physical conditions by reducing the quality of life and the quality of the urban environment of specific social groups (Heynen et al., 2006 ). Although from a geographical point of view, capitalism, more specifically neo-liberal capitalism, obeys several behavioral laws. In general, it may be summarized as depending on the development of urban environments as means of production, exchange, and consumption centers (Glaeser et al., 2001 ). The interesting point is that capitalistic systems consider the city as the commodification of urban elements. For this reason, the owners of power and wealth tend to have more urban facilities and advantages, such as natural endowments. As a consequence, under these conditions, some urban areas become the centers of deprivation and environmental pollution. Harvey argues that the commodification of urban elements, including urban green spaces and urban forests, is like a precious jewel in consuming capital and assets of a city because urban forests represent an important share of urban space consumption. To sum up, the uneven quality of the built environment is not randomly produced; instead, it can be considered as the product of an unbalanced social system. The theory of urban political ecology convincingly explains the role of creating factors of the urban built environment. This approach was used in this research as a theoretical justification for producing and mapping indicators of ecological (environmental) inequality in the city. 3. Case Study Tehran has been the capital city of Iran since the foundation of the Qajar dynasty in 1795. Nowadays, Tehran is one of the largest and fastest-growing cities in the world. One of the sharpest features of the city is the north-south socio-spatial divide. The Northern parts tended to display superior characteristics with respect to the Southern ones in terms of accessibility to urban facilities and services (Rabiei-Dastjerdi et al., 2023 ; Rabiei-Dastjerdi & Kazemi, 2016 ; Rabiei-Dastjerdi & Matthews, 2021 ), social class (Rabiei-Dastjerdi & Kazemi, 2016 ; Zad, 2013 ); the northern part enjoys better environmental conditions where the rich live and the southern part (the poor area) is suffering from lack of green space problem. Although there have been many attempts to reduce spatial inequality, there is still a north-south socioeconomic disparity. Figure 1 , a satellite image of the city, clearly shows urban environmental-ecological spatial inequality. This paper maps the uneven quality of the environment based on the geographical distribution of all types of greens; then it introduces an innovative methodology and a new index for measuring environmental-ecological spatial inequality in Tehran. 4. Measuring Ecological-Environmental Condition In this part of the paper, the procedure of mapping green spaces in the city, and extracting a new index based on the green space map for measuring urban ecological-environmental spatial inequality will be explained. Remotely sensed imagery is an advanced and effective technology for obtaining data and information from the Earth’s surface and features. Earth observations are particularly important; however, there are time, financial, and accessibility limitations. Remote sensing has wide and increasing applications not only in natural resource sciences, but also in social sciences and urban studies (Avery & Berlin, 1992 ). Recently, these digital images have been used to measure many physical indexes and produce objective maps at different scales. To name a few, there are NDVI (Normalized Difference Vegetation Index), land use/land cover maps and their corresponding change maps, urban heat island (UHI), etc. (Lo, 1997 ) used the Landsat TM image and socioeconomic data to calculate the environmental quality index. He used NDVI, surface temperature, and percentage of urban land use areas, as well as per capita income, population density, median home value, and percentage of university graduates from census data. Principal component analysis was implemented to generate the quality-of-life index. His results showed that this index had a positive correlation with NDVI, per capita income, and median home value. On the contrary, it had a negative correlation with population density, percentage of urban land uses, and surface temperature. In addition, satellite images can provide information and data with less effort, less cost, and in a shorter time. To measure greenness and vegetation on the earth, there are several extractable indexes from remote sensing data, such as the Transformed Vegetation Index (TVI), Corrected Transformed Vegetation Index (CTVI), Thiam's Transformed Vegetation Index (TTVI), and NDVI (Bannari et al., 1995 ). The NDVI has received more attention rather than the other indexes. It is calculated according to this equation: NDVI = (NIR - R) / (NIR + R) Eq. (1) Where NIR and R are the near infrared and red spectral bands in the electromagnetic spectrum (Bannari et al., 1995 ). The NDVI is a very easily calculated index that can be extracted from satellite images, although it has its own limitations and must be calibrated for measuring real biomass. Mathematically, this index varies between − 1.0 and + 1.0; but dense vegetation canopies tend to be between 0.2 and 0.8, clouds and snow areas tend to be in negative values, water bodies stand in low positive ranges and even slightly positive values, and soil present values between 0.1 and 0.2 (Huete, 1988 ; Qi et al., 1994 ). Since varieties of plant species have different growing times and maximum greenness, six Landsat 7 and ETM sensor images, at different times and dates, were selected for mapping green spaces. To remove the atmospheric effects on the reflectance values of satellite images, all images must be atmospherically corrected (Rees, 2013 ). After atmospheric correction, the image values represented the spectral reflectance for each pixel. Then, NDVI was calculated for each date/image within city borders. Atmospheric correction of images was done as follows. To counter the effects of cloud, atmospheric aerosol, and gases, the image must be corrected. The Top of Atmosphere Reflectance method using ENVI software was applied. This method consists of two steps. First, all digital numbers (DNs) of the images were converted to the radiance values, and then these radiance values were converted to the reflectance values. For each image, the distance between the Earth and the Sun in astronomical units, the Julian Date (the day of the year), and the solar zenith angle were needed. After each image was atmospherically corrected, an NDVI map was generated for each date. Figure 2 is the NDVI for the image (date: 2002-03-02). At this step, the threshold range (0.2–0.8) was applied to each image to map green spaces at the required time. The green areas show green spaces in the city image. Figure 3 illustrates the map of the geographical distribution of urban green spaces for the first image (date: March 2nd, 2000). Since different species of green plants and trees have different growing times, they cannot all be detected at once, due to the amount of chlorophyll in their leaves. As a result, one image cannot map all types of green plants. To compensate for this issue, six satellite images in a year with a proper interval time (two months) were used. Then the maximum function was applied to all six urban green space maps to produce the final green map, as follows, Fig. 3 . CGSM = Max {Ai} Eq. (2) CGSM : is City Green Spaces Map, and Ai : is the Green-Space Map at Time (i). This map, which obviously demonstrates the lack of green spaces in Tehran’s urban area, was produced to present areas suffering from green space shortages (Fig. 4 ). 5. A New Index for Measuring Ecological-Environmental Condition The effect of green spaces is not limited only to their neighborhood or location; their functions are more far-reaching in the environment, e.g., perceived general health of residents (Maas et al., 2006 ), stressful life events (Van den Berg et al., 2010 ), physical activity and overweight (Coombes et al., 2010 ), mental health (Nutsford et al., 2013 ), and even residential property value. However, the farther away a location is from green spaces, the less the effect it would receive from the green spaces in its neighborhood. In other words, the first law of geography is applicable here again: "Everything is related to everything else, but near things are more related than distant things" (Tobler, 1988 ). For example, in urban planning standards, accessibility to parks and public green spaces is measured by walking distance. Here, a new approach was used because green spaces have different functions for environmental quality, both directly and indirectly, regardless of their accessibility across all dimensions. Green space clears the air, benefits the city and its inhabitants, regardless of ownership, legal issues, and all human-related factors and barriers. The visual and physical access to green spaces can be limited to their owners, but their environmental and biological functions and benefits cannot be assigned only to them. Therefore, green spaces could be measured as a proxy for a quality environment. In doing so, a distance function was implemented to measure distance to green spaces, in order to extrapolate the effects (value) of existing green spaces in the city. The higher values were assigned to places closer to parks and the lower values to locations farther away from them. The values were calculated based on Table 2. Table 1 Assigned Values for Modeling Quality of Environment Based on NDVI List Type of Area Value Rang Minimum Maximum 1 Green Area 0.2 0.8 2 No Green Area 0.0 0.2 To sum up, the green space index was normalized to map the quality of the environment in the city based on the spatial distribution of green spaces and parks (Fig. 5 ). This index allows mapping of ecological disparities in the city. 6. Results and Discussion: Toward the New Index of Quality of Environment In this research, the ecological or environmental conditions were mapped based on the urban political ecology framework. These features are extracted from satellite images, NDVI, and land surface temperature, and used as proxies for the ecological dimension of spatial inequality in the city. A greenness map illustrates the highly uneven spatial distribution of green spaces (private, semi-public, and public) in Tehran. On this map, most parts of the city, except the northern part, strongly suffer from a shortage of green spaces. Despite the recent attempts to create public green spaces in southern deprived regions and large urban forests in the northwestern region of the city, there are still shortages of green spaces. A new index of ecological conditions was designed based on the greenness map as well. This index has high potential to be applied in other cities with a similar socio-ecological context and settings. Figure 6 is the reclassified map of the quality of the environment extracted from Landsat ETM+. Table 3 shows the condition of the city in terms of the quality of the environment. Figure 6 pinpoints a large gap in environmental conditions in different parts of the city. Table 3 indicates that the majority of people living in Tehran, the sum of the lowest (4 and 5) classes (88 percent of citizens), are suffering from low environmental conditions; in other words, 78 percent of the city area. The third class shows people living at a medium level of environmental conditions, which is only 6 percent of the whole population. The sum of the first row shows that only 6 percent of people enjoy better environmental and ecological conditions. Considering the area of the city based on environmental conditions displaying that most areas of the city are not favorable from an environmental point of view. Finally, this new index and methodology are suggested for other measures of urban spatial and ecological-environmental inequality with similar environmental and socioeconomic conditions. Table 3 Reclass of the Population and the City Area Based on the Quality of the Environment Class Area (%) Population (%) 5 10 9 4 77 79 3 7 6 2 5 4 1 2 2 Total 100 100 7. Conclusion In this paper, we studied the environmental-ecological conditions in Tehran and proposed a new index for measuring these conditions at urban scale using satellite images. This methodology seems to be very effective and can provide useful information for urban managers, planners, and researchers due to simplicity, practicability, capability to control for the areal unit problem, being fast and reasonable, a strong connection between theory and real world data, cost, and, of course, a partial solution and ability to control the Modifiable Areal Problem or MAUP (Wong, 2004 ) in measuring spatial environmental-ecological indexes. Moreover, using time series analysis based on produced indexes can produce measures for evaluating the performance and consequences of spatial and social policies in the city. The results confirmed that the city is facing this challenge, spatial inequality , in terms of environmental-ecological conditions. All produced indexes confirmed the hypothesis that there is a north-south spatial inequality trend in the city. Table 3 indicates that 88 percent of the population (class 1 and class 2) lives in low environmental and ecological conditions, and only 6 percent of the population lives in better conditions (class 4 and class 5). In addition, the results support the theory of urban political ecology. To sum up, we observed that Tehran is a highly uneven city in terms of environmental-ecological conditions. This index can be used and tested in other cities, at least in Middle Eastern cities, with similar socioeconomic and environmental conditions. As spatial inequality is a multidimensional phenomenon in the city, other dimensions of spatial inequality, including accessibility to urban facilities and services and socioeconomic conditions, should be studied to find the relations between all dimensions of spatial inequality. It means that to tackle spatial environmental inequality, we should consider the role and effect of other dimensions and causal factors in producing the urban built environment. Taken together, our results suggest that the proposed index offers a reproducible method of describing ecological–environmental inequalities across urban space. It enables easier measurement and comparison of differences and can inform more focused and equitable planning decisions. At the same time, it advances existing assessment approaches by integrating several environmental dimensions into a single meaningful measure and provides a substantive basis for further empirical application and critical debate. References Abercrombie, L. C., Sallis, J. F., Conway, T. L., Frank, L. D., Saelens, B. E., & Chapman, J. E. (2008). Income and racial disparities in access to public parks and private recreation facilities. American Journal of Preventive Medicine , 34 (1), 9–15. Astell-Burt, T., Feng, X., & Kolt, G. S. 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Spatial disparities in the distribution of parks and green spaces in the USA. Annals of Behavioral Medicine , 45 (suppl_1), S18–S27. Weng, Q. (2007). Remote sensing of impervious surfaces . CRC Press. Wong, D. W. (2004). The modifiable areal unit problem (MAUP). In WorldMinds: Geographical perspectives on 100 problems: Commemorating the 100th anniversary of the association of American geographers 1904–2004 (pp. 571–575). Springer. Zad, V. V. (2013). Spatial discrimination in Tehran’s modern urban planning 1906–1979. Journal of Planning History , 12 (1), 49–62. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8463200","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":566276564,"identity":"de7bc003-305f-43e3-af80-781e88ed8e05","order_by":0,"name":"Hamidreza 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14:37:55","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":100251,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8463200/v1/33f9d8b269a0fac682b85b85.html"},{"id":99813127,"identity":"73d46957-de8c-49c0-906f-02a27b9fc1f2","added_by":"auto","created_at":"2026-01-08 14:38:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":415995,"visible":true,"origin":"","legend":"\u003cp\u003eTehran Satellite Image ETM+ (Band Combination: 1, 4, 5)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8463200/v1/3d25011a97019aa77971bdb2.png"},{"id":99812729,"identity":"155ce049-20a0-4e1b-b0e6-ccf707195be2","added_by":"auto","created_at":"2026-01-08 14:37:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":394665,"visible":true,"origin":"","legend":"\u003cp\u003eTehran NDVI Map\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8463200/v1/01d05f3ce13a1ee74f793d0d.png"},{"id":99812810,"identity":"ab181821-ec6f-43f9-8962-515aeb3f7ab8","added_by":"auto","created_at":"2026-01-08 14:37:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":332419,"visible":true,"origin":"","legend":"\u003cp\u003eTehran Urban Green Spaces Map\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8463200/v1/94c161844fd05e7de55b2ac6.png"},{"id":99813247,"identity":"7ce32c91-930a-49d7-9f0e-5c3e0e01133a","added_by":"auto","created_at":"2026-01-08 14:38:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":396849,"visible":true,"origin":"","legend":"\u003cp\u003eThe Final Tehran Green Spaces Map\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8463200/v1/fcedaec66e0bf15283691754.png"},{"id":99812867,"identity":"d701ed90-0f91-4f26-8a88-2b0dceb0c33c","added_by":"auto","created_at":"2026-01-08 14:38:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":410534,"visible":true,"origin":"","legend":"\u003cp\u003eNew Index for Quality of Environment Based on NDVI and Greenness in Tehran\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8463200/v1/8cc4a8f3aa9cf0f3cb7e0994.png"},{"id":100356495,"identity":"a90351c6-f9bd-4015-8b2a-4165dec6f5cd","added_by":"auto","created_at":"2026-01-16 07:13:40","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":322659,"visible":true,"origin":"","legend":"\u003cp\u003eReclassification of the Quality of Environment in Tehran\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8463200/v1/fe216509caeb97e927bdc244.png"},{"id":100376762,"identity":"94837427-50ab-40c1-8d15-60b422288351","added_by":"auto","created_at":"2026-01-16 08:45:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2715564,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8463200/v1/16deb2d4-3dc5-4eba-a9a8-4afb76fa1de2.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eA New Index for Measuring Urban Ecological-Environmental Spatial Inequality\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn recent years, the quality of life has received more attention in a variety of disciplines such as planning, geography, sociology, economics, political sciences, psychology, health sciences, and many other studies. It is also used as a significant index for policy evaluation, and rating places in planning (Kirby, 1999; Seik, 2000; Weng, 2007). There are some ranking systems for comparing cities in the world, such as Mercer[1] that covers 215 cities around the world; this ranking system uses 10 categories of indices for evaluating cities in terms of stable political, social environment, availability of housing, consumer goods, recreation possibilities, and a long list of public services, which are considered for quality of life. In this list, the rank of Tehran is 188 in 2012, and 187 in 2011, and in the Mercer infrastructure ranking list in 2012 is 146.\u003c/p\u003e\n\u003cp\u003eAlthough these monitoring systems can be a tool for urban councils and municipalities, they are not perfect, and they do not provide any information about the quality of life in a city. On the other hand, quality of life is not constant all over the city; some parts definitely enjoy better conditions, while others suffer from problems associated with the quality of life. Recently, many cities have established monitoring systems for quality of life based on associated indexes. Urban Audit System[2]\u003csup\u003e\u0026nbsp;\u003c/sup\u003egathers information for cities on different components of quality of life, including more than 300 indexes in 357 European cities. Tehran has a monitoring system[3] as well; the indexes are limited, and the reports and indexes are mostly at the urban or district level. This means that the indexes are calculated for the whole city or at urban district levels (22 districts).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In addition, quality of life has been defined from different perspectives on this topic. In the literature, it has been explained in both objective and subjective ways\u0026nbsp;(Bauer, 1969; Ferriss, 2004). In an objective description, quality of life is actually the quality of living in a place, neighborhood, or environmental conditions of life. From a subjective point of view, quality of life is the satisfaction of people with their city and the place they live in, and the livability of the city\u0026nbsp;(Pacione, 2003). On the other hand, quality of life is not constant all over the city; some parts definitely have better conditions, while others suffer from problems associated with the quality of life; in other words, urban spatial inequality in terms of \u0026nbsp;Ecological-Environmental conditions. In this paper, an objective definition of the quality of environmental or ecological condition in the city, was used as an indicator of quality of life to introduce a new index for measuring urban\u0026nbsp;ecological-environmental spatial inequality based on\u0026nbsp;NDVI tailored for Tehran, an index that measures density and dispersion of green spaces in urban areas of remotely sensed data, and ecological conditions, environmental conditions and quality of the environment are used in the same meaning. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e[1]. See: http://www.mercer.com/home\u003c/p\u003e\n\u003cp\u003e[2]. See http://www.urbanaudit.org/\u003c/p\u003e\n\u003cp\u003e[3]. See http://statistics.tehran.ir/\u003c/p\u003e"},{"header":"2. Urban Green Spaces and Urban Political Ecology","content":"\u003cp\u003eGreen spaces and urban forests have various functions and values in a city (Carreiro et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Van den Berg et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). From a functional point of view, they balance temperature, clean air, etc. They also have aesthetic values (Kong et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and a privacy function (Tyrv\u0026auml;inen \u0026amp; Miettinen, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) as well. Traditionally, urban green spaces bring public parks to mind, but there are other forms of green spaces. They include urban forests and greenness in the city, green spaces in semi-public spaces such as hospitals and governmental buildings, trees along the streets and boulevards, private gardens, small and limited trees, green spaces inside homes, etc. Van den Berg et al (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) show that having a view of trees and forests (e.g., parks) reduces stress, and enjoyment of the landscape can decrease tension and anger, and increase concentration. Laumann et al (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) explain that parks with various plant species cause relaxation in citizens (Chiesura, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Seeing the trees and natural landscape has positive effects on people, including reducing stress, increasing happiness, and decreasing blood pressure (Hartig et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). An old garden with fruit trees and a variety of flowers can lead to mental concentration (Ottosson \u0026amp; Grahn, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother aspect of urban green space and urban forest regarding the complexity of power relations in the urban space is the spatially uneven distribution of these spaces in the city, which is related to urban socioeconomic inequalities (Mitchell \u0026amp; Popham, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Wen et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and spatial segregation (Abercrombie et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Poor people, who do not have enough financial and credential resources to produce and maintain private green spaces, are often not able to gain access to healthy environments. Yet, investments for green space development depend on governmental and public resources, which in turn depend on taxes. In this sense, the ability of low-income people to have access to quality green space is limited. The lack of attention to investment in public urban green spaces in areas where low-income groups live is a source of environmental tensions, affecting their quality of life directly (Heynen, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e(Heynen et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), studied the unequal distribution of urban canopy cover in relation to social, racial, and ethnic inequalities. They consider the role of green spaces and urban forests in urban metabolism from a political urban ecology point of view. Moreover, green spaces have direct effects on the quality of the urban environment and the quality of life of urban populations. Their far-reaching effects in terms of mental, physical, and social domains can be described as stress and violence reduction (Astell-Burt et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Fan et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), enhanced health (Oliveira et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), improved environmental conditions, improving air quality (Bottalico et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Jayasooriya et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), reducing stress, and heat amelioration, increasing land and property values, etc. (Conway et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Heidt \u0026amp; Neef, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe role and effects of social and material production drew the attention of radical geographers (Castells, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Castree, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Gandy, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Grundmann, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1991\u003c/span\u003e; Harvey, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Hughes et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Swyngedouw \u0026amp; Heynen, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDavid Harvey argues that where society begins, nature ends (Harvey, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Urbanization processes and their extensions towards the green space not only cause a social production of urban space, but also a reproduction of the natural space of the city (Fitzsimmons, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1989\u003c/span\u003e). The social production of the natural space of the city also creates specific social and ecological conditions in the city, thereby providing a battlefield for conflicts and competition (Heynen et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). These statements show how urban political ecology is formed. The social production of urban space explains the new dimensions of the production of social-spatial inequalities within cities.\u003c/p\u003e \u003cp\u003eUrban political ecology, as an interdisciplinary area, has its roots in political economy and ecology (Osmond \u0026amp; Pelleri, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It provides a framework for understanding the effects of social structure in an urban environment. This approach aims to consider and study power-laden social, ecological, and political processes that create an uneven social environment. More specifically, it considers social processes, material metabolism, form, and spatial structure of socio-ecological landscape in contemporary cities. These relations and factors are not constant; in fact, they change over scale and time because of their variation across different groups of people at various scales (Swyngedouw \u0026amp; Heynen, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe relation between cities and nature became an arena for intellectual debate for social and environmental theorists (Bookchin, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1978\u003c/span\u003e). According to Lefebvre, urbanization causes the destruction of nature, the reproduction of nature, and the production of a somewhat second nature.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003e\u0026ldquo;Nature, destroyed as such, has already had to be reconstructed at another level, the level of \u0026ldquo;second nature,\u0026rdquo; i.e., the town and the urban. The town, anti-nature or non-nature and yet second nature, heralds the future world, the world of the generalised urban. Nature, as the sum of particularities which are external to each other and dispersed in space, dies. It gives way to produced space, to the urban. The urban, defined as assemblies and encounters, is therefore the simultaneity (or centrality) of all that exists socially.\u0026rdquo;\u003c/em\u003e (Lefebvre, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1967\u003c/span\u003e, P.15)\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eUrban political ecology explicitly explains that physical conditions, including the urban environment, can be manipulated and controlled by urban elites and stakeholders in favor of their interests. Consequently, this action marginalizes some social groups by limiting their access to the urban natural environment. In the long run, both physical and social forms are combined with physical and social structures to produce the urban natural landscape actively. Therefore, each urban element (such as parks, skyscrapers, and natural heritage) is related to social and physical processes that define urban metabolism and social relations within a city (Heynen, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The socio-spatial metabolism of the city, which produces a set of social and physical abilities and disabilities, leads to the formation of regions with opposite tendencies. This issue causes inequalities in different parts of the city. In addition, quality of life, in both physical and social terms, presents relevant disparities across different regions, and consequently. In addition, it causes a deterioration of social and physical conditions by reducing the quality of life and the quality of the urban environment of specific social groups (Heynen et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough from a geographical point of view, capitalism, more specifically neo-liberal capitalism, obeys several behavioral laws. In general, it may be summarized as depending on the development of urban environments as means of production, exchange, and consumption centers (Glaeser et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The interesting point is that capitalistic systems consider the city as the commodification of urban elements. For this reason, the owners of power and wealth tend to have more urban facilities and advantages, such as natural endowments. As a consequence, under these conditions, some urban areas become the centers of deprivation and environmental pollution. Harvey argues that the commodification of urban elements, including urban green spaces and urban forests, is like a precious jewel in consuming capital and assets of a city because urban forests represent an important share of urban space consumption. To sum up, the uneven quality of the built environment is not randomly produced; instead, it can be considered as the product of an unbalanced social system. The theory of urban political ecology convincingly explains the role of creating factors of the urban built environment. This approach was used in this research as a theoretical justification for producing and mapping indicators of ecological (environmental) inequality in the city.\u003c/p\u003e"},{"header":"3. Case Study","content":"\u003cp\u003eTehran has been the capital city of Iran since the foundation of the Qajar dynasty in 1795. Nowadays, Tehran is one of the largest and fastest-growing cities in the world. One of the sharpest features of the city is the north-south socio-spatial divide. The Northern parts tended to display superior characteristics with respect to the Southern ones in terms of accessibility to urban facilities and services (Rabiei-Dastjerdi et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Rabiei-Dastjerdi \u0026amp; Kazemi, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Rabiei-Dastjerdi \u0026amp; Matthews, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), social class (Rabiei-Dastjerdi \u0026amp; Kazemi, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Zad, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2013\u003c/span\u003e); the northern part enjoys better environmental conditions where the rich live and the southern part (the poor area) is suffering from lack of green space problem.\u003c/p\u003e \u003cp\u003eAlthough there have been many attempts to reduce spatial inequality, there is still a north-south socioeconomic disparity. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, a satellite image of the city, clearly shows urban environmental-ecological spatial inequality. This paper maps the uneven quality of the environment based on the geographical distribution of all types of greens; then it introduces an innovative methodology and a new index for measuring environmental-ecological spatial inequality in Tehran.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Measuring Ecological-Environmental Condition","content":"\u003cp\u003eIn this part of the paper, the procedure of mapping green spaces in the city, and extracting a new index based on the green space map for measuring urban ecological-environmental spatial inequality will be explained.\u003c/p\u003e \u003cp\u003eRemotely sensed imagery is an advanced and effective technology for obtaining data and information from the Earth\u0026rsquo;s surface and features. Earth observations are particularly important; however, there are time, financial, and accessibility limitations. Remote sensing has wide and increasing applications not only in natural resource sciences, but also in social sciences and urban studies (Avery \u0026amp; Berlin, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). Recently, these digital images have been used to measure many physical indexes and produce objective maps at different scales. To name a few, there are NDVI (Normalized Difference Vegetation Index), land use/land cover maps and their corresponding change maps, urban heat island (UHI), etc.\u003c/p\u003e \u003cp\u003e(Lo, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) used the Landsat TM image and socioeconomic data to calculate the environmental quality index. He used NDVI, surface temperature, and percentage of urban land use areas, as well as per capita income, population density, median home value, and percentage of university graduates from census data. Principal component analysis was implemented to generate the quality-of-life index. His results showed that this index had a positive correlation with NDVI, per capita income, and median home value. On the contrary, it had a negative correlation with population density, percentage of urban land uses, and surface temperature.\u003c/p\u003e \u003cp\u003eIn addition, satellite images can provide information and data with less effort, less cost, and in a shorter time. To measure greenness and vegetation on the earth, there are several extractable indexes from remote sensing data, such as the Transformed Vegetation Index (TVI), Corrected Transformed Vegetation Index (CTVI), Thiam's Transformed Vegetation Index (TTVI), and NDVI (Bannari et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). The NDVI has received more attention rather than the other indexes. It is calculated according to this equation:\u003c/p\u003e \u003cp\u003e \u003cb\u003eNDVI = (NIR - R) / (NIR\u0026thinsp;+\u0026thinsp;R)\u003c/b\u003e Eq.\u0026nbsp;(1)\u003c/p\u003e \u003cp\u003eWhere \u003cb\u003eNIR\u003c/b\u003e and \u003cb\u003eR\u003c/b\u003e are the near infrared and red spectral bands in the electromagnetic spectrum (Bannari et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1995\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe NDVI is a very easily calculated index that can be extracted from satellite images, although it has its own limitations and must be calibrated for measuring real biomass. Mathematically, this index varies between \u0026minus;\u0026thinsp;1.0 and +\u0026thinsp;1.0; but dense vegetation canopies tend to be between 0.2 and 0.8, clouds and snow areas tend to be in negative values, water bodies stand in low positive ranges and even slightly positive values, and soil present values between 0.1 and 0.2 (Huete, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Qi et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Since varieties of plant species have different growing times and maximum greenness, six Landsat 7 and ETM sensor images, at different times and dates, were selected for mapping green spaces.\u003c/p\u003e \u003cp\u003eTo remove the atmospheric effects on the reflectance values of satellite images, all images must be atmospherically corrected (Rees, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). After atmospheric correction, the image values represented the spectral reflectance for each pixel. Then, NDVI was calculated for each date/image within city borders. Atmospheric correction of images was done as follows. To counter the effects of cloud, atmospheric aerosol, and gases, the image must be corrected. The \u003cem\u003eTop of Atmosphere Reflectance\u003c/em\u003e method using ENVI software was applied. This method consists of two steps. First, all digital numbers (DNs) of the images were converted to the radiance values, and then these radiance values were converted to the reflectance values. For each image, the distance between the Earth and the Sun in astronomical units, the Julian Date (the day of the year), and the solar zenith angle were needed. After each image was atmospherically corrected, an NDVI map was generated for each date. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e is the NDVI for the image (date: 2002-03-02). At this step, the threshold range (0.2\u0026ndash;0.8) was applied to each image to map green spaces at the required time. The green areas show green spaces in the city image. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates the map of the geographical distribution of urban green spaces for the first image (date: March 2nd, 2000). Since different species of green plants and trees have different growing times, they cannot all be detected at once, due to the amount of chlorophyll in their leaves. As a result, one image cannot map all types of green plants. To compensate for this issue, six satellite images in a year with a proper interval time (two months) were used. Then the maximum function was applied to all six urban green space maps to produce the final green map, as follows, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCGSM\u0026thinsp;=\u0026thinsp;Max {Ai}\u003c/b\u003e Eq.\u0026nbsp;(2)\u003c/p\u003e \u003cp\u003e \u003cb\u003eCGSM\u003c/b\u003e: is City Green Spaces Map, and \u003cb\u003eAi\u003c/b\u003e: is the Green-Space Map at Time (i).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis map, which obviously demonstrates the lack of green spaces in Tehran\u0026rsquo;s urban area, was produced to present areas suffering from green space shortages (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"5. A New Index for Measuring Ecological-Environmental Condition","content":"\u003cp\u003eThe effect of green spaces is not limited only to their neighborhood or location; their functions are more far-reaching in the environment, e.g., perceived general health of residents (Maas et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), stressful life events (Van den Berg et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), physical activity and overweight (Coombes et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), mental health (Nutsford et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and even residential property value. However, the farther away a location is from green spaces, the less the effect it would receive from the green spaces in its neighborhood. In other words, the first law of geography is applicable here again: \"Everything is related to everything else, but near things are more related than distant things\" (Tobler, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). For example, in urban planning standards, accessibility to parks and public green spaces is measured by walking distance. Here, a new approach was used because green spaces have different functions for environmental quality, both directly and indirectly, regardless of their accessibility across all dimensions. Green space clears the air, benefits the city and its inhabitants, regardless of ownership, legal issues, and all human-related factors and barriers. The visual and physical access to green spaces can be limited to their owners, but their environmental and biological functions and benefits cannot be assigned only to them. Therefore, green spaces could be measured as a proxy for a quality environment. In doing so, a distance function was implemented to measure distance to green spaces, in order to extrapolate the effects (value) of existing green spaces in the city. The higher values were assigned to places closer to parks and the lower values to locations farther away from them. The values were calculated based on Table\u0026nbsp;2.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssigned Values for Modeling Quality of Environment Based on NDVI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eList\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eType of Area\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eValue Rang\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreen Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Green Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo sum up, the green space index was normalized to map the quality of the environment in the city based on the spatial distribution of green spaces and parks (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This index allows mapping of ecological disparities in the city.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"6. Results and Discussion: Toward the New Index of Quality of Environment","content":"\u003cp\u003eIn this research, the ecological or environmental conditions were mapped based on the urban political ecology framework. These features are extracted from satellite images, NDVI, and land surface temperature, and used as proxies for the ecological dimension of spatial inequality in the city. A greenness map illustrates the highly uneven spatial distribution of green spaces (private, semi-public, and public) in Tehran. On this map, most parts of the city, except the northern part, strongly suffer from a shortage of green spaces. Despite the recent attempts to create public green spaces in southern deprived regions and large urban forests in the northwestern region of the city, there are still shortages of green spaces. A new index of ecological conditions was designed based on the greenness map as well. This index has high potential to be applied in other cities with a similar socio-ecological context and settings.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e is the reclassified map of the quality of the environment extracted from Landsat ETM+. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the condition of the city in terms of the quality of the environment. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e pinpoints a large gap in environmental conditions in different parts of the city.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicates that the majority of people living in Tehran, the sum of the lowest (4 and 5) classes (88 percent of citizens), are suffering from low environmental conditions; in other words, 78 percent of the city area. The third class shows people living at a medium level of environmental conditions, which is only 6 percent of the whole population. The sum of the first row shows that only 6 percent of people enjoy better environmental and ecological conditions. Considering the area of the city based on environmental conditions displaying that most areas of the city are not favorable from an environmental point of view. Finally, this new index and methodology are suggested for other measures of urban spatial and ecological-environmental inequality with similar environmental and socioeconomic conditions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eReclass of the Population and the City Area Based on the Quality of the Environment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArea (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePopulation (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eIn this paper, we studied the environmental-ecological conditions in Tehran and proposed a new index for measuring these conditions at urban scale using satellite images. This methodology seems to be very effective and can provide useful information for urban managers, planners, and researchers due to simplicity, practicability, capability to control for the areal unit problem, being fast and reasonable, a strong connection between theory and real world data, cost, and, of course, a partial solution and ability to control the Modifiable Areal Problem or MAUP (Wong, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) in measuring spatial environmental-ecological indexes. Moreover, using time series analysis based on produced indexes can produce measures for evaluating the performance and consequences of spatial and social policies in the city.\u003c/p\u003e \u003cp\u003eThe results confirmed that the city is facing this challenge, \u003cem\u003espatial inequality\u003c/em\u003e, in terms of environmental-ecological conditions. All produced indexes confirmed the hypothesis that there is a north-south spatial inequality trend in the city. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicates that 88 percent of the population (class 1 and class 2) lives in low environmental and ecological conditions, and only 6 percent of the population lives in better conditions (class 4 and class 5). In addition, the results support the theory of urban political ecology. To sum up, we observed that Tehran is a highly uneven city in terms of environmental-ecological conditions. This index can be used and tested in other cities, at least in Middle Eastern cities, with similar socioeconomic and environmental conditions.\u003c/p\u003e \u003cp\u003eAs spatial inequality is a multidimensional phenomenon in the city, other dimensions of spatial inequality, including accessibility to urban facilities and services and socioeconomic conditions, should be studied to find the relations between all dimensions of spatial inequality. It means that to tackle spatial environmental inequality, we should consider the role and effect of other dimensions and causal factors in producing the urban built environment. Taken together, our results suggest that the proposed index offers a reproducible method of describing ecological\u0026ndash;environmental inequalities across urban space. It enables easier measurement and comparison of differences and can inform more focused and equitable planning decisions. At the same time, it advances existing assessment approaches by integrating several environmental dimensions into a single meaningful measure and provides a substantive basis for further empirical application and critical debate.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbercrombie, L. C., Sallis, J. F., Conway, T. L., Frank, L. D., Saelens, B. E., \u0026amp; Chapman, J. E. (2008). Income and racial disparities in access to public parks and private recreation facilities. \u003cem\u003eAmerican Journal of Preventive Medicine\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(1), 9\u0026ndash;15.\u003c/li\u003e\n \u003cli\u003eAstell-Burt, T., Feng, X., \u0026amp; Kolt, G. S. (2013). 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Spatial disparities in the distribution of parks and green spaces in the USA. \u003cem\u003eAnnals of Behavioral Medicine\u003c/em\u003e, \u003cem\u003e45\u003c/em\u003e(suppl_1), S18\u0026ndash;S27.\u003c/li\u003e\n \u003cli\u003eWeng, Q. (2007). \u003cem\u003eRemote sensing of impervious surfaces\u003c/em\u003e. CRC Press.\u003c/li\u003e\n \u003cli\u003eWong, D. W. (2004). The modifiable areal unit problem (MAUP). In \u003cem\u003eWorldMinds: Geographical perspectives on 100 problems: Commemorating the 100th anniversary of the association of American geographers 1904\u0026ndash;2004\u003c/em\u003e (pp. 571\u0026ndash;575). Springer.\u003c/li\u003e\n \u003cli\u003eZad, V. V. (2013). Spatial discrimination in Tehran\u0026rsquo;s modern urban planning 1906\u0026ndash;1979. \u003cem\u003eJournal of Planning History\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), 49\u0026ndash;62.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Dublin City University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Environmental Conditions, Remote Sensing, Spatial inequality, Normalized Difference Vegetation Index, Tehran","lastPublishedDoi":"10.21203/rs.3.rs-8463200/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8463200/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn recent years, the quality of the urban environment has received more attention in a variety of disciplines such as planning, geography, sociology, health sciences, and many others. In this paper, a new approach is proposed to measure urban environmental spatial inequality based on the geographical distribution of green spaces and the theory of urban political ecology. In this approach, ecological spatial inequality will be defined, modeled, and measured through green spaces extracted from satellite remote sensing observations. Urban political ecology provides a theoretical framework for implementing green spaces extracted from satellite images as a proxy for modeling the built environment conditions in urban areas. A greenness map, represented by the Normalized Difference Vegetation Index (NDVI), illustrates the highly uneven spatial distribution of green spaces, e.g., private, semi-public, and public. The proposed approach has been applied to study and map the urban ecological-environmental spatial inequality in Tehran, the capital city of Iran, and one of the fastest-growing cities in the world. The results show that most parts of the city and the majority of the population are suffering from spatial inequality in terms of Ecological-Environmental conditions. This new index has high potential to be applied in other cities with a similar socio-ecological context and spatial settings.\u003c/p\u003e","manuscriptTitle":"A New Index for Measuring Urban Ecological-Environmental Spatial Inequality","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-08 14:00:35","doi":"10.21203/rs.3.rs-8463200/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2715bf51-e925-4c34-a720-b578e7f3fb3e","owner":[],"postedDate":"January 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":60280603,"name":"Urban Studies"},{"id":60280604,"name":"City Management and Urban Policy"},{"id":60280605,"name":"Environmental Policy"},{"id":60280606,"name":"Geographic Information Systems"},{"id":60280607,"name":"Sociology"}],"tags":[],"updatedAt":"2026-01-08T14:00:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-08 14:00:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8463200","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8463200","identity":"rs-8463200","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}