Analysis of the Inequality of Spatial Distribution of Administrative-Disciplinary Services via the Spatial Justice Approach (Case Study: Isfahan Neighborhoods)

Extended abstract:Introduction: Following the increasing expansion of cities and urban population, the demand for urban services is also increasing. One of the important services in cities is administrative service that meets the citizens’ daily needs. This type of service has been established by ministries and central organizations with the increase of the number of cities and urban population and consequently, the increase of citizens' service needs. On the other hand, fair and adequate distribution of disciplinary enforcement centers has an effective role in establishing security and tranquility in cities. Therefore, it is necessary to accurately identify the current situation in this field in order to create a more appropriate and equitable distribution of administrative-disciplinary spaces that are needed by today's societies. In this regard, the purpose of this article was to evaluate the spatial pattern of administrative-disciplinary services in Isfahan so as to achieve the effect of the administrative model of administrative-disciplinary services on the desirability of the functional radius of these services and assess the relationship between the spatial distribution of administrative-disciplinary services and population in the related areas. Methodology: This study was of an applied type based on the purpose and a descriptive-analytical research in nature and method. Data collection was based on the library method. After collecting the basic information and data, the spatial distribution of administrative-disciplinary enforcement services was firstly modeled by using the nearest neighborhood analysis method, local Moran index, global Moran index, and hot-spot analysis in Arc GIS software environment. Then, the effect of the spatial distribution pattern of these services on the desirability of their functional radius was evaluated in the same software by using fuzzy membership function. In the next step, by drawing the map of Isfahan neighborhoods in GeoDa software, the spatial autocorrelation of the variable population of Isfahan with the distribution of ​​administrative-disciplinary services in its neighborhoods was determined and analyzed by using Moran’s bivariate index.Discussion: The analysis of the nearest neighborhood showed that the administrative-disciplinary enforcement services in Isfahan were randomly distributed. According to the calculations of the global Moran coefficient, the administrative-disciplinary enforcement services were distributed in clusters in the neighborhoods with a probability of 99%. By calculating the local Moran for the neighborhoods of Isfahan, it was found that 3 neighborhoods in District 13 were significantly located at the High-High clustering level, which indicated establishment of the neighborhoods with more administrative-disciplinary enforcement services nearby and in clusters. One neighborhood in District 10 and one in District 14 were located at the High-Low level. These neighborhoods had a large number of administrative-disciplinary enforcement services, while being surrounded by less record-breaking neighbors. 3 neighborhoods in District 13, which were located at the Low-High clustering level, faced the lack of access to these services, while being adjacent to the neighborhoods with a better access. Other neighborhoods did not have a significant autocorrelation. According to the maps drawn through the hot-spot analysis, the neighborhoods and central areas, especially areas 1, 3, 5, and 6, had formed hot spots and moved to the outskirts of the city due to their high administrative-disciplinary services, especially area 9 and the northeast part of the city. Also, cold spots were forming, which indicated the lack of administrative-disciplinary enforcement services in these neighborhoods. Assessing the effectiveness of the spatial distribution model of these services on the desirability of the functional radius demonstrated the desirability of their functional radius in the central regions, as well as unfavorable areas and neighborhoods around the city. The desirability of the functional radius was in favor of the center but had caused a detriment to the surroundings. Moran’s bivariate index was applied to measure and evaluate the spatial autocorrelation, which showed very low probability of the spatial distribution of administrative-disciplinary enforcement services based on the variable population with low significance. Conclusion: In general, the results indicated that the spatial distribution of administrative-disciplinary enforcement services in the neighborhoods of Isfahan City was inappropriate in a way that the desirability of access to these services in the central areas was very high, while citizens in the suburbs were facing lack of access to these services. Therefore, it is necessary to consider programs and policies that eliminate this major spatial gap and establish spatial justice in the neighborhoods of Isfahan and ultimately social justice to cover the entire city. According to David Harvey, it is advisable to give extra services to the groups in need because they do not have a history of using these services and are not thus accustomed to them. This is especially true of municipal services for very poor groups, new immigrants, and the like. Hence, entitlement to the geographical framework would be allocation of additional resources to compensate for the social and natural problems of each region. Keywords: spatial justice, spatial distribution, administrative-disciplinary services, Isfahan neighborhood References- Ardeshiri, Ali, Ken Willis & Mahyar Ardeshiri (2018). Exploring preference homogeneity and heterogeneity for proximity to urban, public services, Cities, pp 1–13.- Boyne. A., Georg, Martin A. Powell (2002). Territoial Justice Spatial Justice and Local covernment Finance, University of Herhordshire & university of clamorgan.- Delbosec, A. and G., Currie (2011). Using Lorenz curves to assess public transport equity, Journal of Transport Geography, 19(6), 1252-1259.- Deniz, A. (2012). Measuring the satisfaction of citizens for the services given by the municipality: the case of Kirsehir municipality. Procedia Social and Behavioral Sciences, 32(24).- Dutta, v (2012). War on the Dream, How Land use Dynamic and Sprawling City Devour the Master Plan and Urban Suitability. A Fuzzy Multi-Criteria Decision-Making Approach, proceeded in 13th Global Development Conference Urbanisatio and Development: Delving Deeper into the Nexus, Budapest, hungary.- Getis Arthur, (2005). Spatial Pattern Analysis, Encyclopedia of Social Measurement, Volume 3.- Godillon, S (2011). Urban renewal – a vehicle for spatial justice in the face of traffic safety problems, js.1-10.- Harvey, David (1935). "Social Justice and the City", the translator: Farokh. Hesamyan and Mohammad Reza Haeri and Behrouz monadi zadeh, the company processing and urban planning, Winter 1997, page 271.- Herrera, F., & Herrera-Viedma, E. (2002). «Linguistic decision analysis: steps for solving decision problems under linguistic information», Fuzzy Sets and Systems, 115, 67–82.- Langford, M., Higgs, G., Radcliffe, J. While, S. (2008). Urban Population Distntution Models and Service Accessibility Estimation Compuers Environment and Urban System.- Laurent E (2011). Issues in environmental justice within the European Union, Ecological Economics, No. 70, 1846–1853.- Liao, Chin-Hsien, Chang, Hsueh-Sheng, Tsou, Ko-Wan (2009). Explore the spatial equity of urban public facility allocation based on sustainable development viewpoint, 14th International Conference on Urban Planning and Regional Development in the Information Society, Spain: Sitges, p 137-145.- Lorestani A., Yaghoubpour Z., Shirzadian R. (2016). Analysis of spatial distribution of Tehran Metropolis urban services using models of urban planning, Capital Urban Manage., 1(2). Pp 83-92.- Mitchel, G. and Norman, P. (2012). longitudinal environmental justice analysis: Co-evolution of environmental quality and deprivation in England, 1960–2007. Geoforum, No. 43, pp: 44-57.- Parry, Jahangeer A., Showkat A. Ganaie & M. Sultan Bhat (2018). GIS based land suitability analysis using AHP model for urban services planning in Srinagar and Jammu urban centers of J&K, India, Journal of Urban Management 7, pp 46-56.- Sohel Rana M. D (2009). Status of water use sanitation and hygienic condition of urban slums: A study on Rupsha Ferighat slum, Khulna", www.elsevier.com, pp. 322-328.- Tirband, Majid and Azani, Mehri (2012). Distribution of facilities and municipal services based on social justice, case study: Yasouj city, Journal of applied sociology, Issue 23, No46, p: 109-138.- Wiesel, Ilan, Liu Fanqi and Buckle Caitlin (2017). Locational disadvantage and the spatial distribution of government expenditure on urban infrastructure and services in metropolitan Sydney (1988–2015), Geographical Research, pp 1-13.- windner, Robert. (2009). Planning law primer, basics of variances planning commission journal. N6, p30-47.- Zhang Chaosheng, Lin Luo, Weilin Xu & Valerie Ledwith, (2008). Use of local Moran's I and GIS to identify pollution hotspots of Pb in urban soils of Galway, Ireland , Science of The Total Environment, Volume 398, Issues 1-3. Figures:- Figure 1: Map of the political situation of Isfahan in the city, province and country- Figure 2: Map of the central feature and directional distribution of administrative- disciplinary services in neighborhoods and areas of Isfahan- Figure 3: The pattern of distribution of administrative- disciplinary services in Isfahan city using the average nearest neighborhood analysis- Figure 4: The pattern of distribution of administrative- disciplinary services in the neighborhoods of Isfahan using Moran index- Figure 5: Spatial autocorrelation of Isfahan neighborhoods from the perspective of having administrative-disciplinary services- Figure 6: Analysis of hot and cold spots in neighborhoods of Isfahan from the perspective of administrative-disciplinary- Figure 7: Analysis of the desirability of the functional radius of administrative-disciplinary services in Isfahan based on the fuzzy membership method- Figure 8: Spatial autocorrelation diagram (local Moran) between of the population and the area of ​​ administrative- disciplinary services in Isfahan neighborhoods- Figure 9: Spatial autocorrelation map between the population and the area of ​​ administrative- disciplinary services in Isfahan neighborhood

Espaço geográfico e complexidade: modelação do crescimento das áreas construídas na aglomeração de Lisboa

Tese apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em Geografia e Planeamento Regional, Especialidade em Novas Tecnologias em GeografiaA reflexão apresentada procura demonstrar que a teoria da Complexidade pode trazer novas abordagens de análise e de actuação na Geografia. Assim, a análise e modelação do crescimento das áreas construídas, na aglomeração de Lisboa, entre 1960 e 2004, envolveu uma primeira fase de experimentação e análise dos dados, na qual foi possível identificar três propriedades dos sistemas complexos: a não linearidade, a auto-organização e o comportamento fractal. Numa segunda fase, foi desenvolvido um modelo de classificação de tipologias de crescimento das áreas construídas, com base na análise multi-fractal. A modelação destas tipologias permitiu lançar algumas questões, sobre a pertinência dos actuais instrumentos de planeamento territorial, face aos comportamentos esperados para os quais o modelo apont