A spatial zoning approach to calibrate and validate urban growth models

Kazemzadeh-Zow, Ali; Shahraki, Saeed Zanganeh; Salvati, Luca; Samani, Najmeh Neysani

doi:10.1080/13658816.2016.1236927

Cited by 88 publications

(46 citation statements)

References 56 publications

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“…Compact urban expansion, population decline and urban de-concentration were finally assessed using the analytical approach proposed in this study.peri-urban landscapes [13]. Metropolitan areas in Europe have undergone changes in both structure and functions reflecting sequential cycles of compact and dispersed urbanization [14][15][16].The inherent differences in urbanization patterns and processes across countries make the identification of spatio-temporal dynamics of urban change progressively more difficult when considering the effects and consequences of exurban development [17][18][19][20]. Based on the intrinsic nature of societies and economic systems, recent transformations from mono-centric to polycentric structures have attracted rising attention among the social sciences [21][22][23][24].…”

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confidence: 99%

Urban Growth and Demographic Dynamics in Southern Europe: Toward a New Statistical Approach to Regional Science

et al. 2018

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Metropolitan growth in Europe has resulted in drastic changes of urban forms, socio-spatial structures and land-use patterns due to sequential processes of urbanization, suburbanization and re-urbanization. To assess latent shifts from mono-centric models towards more disarticulated and decentralized settlement configurations, the present study evaluates spatio-temporal patterns of growth between the 1920s and the 2010s in three Mediterranean cities with different structure and functions (Barcelona: compact and moderately polycentric; Rome: dispersed, medium-density; Athens: mono-centric, hyper-compact). To identify and characterize long-term urban transformations, an original approach was illustrated in this study, based on a multivariate analysis of 13 indicators resulting from descriptive statistics and linear regression modeling the relationship between population density and distance from inner cities. The empirical results of this study indicate that Barcelona, Rome and Athens have experienced different urbanization cycles, characterized by a (more or less) concentrated distribution of population along urban gradients. Despite similarities in demographic dynamics and planning practices, these processes have determined (i) a mostly centralized growth in Barcelona, (ii) a relatively dispersed and discontinuous spatial structure in Rome, and (iii) a steep decline of population density with the distance from downtown Athens. Compact urban expansion, population decline and urban de-concentration were finally assessed using the analytical approach proposed in this study.peri-urban landscapes [13]. Metropolitan areas in Europe have undergone changes in both structure and functions reflecting sequential cycles of compact and dispersed urbanization [14][15][16].The inherent differences in urbanization patterns and processes across countries make the identification of spatio-temporal dynamics of urban change progressively more difficult when considering the effects and consequences of exurban development [17][18][19][20]. Based on the intrinsic nature of societies and economic systems, recent transformations from mono-centric to polycentric structures have attracted rising attention among the social sciences [21][22][23][24]. The identification of mono-centric and polycentric patterns of growth has benefited from a broad range of approaches derived from different disciplines [5,[25][26][27]. Being an explicit target of the European Spatial Development Perspective [28], polycentrism in Europe has influenced forms of human settlements and socio-spatial structures altering the short-and medium-term dynamics of economic activity [29][30][31][32].Until the early 1990s, large metropolitan areas in Mediterranean Europe have been frequently considered as regions with structurally compact urban forms and functionally monocentric spatial organizations [33][34][35]. Leontidou [36] highlighted similarities in the individual trajectories of urban growth, leading to convergent socio-spatial profiles and homogeneous economic struc...

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confidence: 99%

Urban Growth and Demographic Dynamics in Southern Europe: Toward a New Statistical Approach to Regional Science

et al. 2018

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“…Empirical studies are still required to ascertain latent relationships between population dynamics and re-urbanization processes, discussing the role of social changes-including (but not limited to) aspects of social segregation, immigration, gentrification, and transformation of traditional family structures [22,[32][33][34]. In these regards, Haase et al [35] argued that re-urbanization "relates more to city-mindedness as a housing preference rather than to the actual return of suburbanites to the city".…”

Section: Introductionmentioning

confidence: 99%

“…Empirical evidence for re-urbanization has recently been documented in Europe [13][14][15][16], with inner cities re-attracting populations and suburbs experiencing demographic stability or moderate decline [17][18][19]. Together with the long-term demographic transitions and short-term effects of the 2007 economic recession, different factors were demonstrated to contribute to re-urbanization, depending on local conditions [20][21][22] that have determined spatial heterogeneity in population growth rates [23]. In these regards, drivers of re-urbanization include (i) rehabilitation and renewal of inner districts of central cities through re-development projects ameliorating the condition of housing, public spaces, and transportation; (ii) a (more or less) rapid decline in house prices; (iii) the rising cost of transportation from peri-urban areas to inner cities; (iv) changes in the economic structure with the expansion of high-tech, finance, and business sectors; and finally, (v) a generalized attitude toward urban lifestyles induced by demographic changes, including the increase of mono-nuclear families [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Toward a New Cycle: Short-Term Population Dynamics, Gentrification, and Re-Urbanization of Milan (Italy)

2018

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Abstract:After sequential cycles of urbanization and suburbanization, European cities underwent a (more or less intense) re-urbanization wave. The present study analyzes short-term population dynamics in the core of a large metropolitan region (Milan, northern Italy), providing evidence of spatially-heterogeneous re-urbanization characterized by spatially-complex population growth (or shrinkage) at a local scale. Population dynamics over 1999-2017 were assessed in 88 urban districts partitioning Milan s municipal area and projected up to 2036 for the same spatial units. Empirical results identify spatially-complex and temporally non-linear dynamics with expanding or declining districts distributed heterogeneously across the study area. Multivariate analysis outlines a generalized population decline during 1999-2008 and an opposite pattern afterward (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017), with spatially-homogeneous population expansion expected in the near future. Spatial analysis finally highlights that local-scale population growth rates were more clustered in 2008-2017 than in 1999-2008. While the population decreased continuously in the inner districts (<1 km from the city centre), sub-central districts (1-5 km far from the city centre) experienced mixed patterns of population growth and stability. These results confirm the relevance of local-scale policies managing urban renewal and rehabilitation and promoting metropolitan expansion in a spatially-coordinated manner.

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“…The results of this study indicate that like similar studies, the definitions of non-stationary transition rules can lead to improvements in simulation performance. Some improvements can be made by implementing a zoning approach [24,26]; however, in this study, a local SVM model was developed to estimate the probability of urban development over a continuous surface to avoid discretisation issues. In addition, the improvement in simulation performance attained through integrating the local and global SVMs is another unique aspect of this study.…”

Section: Discussionmentioning

confidence: 99%

“…Employing local models can improve the performance of dynamic simulations of land use change, and the definition of non-stationary transition rules in local CA models has led to improvements in urban growth predictions [24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Integration of Local and Global Support Vector Machines to Improve Urban Growth Modelling

Mirbagheri

Alimohammadi

2018

IJGI

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Abstract:The use of local information for the classification and modelling of spatial variables has increased with the application of statistical and machine learning algorithms, such as support vector machines (SVMs). This study presents a new local SVM (LSVM) model that was developed to model the probability of urban development and simulate urban growth in a subregion in the southwestern suburb of the Tehran metropolitan area, Iran, for the periods of 1992-1996 and 1996-2002. Based on the focal training sample, the model was calibrated using the cross-validation method, and the optimal bandwidth was determined. The results were compared with those of a nonlinear global SVM (GSVM) model that was calibrated based on the ten-fold cross-validation method. This study then evaluated an integrated SVM model (LGSVM) obtained based on a weighted combination of the local and global urban development probabilities. A comparison of the probability maps showed a higher accuracy for the LGSVM than for either the LSVM or GSVM model. To assess the performance of the LSVM, GSVM and LGSVM models in the simulation of urban growth, probability maps were employed as the transition rules for urban cellular automata. The results show that a trade-off between local and global SVM models can enhance the performance of urban growth modelling.

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A spatial zoning approach to calibrate and validate urban growth models

Cited by 88 publications

References 56 publications

Urban Growth and Demographic Dynamics in Southern Europe: Toward a New Statistical Approach to Regional Science

Urban Growth and Demographic Dynamics in Southern Europe: Toward a New Statistical Approach to Regional Science

Toward a New Cycle: Short-Term Population Dynamics, Gentrification, and Re-Urbanization of Milan (Italy)

Integration of Local and Global Support Vector Machines to Improve Urban Growth Modelling

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