Modeling spatial variations of urban growth patterns in Chinese cities: The case of Nanjing

Luo, Jun; Wei, Yehua Dennis

doi:10.1016/j.landurbplan.2008.11.010

Cited by 271 publications

(192 citation statements)

References 39 publications

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“…In general, slope and elevation are acknowledged as the most important topographic factors that affect urban growth (Braimoh & Onishi, 2007;Reilly, O'Mara, & Seto, 2009;Ye, Zhang, Liu, & Wu, 2013). For socioeconomic factors, proximity factors such as distance to road (Luo & Wei, 2009;Müller et al, 2010;Poelmans & Rompaey, 2009), distance to socioeconomic center (Vermeiren, Rompaey, Loopmans, Serwajja, & Mukwaya, 2012) and distance to water (Cheng & Masser, 2003;Luo & Wei, 2009) are crucial influential factors that determine urban growth. Roads and socioeconomic centers always play a significant role in urbanization as they provide residents higher accessibility to daily needs and resources.…”

Section: Selection Of Variablesmentioning

confidence: 99%

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Wang

Maduako

2018

European Journal of Remote Sensing

106

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An accurate information on the amount and location of Land use and land cover (LULC) changes is necessary to develop and implement a sustainable-urban planning.This research investigates the potential of an integrated Multi-Layer Perceptron and Markov Chain Analysis (MLP-MCA) to map and accurately predict the future LULC change scenarios in Lagos Metropolitan Region of Nigeria. Multi-temporal LULC datasets derived from remotely sensed Landsat images from 1984, 2000 and 2015 were used for modeling, validation and prediction. Predicted LULC changes for 2030 and 2050 were performed based on the LULC map of 2015 using MLP-MCA method. The result reveals a significant expansion of built-up areas during the whole study period. Analysis of LULC distribution in Lagos metropolitan region shows that about 50% of urban land expansion happened beyond the administrative boundary of Lagos State during the period of 2000-2015. It is predicted that more than 75% of future urban growth will occur across the border of Lagos State, in the neighbouring Ogun State by 2050. These results imply that a strong and consistent collaboration between different states is crucial to establish an effective regional planning framework and ensure a proper planned growth of the metropolitan region.ARTICLE HISTORY

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Section: Selection Of Variablesmentioning

confidence: 99%

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Wang

Maduako

2018

European Journal of Remote Sensing

106

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“…The image for urban land expansion has 2318 × 2059 pixels, a huge dataset that is difficult to handle, and a proper sampling method is required. To reduce the spatial dependence and ensure that the sample represents the population, we used a spatial sampling method combining systematical sampling and random sampling [8,24]. First, we extracted regularly spaced points with a 10-pixel (300 m) interval from the nonurban areas in the 1991 image.…”

Section: Land Use Data Samplingmentioning

confidence: 99%

“…However, the rapid urbanization in China is also accompanied by arable land loss, landscape fragmentation, and sustainability challenges [1,5,6]. Many efforts have been made to analyze the complex pattern of urban land expansion and understand the underlying factors [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal Dynamics and Spatial Determinants of Urban Growth in Suzhou, China

2017

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This paper analyzes the spatiotemporal dynamics of urban growth and models its spatial determinants in China through a case study of Suzhou, a rapidly industrializing and globalizing city. We conducted spatial analysis on land use data derived from multi-temporal remote sensing images of Suzhou from 1986 to 2008. Three urban growth types, namely infilling, edge-expansion, and leapfrog, were identified. We used landscape metrics to quantify the temporal trend of urban growth in Suzhou. During these 22 years, Suzhou's urbanization changed from bottom-up rural urbanization to city-based top-down urban expansion. The underlying mechanism changed from TVE (town village enterprise) driven rural industrialization to FDI (foreign direct investment) driven development zone fever. Furthermore, we employed both global and local logistic regressions to model the probability of urban land conversion against a set of spatial variables. The global logistic regression model found the significance of proximity, neighborhood conditions, and socioeconomic factors. The logistic geographically weighted regression (GWR) model improved the global regression model with better model goodness-of-fit and higher prediction accuracy. More importantly, the local parameter estimates of variables enabled us to exam spatial variations of the influences of variables on urban growth in Suzhou.

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“…GWR was introduced to the geographical and spatial econometric literature by Brunsdon et al in 1996, formalised by Fotheringham et al in 2002, later by Charlton and Fotheringham (2009 and extended by Nakaya et al (2009). This technique subsequently has received considerable attention in recent years to model spatially varying relationships between dependent and an explanatory variables in real estate and various other fields including ecology (for example, Wang et al, 2005), urban structure (for example, Luo and Wei, 2009;Mohd Shariff and Rainis, 2009), land use change (for example, Hanham et al, 2009;Wang et al, 2011) and political geography (for example, Calvo and Escolar, 2003). However, since this paper focuses on real estate, the discussion in this section will be concentrating on the applications of GWR technique in the relevant research areas.…”

Section: Geographically Weighted Regression (Gwr) Approachmentioning

confidence: 99%

Does Accessibility to the Central Business District (CBD) Have an Impact on High-Rise Condominium Price Gradient in Kuala Lumpur, Malaysia?

Dziauddin¹,

Misran²

2016

SHS Web of Conferences

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This paper uses a spatial econometric method known as Geographically Weighted Regression (GWR) to investigate the impact of accessibility to the CBD on the high-rise condominium price gradient in Kuala Lumpur, Malaysia. Using a GWR method, after having controlled other factors, this study clearly reveal the impact of accessibility to the CBD on high-rise condominium varying prices across the study area, having a much larger positive impact in some areas but less and counterintuitive impact in others. In general, the results from this study show accessibility to the CBD measured by the travel times does affect high-rise condominium prices (high-rise condominium prices decrease as travel times to the CBD increase) in most part of the areas, hence proved Alonso, Muth and Mills were still right.

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Modeling spatial variations of urban growth patterns in Chinese cities: The case of Nanjing

Cited by 271 publications

References 39 publications

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Spatiotemporal Dynamics and Spatial Determinants of Urban Growth in Suzhou, China

Does Accessibility to the Central Business District (CBD) Have an Impact on High-Rise Condominium Price Gradient in Kuala Lumpur, Malaysia?

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