Modeling an Indian megalopolis– A case study on adapting SLEUTH urban growth model

Chaudhuri, Gargi; Clarke, Keith

doi:10.1016/j.compenvurbsys.2019.101358

Cited by 39 publications

(28 citation statements)

References 87 publications

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“…Four scales were used to generate density variables: 150, 300, 600, and 1200 m. However, high multicollinearities (>0.5) among different scales were detected for the respective density factors. Existing literature and urban simulation models have widely indicated that the possibility of urban growth at one site is distinctly attributed to local neighborhood conditions [9][10][11]. Moreover, considering that a 5 × 5 focal window size (i.e., 150 m) is commonly applied in CA models and as an attribute setting for neighborhood conditions [9,10], we used guidance from existing literature to generate density variables of 150 m for our analysis.…”

Section: Landsat 5 Thematic Mapper (Tm) Imagery Acquired In 1985 Andmentioning

confidence: 99%

“…Due to urgent social and environmental issues resulting from rapid urbanization including overcrowding [4], urban heat island effects [5], air pollution [6], and ecosystem degradation [7], ample scholarly research has sought to understand the driving factors of urban growth for cities all over the world. Contemporary studies approach this topic from a number of methodological angles, most of which fall into one or both of two broad categories: (1) urban simulation models (e.g., [8][9][10][11][12][13]) and (2) empirical models (e.g., [14]).…”

Section: Introductionmentioning

confidence: 99%

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Global and Local Modeling of Land Use Change in the Border Cities of Laredo, Texas, USA and Nuevo Laredo, Tamaulipas, Mexico: A Comparative Analysis

Zhao

Jensen

Weaver

2020

Land

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This paper estimates global logistic regression and logistic geographically weighted regression (GWR) models of urban growth in the adjacent border cities of Laredo, Texas in the United States and Nuevo Laredo, Tamaulipas in Mexico, for two time periods from 1985 to 2014. Historical land use and land cover patterns were monitored through Landsat imagery from the United States Geological Survey to identify instances of urban growth through land type change. Data on socioeconomic variables related to urban growth were collected from various sources and used as independent variables. In both time periods, the logistic GWR was proven to be a complementary model for the global logistic regression to explore the urban growth effect. In addition, GWR outperformed the global logistic regression model with respect to goodness of fit. These results suggest that local models are complementary to global models to empirically analyze the determinants of urban growth in study areas that contain political borders, presumably because the relationships between socioeconomic factors and urban growth are characterized by spatial heterogeneity in such areas. The spatial variable of the relationship between urban growth and the neighborhood interactions and proximity effect present the idea of complexity and interconnections between the land use change and associated factors.

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Section: Landsat 5 Thematic Mapper (Tm) Imagery Acquired In 1985 Andmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Global and Local Modeling of Land Use Change in the Border Cities of Laredo, Texas, USA and Nuevo Laredo, Tamaulipas, Mexico: A Comparative Analysis

Zhao

Jensen

Weaver

2020

Land

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“…Despite a fruitful line of research in analyzing ESP, there seems to be a lack of ESP application, particularly in incorporating ESP into urban growth simulation [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 15 , 16 , 17 , 18 , 19 , 23 , 24 , 25 ]. On one hand, most ESP-related studies have focused on ESP identification and construction.…”

Section: Introductionmentioning

confidence: 99%

“…On the basis of the mechanism of cellular automata, a diverse range of models have been developed and improved to simulate and predict future urban growth over the past few decades [ 23 ]. Among these, the SLEUTH model has been widely applied due to its comprehensive evaluation and high accuracy [ 23 , 24 , 25 ]. SLEUTH is an acronym made up of its input datasets from six dimensions, namely, slope, land use/land cover (LULC), exclusion, urban extent, transportation, and hill-shade.…”

Section: Introductionmentioning

confidence: 99%

“…Utilizing the input datasets, the SLEUTH model sets out five growth parameters (i.e., diffusion, breed, spread, slope resistance, and road gravity) and four growth types (i.e., spontaneous growth, new spreading center growth, edge growth, and road-influenced growth) to refine the calibration and finalize the urban growth prediction [ 26 , 27 ]. In building the exclusion layer, water bodies, wetlands, and reserved forest have mostly been used in previous studies, while, factors related to ecological security are scarcely mentioned [ 23 , 24 , 25 , 26 , 28 , 29 ]. As a matter of fact, it is evident that ESP covers a much larger extent than the conservation area [ 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

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Simulating Urban Growth Scenarios Based on Ecological Security Pattern: A Case Study in Quanzhou, China

Liu

Wei

Jia

2020

IJERPH

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In recent decades, the ecological security pattern (ESP) has drawn increasing scientific attention against the backdrop of rapid urbanization and worsening ecological environment. Despite numerous achievements in identifying and constructing the ecological security pattern, limited attention has been paid on applying ESP to predict urban growth. To bridge the research gap, this paper took Quanzhou, China as a study case and incorporated the identified ESP into an urban growth simulation with three distinct scenarios. Following the “ecological source–ecological corridor–ecological security pattern” paradigm, the ESP identification was carried out from four single aspects (i.e., water, geology, biodiversity, and recreation) into three levels (i.e., basic ESP, intermediate ESP, and optimal ESP). Grounded in an equally weighted superposition algorithm, the four single ESPs were combined as an integrated ESP (IESP) with three levels. Taking IESP as an exclusion element, urban growth simulation in 2030 was completed with thee SLEUTH model. Drawing on the three levels of IESP, our urban growth simulation contained three scenarios. In terms of urban sprawl distribution coupled with urban growth rate, an optimal urban growth scenario is recommended in this paper to balance both urban development and eco-environment protection. We argue that our ESP-based urban growth simulation results shed new light on predicting urban sprawl and have the potential to inform planners and policymakers to contribute to more environmentally-friendly urban development.

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Management Strategy for Indian Housing Development Waste

Singh¹,

Jagun²,

Daud³

et al. 2022

Lecture Notes in Civil Engineering

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Modeling an Indian megalopolis– A case study on adapting SLEUTH urban growth model

Cited by 39 publications

References 87 publications

Global and Local Modeling of Land Use Change in the Border Cities of Laredo, Texas, USA and Nuevo Laredo, Tamaulipas, Mexico: A Comparative Analysis

Global and Local Modeling of Land Use Change in the Border Cities of Laredo, Texas, USA and Nuevo Laredo, Tamaulipas, Mexico: A Comparative Analysis

Simulating Urban Growth Scenarios Based on Ecological Security Pattern: A Case Study in Quanzhou, China

Management Strategy for Indian Housing Development Waste

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