Land use changes modelling using advanced methods: Cellular automata and artificial neural networks. The spatial and explicit representation of land cover dynamics at the cross-border region scale

Basse, Reine Maria; Omrani, Hichem; Charif, Omar; Gerber, Philippe; Katalin, Bodis

doi:10.1016/j.apgeog.2014.06.016

Cited by 212 publications

(122 citation statements)

References 63 publications

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“…Therefore, the integrated modeling approaches are widely used for LULC change simulation and projection to overcome the limitations of individual models (Al-Sharif & Pradhan, 2015;Basse, Omrani, Charif, Gerber, & Bódis, 2014;Guan et al, 2011;Mishra, Rai, & Mohan, 2014).…”

Section: Introductionmentioning

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

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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: Introductionmentioning

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

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“…This research tries to analyse the model responses and behaviours with respect to the changes of neighbourhood sizes and types. The most famous neighbourhoods used in UCA models are Von Neumann (Basse et al 2014), rectangular -Moore, and circular neighbourhoods. In this study the rectangular and circular neighbourhood types (Figure1) were chosen in order to evaluate the effects of neighbourhood's type on simulation results.…”

Section: Spatial Filter Issue In Land-use Modellingmentioning

confidence: 99%

Impact of Spatial Filter on Land-Use Changes Modelling Using Urban Cellular Automata

Omidipoor¹,

Samani²

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Urban cellular automata is used vastly in simulating of urban evolutions and dynamics. Finding an appropriate neighbourhood size in urban cellular automata modelling is important because the outputs are strongly influenced by input parameters. This paper investigates the impact of spatial filters on behaviour and outcome of urban cellular automata models. In this study different spatial filters in various sizes including 3*3, 5*5, 7*7, 9*9, 11*11, 13*13, 15*15 and 17*17 cells are used in a scenario of land-use changes. The proposed method is examined changes in size and shape of spatial filter whereas the resolution was kept fixed. The implementation results in Ahvaz city demonstrated that KAPPA index is changed in different shapes and types at the time when different spatial filters are used. However, circular shape with size of 5*5 offers better accuracy.

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“…The changes in urban development over time can be evaluated by using these land use maps. Since land use change is mainly due to human activities and natural factors, twelve spatial variables (normalized into the range [0, 1]) were adopted in light of previous studies [41,50,69]. A detailed description of them is provided in Table 2.…”

Section: Simulating the Spatial Impacts Of Line R2 On Its Surroundingmentioning

confidence: 99%

Simulating and Predicting the Impacts of Light Rail Transit Systems on Urban Land Use by Using Cellular Automata: A Case Study of Dongguan, China

Lin

Chen²,

Han

2018

Sustainability

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Abstract:The emergence of Light Rail Transit systems (LRTs) could exert considerable impacts on sustainable urban development. It is crucial to predict the potential land use changes since LRTs are being increasingly built throughout the world. While various land use and land cover change (LUCC) models have been developed during the past two decades, the basic assumption for LUCC prediction is the continuation of present trends in land use development. It is therefore unreasonable to predict potential urban land use changes associated with LRTs simply based on earlier trends because the impacts of LRT investment may vary greatly over time. To tackle this challenge, our study aims to share the experiences from previous lines with newly planned lines. Dongguan, whose government decided to build LRTs around 2008, was selected as the study area. First, we assessed the impacts of this city's first LRT (Line R2) on three urban land use types (i.e., industrial development, commercial and residential development, and rural development) at different periods. The results indicate that Line R2 exerted a negative impact on industrial development and rural development, but a positive impact on commercial and residential development during the planning stage of this line. Second, such spatial impacts (the consequent land use changes) during this stage were simulated by using artificial neural network cellular automata. More importantly, we further predicted the potential impacts of Line R1, which is assumed to be a newly planned line, based on the above calibrated model and a traditional method respectively. The comparisons between them demonstrate the effectiveness of our method, which can easily take advantage of the experiences from other LRTs. The proposed method is expected to provide technical support for sustainable urban and transportation planning.

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Land use changes modelling using advanced methods: Cellular automata and artificial neural networks. The spatial and explicit representation of land cover dynamics at the cross-border region scale

Cited by 212 publications

References 63 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

Impact of Spatial Filter on Land-Use Changes Modelling Using Urban Cellular Automata

Simulating and Predicting the Impacts of Light Rail Transit Systems on Urban Land Use by Using Cellular Automata: A Case Study of Dongguan, China

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