Accuracy assessments of land use change simulation based on Markov-cellular automata model

Wang, S.Q.; Zheng, Xinqi; Zang, Xiaobing

doi:10.1016/j.proenv.2012.01.117

Cited by 144 publications

(57 citation statements)

References 7 publications

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“…Therefore, the predicted LULC map of 2015 was compared with the observed LULC map of 2015 using kappa index statistics (Kamusoko et al, 2009;Wang, Zheng, & Zang, 2012). The kappa index includes kappa for no information (K no ), kappa for grid cell level location (K location ) and kappa for stratum-level location (K locationStrata ) in addition to kappa standard (K standard ) which is equivalent to kappa (Cohen, 1960;Geri, Amici, & Rocchini, 2011;Pontius, 2000).…”

Section: Lulc Change Prediction and Validationmentioning

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: Lulc Change Prediction and Validationmentioning

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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“…Land-use and land-cover change (LUCC) modeling as a scientific field is rapidly advancing, as land use change is among the most important human influences on the environment. The cellular automata (CA)-Markov model is applicable to spatial land use simulations and land cover reconstructions [28], which could be capable of converting the quantitative results of the Markov chain into spatially explicit outcomes by means of a CA function [29]. This approach is also capable of simulating several land categories simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Using a Cellular Automata-Markov Model to Reconstruct Spatial Land-Use Patterns in Zhenlai County, Northeast China

et al. 2015

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Decadal to centennial land use and land cover change has been consistently singled out as a key element and an important driver of global environmental change, playing an essential role in balancing energy use. Understanding long-term human-environment interactions requires historical reconstruction of past land use and land cover changes. Most of the existing historical reconstructions have insufficient spatial and thematic detail and do not consider various land change types. In this context, this paper explored the possibility of using a cellular automata-Markov model in 90 m × 90 m spatial resolution to reconstruct historical land use in the 1930s in Zhenlai County, China. Then the three-map comparison methodology was employed to assess the predictive accuracy of the transition modeling. The model could produce backward projections by analyzing land use changes in recent decades, assuming that the present land use pattern is dynamically dependent on the historical one. The reconstruction results indicated that in the 1930s most of the study area was occupied by grasslands, followed by wetlands and arable land, while other land categories occupied relatively small areas. Analysis of the three-map comparison illustrated that the major differences among the three maps have less to do with the simulation model and more to do with the inconsistencies among the land categories during the study period. OPEN ACCESSEnergies 2015, 8 3883Different information provided by topographic maps and remote sensing images must be recognized.

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“…It is also observed that the reaction of the model is very good for 30 m to 120 m image resolution, which fits with Landsat TM, ETM remote sensing resolution and more time was spent to simulate the land use change (Wang et al, 2012) .…”

Section: Resultsmentioning

confidence: 57%

Modelling Land-use and Land-cover Changes Using Markov-CA, and Multiple Decision Making in Kirkuk City

Omar

Ahamad²,

Hussin³

et al. 2014

IJSRES

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Abstract. This paper tries to highlight on the analysis of the land-use and land-cover changes in Kirkuk city / Iraq that's due to repeated changes in structures of governments, wars and economic blockade over the past three decades that drove to chaos. The Markov-cellular automata model is an important and powerful tool in simulation. In this article a new Markov-CA model was developed based on built-in multi-regression model and multi-criteria evaluation approach to improve the representation of Markov-CA transition rules. Utilised data relate to the environmental and socio-economic are produce criteria layers and weights in order to output the suitability maps via a ranking method for periods 1984, 1990, 2000 and 2010, which have become conditional for the next step of Markov-CA generation. The suitability maps are compared in order to determine the best fit maps based on the values of the root equation (R 2 ). This comparison helpful to the stakeholders make better decisions and the best maps indicated best transition rules, which is represent the core of Markov-CA model. Thus, the resultant of best suitability maps derives a predefined transition rule for the end of Markov-CA model step. The approach used in the present study a mechanism for monitoring the land-use and land-cover changes in Kirkuk depend on Markov-CA is implemented and evaluated thru the different decision maker. The results assert that the model bears a high applicability and flexibility degree in land-use and land-cover changes.

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Accuracy assessments of land use change simulation based on Markov-cellular automata model

Cited by 144 publications

References 7 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

Using a Cellular Automata-Markov Model to Reconstruct Spatial Land-Use Patterns in Zhenlai County, Northeast China

Modelling Land-use and Land-cover Changes Using Markov-CA, and Multiple Decision Making in Kirkuk City

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