Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio
Improving the capability of an integrated CA-Markov model to simulate spatio-temporal urban growth trends using an Analytical Hierarchy Process and Frequency Ratio
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DOI：
10.1016/j.jag.2017.03.006
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发表时间：
2017-07-01
影响因子：
7.5
通讯作者：
Ash'aari, Zulfa Hanan
中科院分区：
文献类型：
--
作者：
Aburas, Maher Milad;Ho, Yuek Ming;Ash'aari, Zulfa Hanan
在涉及空间建模的城市研究中，建立对未来城市增长的精确模拟被认为是最重要的挑战之一。本研究的目的是利用基于层次分析法（AHP）的CA-MC和基于频率比（FR）的CA-MC，提高综合ca -马尔可夫链（CA-MC）模型的模拟能力，并比较传统模型和混合模型的性能和准确性。各种物理、社会经济、公用事业和环境标准被用作预测指标，包括海拔、坡度、土壤质地、人口密度、到商业区的距离、到教育区的距离、到居民区的距离、到工业区的距离、到公路的距离、到高速公路的距离、到铁路的距离、到电力线的距离、到河流的距离和土地覆盖。为了进行校准，采用了三个模型来模拟2010年的城市增长趋势；利用2010年的实际数据，利用相对操作特征（ROC）和Kappa系数方法对模型进行验证，从而创建2020年和2030年的未来城市增长图。验证结果证实，CA-MC模型与FR模型的整合，以及在模拟过程中引入城市增长的重要驱动力，使得CA-MC模型的模拟能力得到了提高。本研究为基于FR的CA-MC模型的改进提供了一种新的途径，将为未来可持续城市规划的发展提供有力的支持。(C) 2017 Elsevier B.V.版权所有
The creation of an accurate simulation of future urban growth is considered one of the most important challenges in urban studies that involve spatial modeling. The purpose of this study is to improve the simulation capability of an integrated CA-Markov Chain (CA-MC) model using CA-MC based on the Analytical Hierarchy Process (AHP) and CA-MC based on Frequency Ratio (FR), both applied in Seremban, Malaysia, as well as to compare the performance and accuracy between the traditional and hybrid models. Various physical, socio-economic, utilities, and environmental criteria were used as predictors, including elevation, slope, soil texture, population density, distance to commercial area, distance to educational area, distance to residential area, distance to industrial area, distance to roads, distance to highway, distance to railway, distance to power line, distance to stream, and land cover. For calibration, three models were applied to simulate urban growth trends in 2010; the actual data of 2010 were used for model validation utilizing the Relative Operating Characteristic (ROC) and Kappa coefficient methods Consequently, future urban growth maps of 2020 and 2030 were created. The validation findings confirm that the integration of the CA-MC model with the FR model and employing the significant driving force of urban growth in the simulation process have resulted in the improved simulation capability of the CA-MC model. This study has provided a novel approach for improving the CA-MC model based on FR, which will provide powerful support to planners and decision-makers in the development of future sustainable urban planning. (C) 2017 Elsevier B.V. All rights reserved.