A neural network based urban growth model of an Indian city |
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| Authors: | S Maithani |
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| Institution: | (1) Institute of Applied Ecology, Chinese Academy of Sciences, 72, Wenhua Road, Shenhe District, Shenyang, 110016, China;(2) Department of International Relations and Geography, Florida International University, 11200 S.W. 8th Street, Miami, FL 33199, USA; |
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| Abstract: | The aim of the study reported in this paper is to demonstrate that the subjectivity in urban growth modeling and the calibration
time can be reduced by using objective techniques like Artificial neural network (ANN). As a case study, the ANN-based model
was applied to simulate the urban growth of Saharanpur city in India. In the proposed model, remote sensing and GIS were used
to generate site attributes, while ANN was used to reveal the relationships between urban growth potential and the site attributes.
Once ANN learnt the relationship, it was then used to simulate the urban growth. Different feed forward ANN architectures
were evaluated in this study and finally the most optimum ANN architecture was selected for future growth simulation.
The simulated urban growth maps were evaluated on a cell by cell matching using Kappa index and three spatial metrices namely,
Mean Patch Fractal Dimension, Landscape Shape Index and Percentage of like Adjacencies. The most optimal architecture was
then used subsequently for simulating the future urban growth. The study results thus, demonstrated that the ANN-based model
can objectively simulate urban growth, besides successfully coupling GIS, remote sensing and ANN. |
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