TITLE:
Urban Growth Modeling Using Neural Network Simulation: A Case Study of Dongguan City, China
AUTHORS:
Xinmin Zhang
KEYWORDS:
Urban Growth, Neural Network Simulation, Dongguan City
JOURNAL NAME:
Journal of Geographic Information System,
Vol.8 No.3,
May
11,
2016
ABSTRACT: Dongguan is an important
industrial city, located in the Pearl River Delta, South China. Recently,
Dongguan city experienced a rapid urban growth with the locational advantage by
transforming from traditional agricultural region to modern manufacturing
metropolis. The urban transformation became the usual change in China under the
background of urbanization which belongs to one trend of globalization in the
21st century. This paper tries to analyze urban growth simulation based on
remotely sensed data of previous years and the related physical and
socio-economic factors and predict future urban growth in 2024. The study
examined and compared the land use/cover (LUC) changes over time based on
produced maps of 2004, 2009, and 2014. The results showed that water and forest
area decreased since the past years. In contrast, the urban land increased from
2004 to 2014, and this increasing trend will continue to the future years
through the urbanization process. Having understood the spatiotemporal trends
of urban growth, the study simulated the urban growth of Dongguan city for 2024
using neural network simulation technique. Further, the figure of merit (FoM)
of simulated map of 2014 map was 8.86%, which can be accepted in the simulation
and used in the prediction process. Based on the consideration of water body
and forest, the newly growth area is located in the west, northeast, and
southeast regions of Dongguan city. The finding can help us to understand which
areas are going to be considered in the future urban planning and policy by the
local government.