Dynamic urban growth model at regional scale and its application

• Dynamic urban expansion simulation at regional scale is one of the important research methodologies in Land Use/Cover Change (LUCC) and global environmental change influenced by urbanization. However, previous studies indicate that the single urban expansion simulation for future scenarios at local scale cannot meet the requirements for characterizing and interpreting the interactive mechanisms of regional urbanization and global environmental change. This study constructed a regional Dynamic Urban Expansion Model (Reg-DUEM) suitable for different scenarios by integrating the Artificial Neural Network (ANN) and Cellular Automaton (CA) model. Firstly we analyzed the temporal and spatial characteristics of urban expansion and acquired a prior knowledge rules using land use/cover change datasets of Beijing-Tianjin-Tangshan metropolitan area. The future urban expansion under different scenarios is then simulated based on a baseline model, economic models, policy models and the structural adjustment model. The results indicate that Reg-DUEM has good reliability for a non-linear expansion simulation at regional scale influenced by macro-policies. The simulating results show that future urban expansion patterns from different scenarios of the metropolitan area have the tremendous spatio-temporal differences. Future urban expansion will shift quickly from Beijing metropolis to the periphery of Tianjin and Tangshan city along coastal belt.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Geoteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Geotechnical Engineering (hsv//eng)

Keyword

Beijing-Tianjin-Tangshan Metropolitan Area

GIS

Remote sensing

Urban expansion simulation

artificial neural network

baseline conditions

cellular automaton

coastal zone

data set

global change

land cover

land use change

metropolitan area

regionalization

urban development

urban growth

urbanization

Beijing [China]

China

Hebei

Tangshan

Tianjin

Publication and Content Type

ref (subject category)

art (subject category)