Study of Urban Growth Dynamics Using Global Human Settlement Layer Data Set: Uttarakhand, India

2020 ◽  
Vol 48 (5) ◽  
pp. 817-827
Author(s):  
Garima Nautiyal ◽  
Sandeep Maithani ◽  
Archana Sharma
Keyword(s):  
Urban Growth ◽  
Growth Dynamics ◽  
Human Settlement ◽  
Data Set

Simulation Of Polycentric Urban Growth Dynamics Through Agents

2007 ◽  
pp. 219-235 ◽  
Author(s):  
W. Loibl ◽  
T. Tötzer ◽  
K. Köstl ◽  
K. Steinnocher
Keyword(s):  
Urban Growth ◽  
Growth Dynamics

Urban Growth Dynamics in a Regional Cluster of Cities.

Social Forces ◽  
1963 ◽  
Vol 42 (2) ◽  
pp. 255
Author(s):  
Hope T. Eldridge ◽  
F. Stuart Chapin ◽  
Shirley F. Weiss
Keyword(s):  
Urban Growth ◽  
Growth Dynamics ◽  
Regional Cluster

Urban Growth Dynamics: In a Regional Cluster of Cities

1963 ◽  
Vol 30 (2) ◽  
pp. 184
Author(s):  
Werner Z. Hirsch ◽  
F. Stuart Chapin
Keyword(s):  
Urban Growth ◽  
Growth Dynamics ◽  
Regional Cluster

scholarly journals Urban Growth Dynamics in Perth, Western Australia: Using Applied Remote Sensing for Sustainable Future Planning

Land ◽  
2017 ◽  
Vol 6 (1) ◽  
pp. 9 ◽  
Author(s):  
Andrew MacLachlan ◽  
Eloise Biggs ◽  
Gareth Roberts ◽  
Bryan Boruff
Keyword(s):  
Remote Sensing ◽  
Western Australia ◽  
Urban Growth ◽  
Growth Dynamics ◽  
Future Planning ◽  
Sustainable Future

Urban Growth Dynamics and Modelling Using Remote Sensing Data and Multivariate Statistical Techniques

2018 ◽  
Vol 114 (10) ◽  
pp. 2080 ◽  
Author(s):  
Manish Kumar ◽  
R. B. Singh ◽  
Ram Pravesh ◽  
Pankaj Kumar ◽  
Dinesh Kumar Tripathi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Urban Growth ◽  
Growth Dynamics ◽  
Remote Sensing Data ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical ◽  
Sensing Data

Urban Growth Dynamics.

1963 ◽  
Vol 17 (1) ◽  
pp. 79
Author(s):  
Maurice Kirk ◽  
F. S. Chapin ◽  
Shirley F. Weiss
Keyword(s):  
Urban Growth ◽  
Growth Dynamics

scholarly journals Urban Growth Modeling and Future Scenario Projection Using Cellular Automata (CA) Models and the R Package Optimx

2018 ◽  
Vol 7 (10) ◽  
pp. 387 ◽  
Author(s):  
Yongjiu Feng ◽  
Zongbo Cai ◽  
Xiaohua Tong ◽  
Jiafeng Wang ◽  
Chen Gao ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Urban Growth ◽  
Growth Dynamics ◽  
R Package ◽  
Future Scenarios ◽  
Good Ability ◽  
Gradient Based ◽  
Transition Rules ◽  
Alternative Scenarios ◽  
Spatially Explicit Modeling

Cellular automata (CA) is a spatially explicit modeling tool that has been shown to be effective in simulating urban growth dynamics and in projecting future scenarios across scales. At the core of urban CA models are transition rules that define land transformation from non-urban to urban. Our objective is to compare the urban growth simulation and prediction abilities of different metaheuristics included in the R package optimx. We applied five metaheuristics in optimx to near-optimally parameterize CA transition rules and construct CA models for urban simulation. One advantage of metaheuristics is their ability to optimize complexly constrained computational problems, yielding objective parameterization with strong predictive power. From these five models, we selected conjugate gradient-based CA (CG-CA) and spectral projected gradient-based CA (SPG-CA) to simulate the 2005–2015 urban growth and to project future scenarios to 2035 with four strategies for Su-Xi-Chang Agglomeration in China. The two CA models produced about 86% overall accuracy with standard Kappa coefficient above 69%, indicating their good ability to capture urban growth dynamics. Four alternative scenarios out to the year 2035 were constructed considering the overall effect of all candidate influencing factors and the enhanced effects of county centers, road networks and population density. These scenarios can provide insight into future urban patterns resulting from today’s urban planning and infrastructure, and can inform future development strategies for sustainable cities. Our proposed metaheuristic CA models are also applicable in modeling land-use and urban growth in other rapidly developing areas.

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