A Local Land Use Competition Cellular Automata Model and Its Application

Yang, Jun; Su, Junru; Chen, Fei; Xie, Peng; Ge, Quansheng

doi:10.3390/ijgi5070106

Cited by 41 publications

(26 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Similar to other metropolitan areas, like Beijing and Shanghai, the Tokyo metropolitan area has more than 10% of cropland areas that potentially can be changed to built-up areas. However, the difference is in the population change rate; in other words, the birth rate in Japan is very low, and if it continues decreasing, the built-up areas located in sub-regions will disappear, and as a result, the study area will become a shrunken city [67,68]. For these reasons, predicting land use/cover distribution in the immediate future gets more and more critical, thus simulating conditions under different scenarios can provide valuable information in order to avoid many issues, including chaotic urban sprawl.…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area

2018

View full text Add to dashboard Cite

Abstract:Simulating future land use/cover changes is of great importance for urban planners and decision-makers, especially in metropolitan areas, to maintain a sustainable environment. This study examines the changes in land use/cover in the Tokyo metropolitan area (TMA) from 2007 to 2017 as a first step in using supervised classification. Second, based on the map results, we predicted the expected patterns of change in 2027 and 2037 by employing a hybrid model composed of cellular automata and the Markov model. The next step was to decide the model inputs consisting of the modeling variables affecting the distribution of land use/cover in the study area, for instance distance to central business district (CBD) and distance to railways, in addition to the classified maps of 2007 and 2017. Finally, we considered three scenarios for simulating land use/cover changes: spontaneous, sub-region development, and green space improvement. Simulation results show varied patterns of change according to the different scenarios. The sub-region development scenario is the most promising because it balances between urban areas, resources, and green spaces. This study provides significant insight for planners about change trends in the TMA and future challenges that might be encountered to maintain a sustainable region.

show abstract

Section: Discussionmentioning

confidence: 99%

Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area

2018

View full text Add to dashboard Cite

show abstract

“…There are many methods to evaluate the model of land use change, such as Land Use Intensity [39], CLUE-S (conversion of land use and its effects at a small region extent) [40], Landscape Fragmentation Index [5], etc. Many evaluation methods are mainly focused on a certain aspects in There is a large trend for Chinese LUCC entropy during 1990-2010 which is reflected in the value of Shannon entropy.…”

Section: Discussionmentioning

confidence: 99%

“…More and more attention has been given to LUCC by related scholars in recent years [1][2][3][4][5]. LUCC is a complex system that is composed of nature, society and economy, the structure and function of the system show different patterns and combinations in space, and evolution processes in time [6,7].…”

Section: Introductionmentioning

confidence: 99%

Entropies of the Chinese Land Use/Cover Change from 1990 to 2010 at a County Level

Fan

et al. 2017

Entropy

View full text Add to dashboard Cite

Land Use/Cover Change (LUCC) has gradually became an important direction in the research of global changes. LUCC is a complex system, and entropy is a measure of the degree of disorder of a system. According to land use information entropy, this paper analyzes changes in land use from the perspective of the system. Research on the entropy of LUCC structures has a certain "guiding role" for the optimization and adjustment of regional land use structure. Based on the five periods of LUCC data from the year of 1990 to 2010, this paper focuses on analyzing three types of LUCC entropies among counties in China-namely, Shannon, Renyi, and Tsallis entropies. The findings suggest that: (1) Shannon entropy can reflect the volatility of the LUCC, that Renyi and Tsallis entropies also have this function when their parameter has a positive value, and that Renyi and Tsallis entropies can reflect the extreme case of the LUCC when their parameter has a negative value.; (2) The entropy of China's LUCC is uneven in time and space distributions, and that there is a large trend during 1990-2010, the central region generally has high entropy in space.

show abstract

“…Over the past two decades, many studies have focused on the modelling and dynamic simulation of urban development with the help of the spatial data analysis functionality of Geographic Information Systems (GIS), as well as statistical and artificial intelligence methods and geosimulation models such as the cellular automata (CA) (e.g., [9][10][11][12][13][14][15][16][17][18][19]). …”

Section: Introductionmentioning

confidence: 99%

Integration of Local and Global Support Vector Machines to Improve Urban Growth Modelling

Mirbagheri

Alimohammadi

2018

IJGI

View full text Add to dashboard Cite

Abstract:The use of local information for the classification and modelling of spatial variables has increased with the application of statistical and machine learning algorithms, such as support vector machines (SVMs). This study presents a new local SVM (LSVM) model that was developed to model the probability of urban development and simulate urban growth in a subregion in the southwestern suburb of the Tehran metropolitan area, Iran, for the periods of 1992-1996 and 1996-2002. Based on the focal training sample, the model was calibrated using the cross-validation method, and the optimal bandwidth was determined. The results were compared with those of a nonlinear global SVM (GSVM) model that was calibrated based on the ten-fold cross-validation method. This study then evaluated an integrated SVM model (LGSVM) obtained based on a weighted combination of the local and global urban development probabilities. A comparison of the probability maps showed a higher accuracy for the LGSVM than for either the LSVM or GSVM model. To assess the performance of the LSVM, GSVM and LGSVM models in the simulation of urban growth, probability maps were employed as the transition rules for urban cellular automata. The results show that a trade-off between local and global SVM models can enhance the performance of urban growth modelling.

show abstract

A Local Land Use Competition Cellular Automata Model and Its Application

Cited by 41 publications

References 31 publications

Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area

Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area

Entropies of the Chinese Land Use/Cover Change from 1990 to 2010 at a County Level

Integration of Local and Global Support Vector Machines to Improve Urban Growth Modelling

Contact Info

Product

Resources

About