Predicting Urban Land Use Changes Using a CA–Markov Model

Nouri, J.; Gharagozlou, Alireza; Arjmandi, Reza; Faryadi, S H; Adl, Mahsa

doi:10.1007/s13369-014-1119-2

Cited by 112 publications

(51 citation statements)

References 12 publications

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“…The CA-Markov model is a highly capable and widely-used tool for land use simulation [42,43], which combines the Markov chain process and the CA model. The Markov chain process controls temporal change among land use types based on a transition matrix, and the CA model controls spatial pattern change through suitability maps [44,45].…”

Section: Establishment Of Future Luc Scenariosmentioning

confidence: 99%

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Runoff Responses to Climate and Land Use/Cover Changes under Future Scenarios

Pan

Liu

Wang

et al. 2017

Water

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Climate and land use/cover (LUC) are the two most significant factors that directly affect the runoff process. However, most research on runoff response has focused mainly on projected climate variation, while future LUC variability has been neglected. Therefore, the objective of this study is to examine the impacts of projected climate and LUC changes on runoff. -2020, 2021-2030, 2031-2040 and 2041-2050 period, abbreviated S3). These three scenarios are then input into the Soil and Water Assessment Tool (SWAT) model to assess runoff responses. Beijiang River Basin, located in southern China, is used in this case study. The results obtained from S1, S2 and S3 show that runoff change in this basin is mainly caused by climate change; warmer temperatures and greater precipitation increase runoff. LUC change has little influence on runoff at the whole-basin scale, but changes in runoff components are more notable in the urban area than in the natural region at the sub-watershed level. The impact of LUC change in urbanized region on runoff components differ obviously among the wet, normal and dry years, and surface runoff and groundwater are found to be more sensitive to urbanization. Runoff depth is predicted to increase in this basin under the impacts of both climate and LUC changes in the future. Climate change brings greater increase in water yield and surface runoff, whereas LUC change leads to changes in allocation between surface runoff and groundwater in the urban region.

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Section: Establishment Of Future Luc Scenariosmentioning

confidence: 99%

“…The CA-Markov model used in this study is embedded in the IDRISI Kilimanjaro software from Clark Labs. This model contains three stages [43,44,46]. (I) The LUC transition matrix is computed from the LUC map using the Markov model.…”

Section: Establishment Of Future Luc Scenariosmentioning

confidence: 99%

Runoff Responses to Climate and Land Use/Cover Changes under Future Scenarios

Pan

Liu

Wang

et al. 2017

Water

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“…The FLUS model tightly integrates machine learning and statistical models with the CA model [30,35,41,42] for a multiple land use and land cover (LUCC) dynamic simulation. The FLUS model can also consider the non-dominant land use types, which is smarter than the CLUE model.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Simulation of Land Use Change of the Upper and Middle Streams of the Luan River, Northern China

Guan

Jiang

et al. 2019

Sustainability

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Climatic, socio-economic, geophysical, and human activity factors, among others, influence land use patterns. However, these driving factors also have different relationships with each other. Combining machine learning methods and statistical models is a good way to simulate the dominant land use types. The Luan River basin is located in a farming-pastoral transitional zone and is an important ecological barrier between Beijing and Tianjin. In this study, we predicted future land use and land cover changes from 2010 to 2020 in the Luan River’s upper and middle reaches under three scenarios—the natural scenario, the ecological scenario, and the sustainable scenario. The results indicate that cultivated land will decrease while the forested areas will increase quantitatively in the future. Built-up areas would increase quickly in the natural scenario, and augmented expansion of forest would be the main features of land use changes in both the ecological scenario and the sustainable scenario. Regarding the spatial pattern, different land use patterns will be aggregated and patches will become larger. Our findings for the scenario analysis of land use changes can provide a reference case for sustainable land use planning and management in the upper and middle Luan River basin.

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“…In recent years, the land use prediction models have been built by many researchers and some urban geospatial statistical models, such as logistic regression [7] , cellular automata (CA) [8] , Markov chains [9][10] , etc. The Markov model not only predicts the complex urban environment, but also predicts the future prospects of ecologically fragile areas [11] .…”

Section: Introductionmentioning

confidence: 99%