Driving Force Analysis and Scenarios Simulation of Land Use Based on Cell Automata Model
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    Abstract:

    Simulation of land use spatial pattern can reveal the geological regularity and identify the driving factors of regional land use change from multi-scales, which is an important way to clarify land use changes process and pattern for the future period. This paper took Shuangcheng District in Harbin City as a case and developed a simulation model based on Cellular automata (CA) combined with Artificial neural network (ANN). Totally 14 driving force factors were selected from four aspects which had significant impact on land use change, including the distance variables, number of adjacent land use type, unit natural attribute and socio-economic factors. They were used in the ANN-CA model to simulate land use change of Shuangcheng District from 2002 to 2013. The accuracy of simulation was verified by using the actual interpretation data in 2013 and it was 85.26%, which showed the model could be used to simulate the LUCC of Shuangcheng District. Furthermore, the land use pattern in 2024 was simulated under four scenarios: natural endowment scenario, rapid economic development scenario, basic farmland protection scenario and land use planning scenario. The results showed that land use pattern presented obvious spatial diversity under different scenarios, different driving factors resulted in diverse changes of various land-use types, and socio-economic factors played an important role in the conversion of land use types. The study outcomes could provide scientific decision support for the sustainable utilization of land resources in Shuangcheng District.

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History
  • Received:July 10,2017
  • Revised:
  • Adopted:
  • Online: December 10,2017
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