Land Use Change Prediction Method Based on CA-Markov Model Under Cloud Computing Environment

KANG Junfeng; LI Shuang; FANG Lei

doi:10.13203/j.whugis20180319

Volume 45 Issue 7

Jul. 2020

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Geomatics and Information Science of Wuhan University > 2020 > 45(7): 1021-1026, 1034. > DOI: 10.13203/j.whugis20180319

KANG Junfeng, LI Shuang, FANG Lei. Land Use Change Prediction Method Based on CA-Markov Model Under Cloud Computing Environment[J]. Geomatics and Information Science of Wuhan University, 2020, 45(7): 1021-1026, 1034. DOI: 10.13203/j.whugis20180319

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Land Use Change Prediction Method Based on CA-Markov Model Under Cloud Computing Environment

KANG Junfeng^{1, 2,},
LI Shuang¹,
FANG Lei^{3, 4, ,}

1.
School of Architectural and Surverying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China
2.
School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
3.
Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
4.
Shenzhen Institute of Research and Innovation, the University of Hong Kong, Shenzhen 518172, China

Funds:

The National Key Research and Development Program of China 2016YFC0803105

the National Natural Science Foundation of China 41701462

Chinese Scholarship Council Foundation 201808360065

Jiangxi Provincial Department of Education Science and Technology Research Projects 3204704062

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Author Bio:
KANG Junfeng, PhD, associate professor, specializes in researches of high-performance GIS algorithms and applications. E-mail: junfeng.kang@jxust.edu.cn
Corresponding author:
FANG Lei, PhD. E-mail: fanglei@fudan.edu.cn
Received Date: June 19, 2019
Published Date: July 29, 2020

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Abstract

Abstract

Traditional land-use change prediction methods are usually implemented by serial algorithms or semi-manual methods and they were often inefficient. This paper develops a parallel land-use change prediction method based on cloud lomputing (Cloud-CMLP), the map reduce programming model is used to parallelize and extend the cellular automata(CA)-Markov model. Taking Hangzhou as a study area, the experiments are conducted as follows: ① Efficiency tests are conducted to compare the core algorithms of Cloud-CMLP under the different number of data. ② The Cloud-CMLP method is used to simulate the land-use change in 2013, and the simulated results are compared with the 2013 remote sensing image classification results to verify the validity of Cloud-CMLP method. ③ The land-use change in 2020 is predicted and analyzed by using Cloud-CMLP, and the predicted results show that the land area of urban construction is rising rapidly and mainly come from the conversion of agricultural land.
- cloud computing,
- Hadoop,
- MapReduce,
- CA-Markov,
- land use change

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