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An adding/deleting approach to improve land change modeling: a case study in Qeshm Island, Iran

  • Ali Kourosh Niya
  • Jinliang HuangEmail author
  • Ali Kazemzadeh-Zow
  • Babak Naimi
Original Paper
  • 48 Downloads

Abstract

Land use/cover change (LUCC) simulation models are helpful tools for decision makers because of their capacity of predicting the landscape dynamics under various scenarios and thereby developing countermeasures. Developing LUCC models with high reliability still remains challenging due to complicated influencing of natural and anthropogenic factors. An adding/deleting approach is proposed in this study to explore whether and to what extent it can improve the accuracy of a hybrid LUCC model involved with cellular automata, Markov chain, and artificial neural network in the Qeshm Island, the biggest island in the Persian Gulf. The accuracy assessment was conducted by comparing the simulation results obtained from the models with the maps derived from Landsat image in 2014. The results revealed that the adding/deleting approach could improve the prediction accuracy of the model for the majority of land use classes as the area of the correctly predicted classes increased to 7.2 km2, which is greater than 6.09 km2 without using the approach. We further compared the results derived from the proposed approach with those from cellular automata-Markov chain-artificial neural network, Markov chain-artificial neural network, and cellular automata-Markov chain-logistic regression, resulting in the Figure of Merit index of 7.8 with this approach, compared to 6.7, 5.1, and 4.5 with the other three models mentioned above. This study demonstrates that the proposed approach is effective for improving the performance of LUCC modeling.

Keywords

Land use/cover change modeling Cellular automata-Markov chain Adding/deleting Qeshm Island 

Notes

Acknowledgments

Anonymous reviewers supplied constructive feedback that helped to improve this manuscript.

Authors’ contributions

A.K. N., J. H., and A.K. conceived and designed the project; A.K.N. and A.K. executed analyses; A. K. N, J. H., A.K., and B. N. wrote the paper.

Funding

This research was partially supported by Chinese Government Marine Scholarship (Grant No: 2016SOA016).

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest. The funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

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Copyright information

© Saudi Society for Geosciences 2019

Authors and Affiliations

  • Ali Kourosh Niya
    • 1
  • Jinliang Huang
    • 1
    Email author
  • Ali Kazemzadeh-Zow
    • 2
  • Babak Naimi
    • 3
  1. 1.Coastal & Ocean Management InstituteXiamen UniversityXiamenChina
  2. 2.Department of RS and GIS, Geography FacultyUniversity of TehranTehranIran
  3. 3.Institute for Biodiversity and Ecosystem DynamicsUniversity of AmsterdamAmsterdamThe Netherlands

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