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Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery: a case study from Lianyungang City, China

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Abstract

Land use/land cover (LULC) inventory provides an important dataset in regional planning and environmental assessment. To efficiently obtain the LULC inventory, we compared the LULC classifications based on single satellite imagery with a rule-based classification based on multi-seasonal imagery in Lianyungang City, a coastal city in China, using CBERS-02 (the 2nd China-Brazil Environmental Resource Satellites) images. The overall accuracies of the classification based on single imagery are 78.9, 82.8, and 82.0 % in winter, early summer, and autumn, respectively. The rule-based classification improves the accuracy to 87.9 % (kappa 0.85), suggesting that combining multi-seasonal images can considerably improve the classification accuracy over any single image-based classification. This method could also be used to analyze seasonal changes of LULC types, especially for those associated with tidal changes in coastal areas. The distribution and inventory of LULC types with an overall accuracy of 87.9 % and a spatial resolution of 19.5 m can assist regional planning and environmental assessment efficiently in Lianyungang City. This rule-based classification provides a guidance to improve accuracy for coastal areas with distinct LULC temporal spectral features.

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Acknowledgments

This work is one of the achievements of “Study on the Model of Land Use Planning Environmental Multi-temporal States Assessment at County Level” (No: 41271121). It is supported by the National Natural Science Foundation of China to Chen Longgao. The work is also supported by A Project Funded by the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions (SZBF2011-6-B35) in China. We thank the China Center for Resources Satellite Data and Application (CRESDA) for providing the CBERS-02 RS imagery. We also thank the editor and reviewers, and Dr. Shuguo Wang and Dr. Lijuan Wang from Jiangsu Normal University for their constructive advices for the manuscript.

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Authors and Affiliations

  1. Jiangsu Key Laboratory of Resources and Environmental Information Engineering, School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China

    Xiaoyan Yang & Longqian Chen

  2. Institute of Land Resources, Jiangsu Normal University, Xuzhou, 221116, China

    Xiaoyan Yang & Longgao Chen

  3. Department of Geography, University of Tennessee, Knoxville, TN, 37996, USA

    Yingkui Li

  4. Department of Estate Management, Faculty of Built Environment, University of Malaya, Kuala Lumpur, Wilayah Persekutuan, 50603, Malaysia

    Wenjia Xi

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  1. Xiaoyan Yang
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Correspondence to Longqian Chen.

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Yang, X., Chen, L., Li, Y. et al. Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery: a case study from Lianyungang City, China. Environ Monit Assess 187, 449 (2015). https://doi.org/10.1007/s10661-015-4667-3

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