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Modeling Change-Pattern-Value Dynamics on Land Use: An Integrated GIS and Artificial Neural Networks Approach

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Abstract

The use of spatial methods to detect and characterize changes in land use has been attracting increasing attention from researchers. The objectives of this article were to formulate the dynamics of land use on the temporal and spatial dimensions from the perspectives of the Change-Pattern-Value (CPV) and driving mechanism, based on multitemporal remote sensing data and socioeconomic data. The Artificial Neural Networks were used to identify the factors driving changes in land use. The Pearl River Delta Region of southeast China, which was experiencing rapid economic growth and widespread land conversion, has been selected as the study region. The results show that from 1985 to 2000 in the study region (1) the most prominent characteristics of change in land use were the expansion of the urban land at the expense of farmland, forests, and grasslands, (2) the land-use pattern was being optimized during this period, (3) in an analysis of value, built-up land can yield a return of more than 30 times that of farmland, water area, and forests lands, and (4) rapid economic development, growth in population, and the development of an infrastructure were major driving factors behind ecological land loss and the nonecological land expansion.

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Acknowledgments

The work described in this article was substantially supported by grants from the CRC scheme, the Research Grants Council of The Hong Kong SAR (Project No. 3-ZB40), The Hong Kong Polytechnic University (Project Nos. 1.32.37.87CK and 1.34.9709), Frontier Project on Knowledge Innovation in Institute of Geographical Sciences and Natural Resources Research (IGSNRR), CAS, China (Project No. CXIOG-A02-03), and Knowledge Innovation Project of CAS, China (Project No. KZCX3-SW-333). The authors also wish to express thanks to Professor D. Zheng and Professor Y. L. Cai for valuable discussion and support, and anonymous reviewers for their constructive comments.

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Authors and Affiliations

  1. Institute of Geographical Sciences and Natural Resource Research (IGSNRR), Chinese Academy of Sciences, Anwai, Chaoyang District, Beijing, China

    Erfu Dai & Shaohong Wu

  2. Advanced Research Centre for Spatial Information TechnologyDepartment of Land Surveying and Geo-Infomatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    Wenzhong Shi, Chui-kwan Cheung & Ahmed Shaker

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  1. Erfu Dai
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  2. Shaohong Wu
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  5. Ahmed Shaker
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Correspondence to Erfu Dai.

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Dai, E., Wu, S., Shi, W. et al. Modeling Change-Pattern-Value Dynamics on Land Use: An Integrated GIS and Artificial Neural Networks Approach. Environmental Management 36, 576–591 (2005). https://doi.org/10.1007/s00267-004-0165-z

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