4.7 Article

Changes in arable land in response to township urbanization in a Chinese low hilly region: Scale effects and spatial interactions

期刊

APPLIED GEOGRAPHY
卷 88, 期 -, 页码 24-37

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apgeog.2017.08.019

关键词

Arable land change; Scale effect; Neighborhood effect; Catchment scale; Spatial regression model

资金

  1. National Key Research and Development Program [2017YFD0800100]
  2. National Natural Science Foundation of China [41301202]
  3. National Science and Technology Supporting Project [2014BAD14B01, 2014BAD14B05]

向作者/读者索取更多资源

Rapid urbanization leads to losses in arable land; quantitatively analyzing the impact of urbanization on arable land is significant for arable land management. However, changes in arable land due to urbanization with scale and neighborhood effects remains poorly understood at the town scale. In this study, high-resolution historical land use data, landscape metric analysis and spatial regression were integrated to quantify the impacts of urbanization on arable land use change (abandonment and conversion) at spatial scales of 300 m-3300 m using a block size increment of 200 m and at the catchment scale in the town of Jinjing in subtropical central China. Arable land abandonment was the predominant type of arable land change and presented strong spatial autocorrelations at each spatial scale. Arable land was converted to tea fields because agricultural structure transformations were occurring around the urban cores, and the amount of arable land converted to residential land accounted for only a small proportion of the total arable land loss and had no spatial autocorrelation.. The significance and robustness of the arable land changes impacted by urbanization had obvious scale effects and strong neighborhood effects in nearby regions. Compared with block scales, the catchment scale is an optimal scale for assessing the influence of urbanization and applying planning policy. Our results highlight the significance of incorporating spatial interactions in urbanization research, which can generate less biased estimations and consequently lead to proper policy implication and recommendations. In addition, multi-scale comparisons are helpful for better understanding the relationships between arable land changes and urbanization and provide further insights into the harmonious development of rural settlements and urban cores to preserve arable land. (C) 2017 Elsevier Ltd. All rights reserved.

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