生态与农村环境学报 ›› 2017, Vol. 33 ›› Issue (7): 592-599.doi: 10.11934/j.issn.1673-4831.2017.07.003

• 区域环境与发展 • 上一篇    下一篇

徐州市区土地利用格局变化分析及其空间扩张模拟

郎文婧1, 李效顺1,2, 卞正富1, 曲福田2   

  1. 1. 中国矿业大学国土环境与灾害监测国家测绘局重点实验室, 江苏 徐州 221116;
    2. 南京农业大学中国土地问题研究中心, 江苏 南京 210095
  • 收稿日期:2016-09-08 出版日期:2017-07-25 发布日期:2017-07-25
  • 通讯作者: 李效顺,E-mail:lxsh@cumt.edu.cn E-mail:lxsh@cumt.edu.cn
  • 作者简介:郎文婧(1993-),女,吉林吉林人,硕士生,主要研究方向为土地经济与政策。E-mail:ts15160129a3@cumt.edu.cn
  • 基金资助:

    国家自然科学基金面上项目(71473249);国家自然科学基金重点项目(U1361214);国家科技基础性工作专项重点项目(2014FY110800);江苏省社会科学基金重点项目(15EYA002)

Analysis of Changes in Land Use Pattern in Xuzhou City and Simulation of Its Spatial Expansion

LANG Wen-jing1, LI Xiao-shun1,2, BIAN Zheng-fu1, QU Fu-tian2   

  1. 1. The Key Laboratory for Land Environment and Disaster Monitoring of SBSM in Jiangsu Province, China University of Mining and Technology, Xuzhou 221116, China;
    2. China Land Problem Research Center, Nanjing Agricultural University, Nanjing 210095, China
  • Received:2016-09-08 Online:2017-07-25 Published:2017-07-25

摘要:

城市化是社会发展进程中的重要阶段,而随着城市化的快速发展,城市土地利用格局发生了巨大变化,城市土地利用问题逐渐浮现。为了破解城市土地利用格局失衡和空间扩张失控的难题,通过遥感解译、空间分析及模型仿真对徐州市区进行土地利用格局分析及其空间扩张模拟预测,预测结果可为未来土地资源的合理利用及政府决策提供科学依据。结果表明:(1)徐州市区各土地利用格局演变表现为集聚趋势,城市空间扩张与结构调整并行,并且总量增长占主导;景观格局方面,斑块破碎化程度降低,斑块分布更加集中,景观复杂程度降低,景观内部与其他斑块类型相邻的斑块数量减少;土地利用/覆被方面,徐州市区周边的耕地、林地和未利用地等用地类型向建设用地不断转化,并且建设用地表现为向东北部和东部扩张趋势。(2)空间模拟显示,2016-2020年间徐州市区周边建设用地空间扩张方向上仍然集中在东北部和东部地区,与现有土地和城市规划方向较为一致,空间扩张预测规模由高到低分别为:东北部4 126.23 hm2,东部3 203.01 hm2,西北部2 723.22 hm2,南部2 600.91 hm2,东南部2 203.11 hm2,西南部2 150.64 hm2,西部1 834.83 hm2,北部1 565.91 hm2。建议徐州市区未来(至少5 a内)继续对东部和东北部地区进行重点建设,以实现区域高效可持续发展。

关键词: 遥感应用, 景观格局, 土地利用, CA-Markov模型

Abstract:

Urbanization is an important stage in the process of social development. However, with rapid development of the urbanization, urban land use has undergone tremendous changes in pattern, and consequently problems gradually emerge in urban land use. In order to solve the problems of disbalance of urban land-use in pattern and uncontrolled spatial expansion of cities and towns, the land use pattern was analyzed and spatial expansion of the urban area of Xuzhou was simulated and predicted by means of interpretation of remote sensing images, spatial analysis and model simulation, in the hope that the prediction may provide some scientific bases for rational utilization of the land resources and government decision-making in future. Results show that:(1) Land use in various districts of Xuzhou City tends to be on a trend of agglomeration in pattern with urban spatial expansion and structural readjustment going on in parallel and taking the lead in growth of the total amount of GDP. As for the landscape pattern, patches will decline in fragmentation degree and get more concentrated in distribution; and the landscape is getting less in complexity and in number of types of internal plaques adjoining to other types. As regards to land use or land cover, cultivated farmlands, woodlands and unused lands around the urban area of Xuzhou City will keep on alienating into construction land, and the expansion of construction land tends to be heading toward northeast and east. (2) The spatial simulation shows that the spatial expansion of construction land around the urban area of Xuzhou City will be oriented towards northeast and east in 2016-2020, which is consistent with the direction of the existing land use and urban planning. Predicted scale of the spatial expansion varies from area to area, showing a decreasing order of 4 126.23 hm2 in the northeast > 3 203.01 hm2 in the east > 2 723.22 hm2 in the northwest > 2 600.91 hm2 in the south > 2 203.11 hm2 in the southeast > 2 150.64 hm2 in the southwest > 1 834.83 hm2 in the west > 1 565.91 hm2 in the north. It is suggested that in future (at least in the five years to come), Xuzhou City should keep on accomplishing its key construction projects in the eastern and northeastern parts of the urban areas as predicted in order to achieve regional high-efficient sustainable development.

Key words: remote sensing application, landscape pattern, land use, CA-Markov model

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