资源科学 ›› 2019, Vol. 41 ›› Issue (6): 1082-1092.doi: 10.18402/resci.2019.06.07

• 土地资源 • 上一篇    下一篇

基于最坏情景理论的连云港土地利用变化情景模拟

杨小艳1(), 凌宇3, 李龙2, 陈龙高1(), 陈龙乾2   

  1. 1. 江苏师范大学地理测绘与城乡规划学院,徐州 221116
    2. 中国矿业大学环境与测绘学院,徐州 221116
    3. 江苏省土地开发整理中心,南京 210024
  • 收稿日期:2018-10-17 修回日期:2019-02-27 出版日期:2019-06-25 发布日期:2019-06-25
  • 作者简介:

    作者简介:杨小艳,女,四川简阳人,副教授,博士,研究方向为土地利用及规划。E-mail: yangxy0705@163.com

  • 基金资助:
    国家自然科学基金项目(41601087);江苏高校优势学科建设工程资助项目;江苏高校人文社会科学校外研究基地(特色镇村建设与土地管理研究基地)项目

Worst case scenario-based methodology for simulating land-use change in coastal city in China: A case study of Lianyungang

Xiaoyan YANG1(), Yu LING3, Long LI2, Longgao CHEN1(), Longqian CHEN2   

  1. 1. School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China
    2. School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
    3. Land Consolidation Center in Jiangsu Province, Nanjing 210024, China
  • Received:2018-10-17 Revised:2019-02-27 Online:2019-06-25 Published:2019-06-25

摘要:

预测和模拟土地利用情景变化对于进一步评估土地利用变化的生态环境影响以及优化土地利用规划方案具有重要作用。本文基于最坏情景理论,以基于人工神经网络(ANN)和元胞自动机(CA)的FLUS模型为支持,模拟了最坏情景模式(WSB)和非最坏情景模式下(NWSB)的沿海城市连云港2020年土地利用变化。结果表明:①基于生态因子耐受度测算得出研究区最坏情景区域共计489.67 km2,该区域主要包括连云港中部云台山国家自然保护区内海拔较高、坡度较大、分布大量天然林地的区域以及重要的河流湖泊水库等生态水体;②两种情景模式下城镇用地均有较大程度的扩张,在WSB情景下城镇用地扩张避开了最坏情景区域;③由于村庄的存量利用率较高,因此在WSB模式下对于耕地的占用相对较小,表明该模式下可在一定程度上减少村庄建设对耕地的占用,从而提高了存量建设用地的使用效率;④由于最坏情景区域的约束和限制转化作用,城镇用地扩张在WSB模式下不得不占用更多的耕地,从而对耕地保护工作提出了更高的要求。基于最坏情景理论进行土地利用变化模拟对于生态环境保护及区域可持续发展具有重要的支撑作用,因而既可为区域土地规划和管理提供支持,也可为其他地区土地利用模拟提供参考和借鉴。

关键词: 最坏情景理论, 生态因子耐受度, 土地利用变化, 情景模拟, 连云港

Abstract:

Simulating and predicting future land-use pattern is of great importance for supporting land-use eco-environmental impact assessment and optimizing land-use planning schemes. Using artificial neural network (ANN) and cellular automata (CA) based future land use simulation (FLUS) model, we proposed a land-use change simulation methodology and applied it for predicting the land-use pattern in a coastal city of China, Lianyungang, in 2020 using the worst case scenario-based (WSB) constraint and non-worst case scenario-based (NWSB) models. The results indicate that: (1) The “worst case” areas are mainly identified in the central-eastern part of the city with a national nature reserve, high elevation and steep slope, natural forests, and water bodies such as rivers, lakes, and reservoirs, and the area is 489.67 km2; (2) With or without the constraint of prohibiting factors or “worst case”, urban land would both expand to a large extent; and with the WSB constraint urban expansion would avoid the “worst case” areas; (3) More arable land would convert into rural residential land in the simulation based on NWSB than with WSB constraint, indicating that the land use simulation with WSB constraint can decrease the occupation of arable land when additional rural residential land is needed; However, (4) the overall area of arable land converting to urban land is lager in the simulation based on the WSB constraint due to the restriction of land use conversion in the “worst case” areas, which challenges the arable land protection strategy in the city. The simulation and prediction of future land-use pattern based on the “worst case” constraint can support eco-environmental protection and regional sustainable development as well as local land-use planning and management. It may also provide a reference for land-use change simulation in other areas.

Key words: worst case constraint, ecological tolerance index, land-use change, simulation, Lianyungang City