长江流域资源与环境 >> 2016, Vol. 25 >> Issue (11): 1729-1737.doi: 10.11870/cjlyzyyhj201611012

• 自然资源 • 上一篇    下一篇

基于CLUE-S模型的重庆市渝北区土地利用变化动态模拟

谢莹, 匡鸿海, 吴晶晶, 程玉丝   

  1. 西南大学地理科学学院, 重庆 400715
  • 收稿日期:2016-03-16 修回日期:2016-06-05 出版日期:2016-11-20
  • 通讯作者: 匡鸿海,E-mail:hhkuang@yahoo.com E-mail:hhkuang@yahoo.com
  • 作者简介:谢莹(1992~),女,硕士研究生,主要从事土地利用变化和3s技术研究.E-mail:xieying19926@163.com
  • 基金资助:
    国家自然科学基金青年基金资助项目(41101036)

DYNAMIC SIMULATION OF LAND USE CHANGE IN YUBEI DISTRICT OF CHONGQING BASED ON CLUE-S MODEL

XIE Ying, KUANG Hong-hai, WU Jing-jing, CHENG Yu-si   

  1. School of Geographical Sciences, Southwest University, Chongqing 400715, China
  • Received:2016-03-16 Revised:2016-06-05 Online:2016-11-20
  • Supported by:
    National Natural Science Foundation of China(41101036)

摘要: 以重庆市渝北区为研究区域,运用CLUE-S模型,结合Logistic回归分析,分别以2007年和2009年为基期,对渝北区2013年土地利用情况进行模拟研究,在此基础上构建了渝北区2013~2020年3种不同情景的土地利用变化模式,模拟了3种情景模式下渝北区在2020年的土地利用空间分布格局。结果表明:(1)两期模拟的正确率分别达到了92.26%和94%,Kappa系数值分别为90.32%和92.5%,均取得了较好的模拟效果,说明CLUE-S模型适用于渝北区的土地利用空间格局变化的模拟研究,具有较好的模拟区域土地利用时空变化的能力;(2)地形、国道、省道、高速公路等主要道路、河流、城镇和村庄是影响渝北区土地利用空间格局变化的重要驱动因素;(3)在3种情景模式中,主要的用地格局变化均发生在两江新区,区内建设用地总体呈现向东北部扩张的趋势,表明区域经济社会发展政策对用地类型的变化具有较大的影响;(4)从促进城乡统筹和谐发展、土地节约集约利用、生态环境显著改善和保护耕地的区域发展目标而言,情景模式2为较为合理的发展模式。研究结果可为决策部门在土地可持续利用和土地管理方面提供参考依据。

关键词: 渝北区, 土地利用/土地覆被变化, CLUE-S模型, 情景模拟, Logistic回归

Abstract: In this paper, taking the Yubei District of Chongqing as the study area, based on CLUE-S model and Binary Logistic stepwise regression analysis, using the remote sensing land use historical imageries of 2007 and 2009 of Yubei District,and the key forces driving land use change and controlling land use pattern in Yubei District, land use spatial distribution pattern in 2013 of Yubei District was simulated. Then, the simulated results of the two temporal scale were compared with the real land use map of 2013 to validate the precision of the simulation. And on this basis, for a better understanding of the future land use changes in Yubei District, three different scenarios of land use change for further 7 years (from 2013 to 2020) of Yubei District were constructed, and three different land use spatial distribution patterns in 2020 of Yubei District were predicted by using the CLUE-S model. The results showed that using CLUE-S model, at 100m spatial resolution level, the simulation accuracy of the two temporal scale reached respectively 92.26% and 94%, Kappa indexes were 90.32% and 92.5% respectively, which suggesting that the CLUE-S model applies to simulate temporal and spatial changes in land use from 2007 to 2009 and from 2009 to 2013 of Yubei District.This model which has the capability of rnodeling changes in quantity and location sirnultaneously, has a good understanding of the futher land use change of Yubei District and applies to predict the land use spatio-temporal change of Yubei District. And the key driving factors which are selected from biophysical and socioeconomic factors including topography, national roads, province roads, highways, rivers, urban, town and rural residential areas play important roles in driving the land use spatial distribution change of Yubei District. The results of scenarios analysis demonstrate that in 2020 the land use change mainly occured in Chongqing Liang Jiang New Area, including Yufengshan town, Shuangfengqiao subdistrict, Lianglu subdistrict, Wangjia subdistrict and Gulu town, which suggesting that the regional social and economic development policy has an important influence on land use change. In the scenario analysis, the urban and built-up land was significantly increased under all three different scenarios, that is scenario Ⅰ > scenario Ⅱ > scenario Ⅲ. Whereas there was obvious difference in the cultivated land and forest land change under three different scenarios. The cultivated land was decreasing under all three different scenarios, that is scenario Ⅲ > scenario Ⅰ > scenario Ⅱ. And in scenario Ⅰ, the forest land was decreasing, whereas in scenario Ⅱand Ⅲ, the forest land was increasing. So during the process of social economy development in Yubei District, the scenario Ⅱ is much more reasonable for the goal of urban and rural harmonious development, economical and intensive use of land, ecological environment improvement and cultivated land protection. The study conclusions will provide data reference and basic information of decision support for Yubei District future land use planning, management and policy-making.

Key words: Yubei District, land use/land cover change, CLUE-S model, scenario simulation, Logistic regression

中图分类号: 

  • F293.2
[1] VERBURG P H, SOEPBOER W, VELDKAMP A, et al. Modeling the spatial dynamics of regional land use:the CLUE-S Model[J]. Environmental Management, 2002, 30(3):391-405.
[2] 唐华俊, 吴文斌, 杨鹏, 等. 土地利用/土地覆被变化(LUCC)模型研究进展[J]. 地理学报, 2009, 64(4):456-468.[TANG H J, WU W B, YANG P, et al. Recent progresses of land use and land cover change (LUCC) models[J]. Acta Geographica Sinica, 2009, 64(4):456-468.]
[3] 蔡玉梅, 刘彦随, 宇振荣, 等. 土地利用变化空间模拟的进展-CLUE-S模型及其应用[J]. 地理科学进展, 2004, 23(4):63-71[CAI Y M, LIU Y S, YU Z R, et al. Progress in spatial simulation of land use change-CLUE-S model and its application[J]. Progress in Geography, 2004, 23(4):63-71.]
[4] LAMBIN E F, BAULIES X, BOCKSTAEL N, et al. Land-use and land-cover change (LUCC):implementation strategy[R]. IGBP Report No. 48 and IHDP Report No. 10, 1999.
[5] 王丽艳, 张学儒, 张华, 等. CLUE-S模型原理与结构及其应用进展[J]. 地理与地理信息科学, 2010, 26(3):73-77[WANG L Y, ZHANG X R, ZHANG H, et al. Principle and structure of CLUE-S model and its progresses[J]. Geography and Geo-Information Science, 2010, 26(3):73-77.]
[6] ZHOU R, SU H L, WANG X J, et al. Application of Land Use Model Combined with GIS and RS Technology in Supporting Urban Spatial Planning[M]//GEERTMAN S, TOPPEN F, STILLWELL J. Planning Support Systems for Sustainable Urban Development. Berlin Heidelberg:Springer, 2013, 195:107-125.
[7] 蔺卿, 罗格平, 陈曦. LUCC驱动力模型研究综述[J]. 地理科学进展, 2005, 24(5):81-89[LIN Q, LUO G P, CHEN X. Review of land-use model[J]. Progress in Geography, 2005, 24(5):81-89.]
[8] 朱利凯, 蒙吉军. 国际LUCC模型研究进展及趋势[J]. 地理科学进展, 2009, 28(5):782-790[ZHU L K, MENG J J. Advance in and tendencies of land use and cover change model[J]. Progress in Geography, 2009, 28(5):782-790.]
[9] 王丽, 钱乐祥. 土地利用和土地覆被变化模型方法综述[J]. 河南大学学报(自然科学版), 2005, 35(1):52-57[WANG L, QIAN L X. An reviews of model methods on land use and land covor change[J]. Journal of Henan University (Natural Science), 2005, 35(1):52-57.]
[10] 张叶, 江晓波, 邱枫. LUCC模型研究综述[J]. 资源开发与市场, 2006, 22(4):311-314[ZHANG Y, JIANG X B, QIU F. Summary on LUCC model research[J]. Resource Development & Market, 2006, 22(4):311-314.]
[11] 解靓, 钟凯文, 孙彩歌, 等. 土地利用与土地覆盖模型研究概述[J]. 农机化研究, 2008(7):8-12, 17[XIE L, ZHONG K W, SUN C G, et al. A review of land use and land cover change model[J]. Journal of Agricultural Mechanization Research, 2008(7):8-12, 17.]
[12] 吴建生, 冯喆, 黄力, 等. 基于CLUE-S模型框架的土地可持续利用情景预测——以阳泉市郊区为例[J]. 资源科学, 2011, 33(9):1699-1707[WU J S, FENG Z, HUANG L, et al. CLUE-S based scenario prediction on sustainable land use:a case study of suburban district, Yangquan city[J]. Resources Science, 2011, 33(9):1699-1707.]
[13] 周嵩山, 李红波. 元胞自动机(CA)模型在土地利用领域的研究综述[J]. 地理信息世界, 2012(5):6-10, 13[ZHOU S S, LI H B. The research summary of land use with the model of cellular automata[J]. Geomatics World, 2012(5):6-10, 13.]
[14] 韩超峰, 陈仲新. LUCC驱动力模型研究综述[J]. 中国农学通报, 2008, 24(4):365-368[HAN C F, CHEN Z X. Models for driving forces of land use/cover change:a review[J]. Chinese Agricultural Science Bulletin, 2008, 24(4):365-368.]
[15] 吴文斌, 杨鹏, 柴崎亮介, 等. 基于Agent的土地利用/土地覆盖变化模型的研究进展[J]. 地理科学, 2007, 27(4):573-578[WU W B, YANG P, SHIBASAKI R, et al. Agent-based model for land-use/cover change:a review[J]. Scientia Geographica Sinica, 2007, 27(4):573-578.]
[16] VERBURG P H, EICKHOUT B, VAN MEIJL H. A multi-scale, multi-model approach for analyzing the future dynamics of European land use[J]. The Annals of Regional Science, 2008, 42(1):57-77.
[17] 潘影, 刘云慧, 王静, 等. 基于CLUE-S模型的密云县面源污染控制景观安全格局分析[J]. 生态学报, 2011, 31(2):529-537[PAN Y, LIU Y H, WANG J, et al. Non-point pollution control for landscape conservation analysis based on CLUE-S simulations in Miyun county[J]. Acta Ecologica Sinica, 2011, 31(2):529-537.]
[18] SANTINI M, VALENTINI R. Predicting hot-spots of land use changes in Italy by ensemble forecasting[J]. Regional Environmental Change, 2011, 11(3):483-502.
[19] FOX J, VOGLER J B, SEN O L, et al. Simulating land-cover change in Montane Mainland Southeast Asia[J]. Environmental Management, 2012, 49(5):968-979.
[20] 王建, 田光进, 全泉, 等. 基于CLUS-E模型的广州市土地利用格局动态模拟[J]. 生态学杂志, 2010, 29(6):1257-1262.[WANG J, TIAN G J, QUAN Q, et al. Dynamic simulation of land use pattern in Guangzhou based on CLUE-S model[J]. Chinese Journal of Ecology, 2010, 29(6):1257-1262.]
[21] 王祺, 蒙吉军, 毛煕彦. 基于邻域相关的漓江流域土地利用多情景模拟与景观格局变化[J]. 地理研究, 2014, 33(6):1073-1084[WANG Q, MENG J J, MAO X Y. Scenario simulation and landscape pattern assessment of land use change based on neighborhood analysis and auto-logistic model:a case study of Lijiang River Basin[J]. Geographical Research, 2014, 33(6):1073-1084.]
[22] LI W L, WU C S, ZANG S Y. Modeling urban land use conversion of Daqing City, China:a comparative analysis of "top-down" and "bottom-up" approaches[J]. Stochastic Environmental Research and Risk Assessment, 2014, 28(4):817-828.
[23] 朱康文, 李月臣, 周梦甜. 基于CLUE-S模型的重庆市主城区土地利用情景模拟[J]. 长江流域资源与环境, 2015, 24(5):789-797[ZHU K W, LI Y C, ZHOU M T. Land use scenario simulation of the main city of Chongqing based on the CLUE-S model[J]. Resources and Environment in the Yangtze Basin, 2015, 24(5):789-797.]
[24] 黄方. 重庆市土地利用空间格局分析及其预测模拟[D]. 重庆:重庆大学硕士学位论文, 2013[HUANG F. Analysis and simulation of land use spatial pattern of Chongqing municipality[D]. Chongqing:Master Dissertation of Chongqing University, 2013.]
[25] 杨德生. 重庆市渝北区地表景观格局时空演化及生态环境响应[D]. 成都:成都理工大学博士学位论文, 2011[YANG D S. Landscape spatial-temporal evolution and ecological environment response in Chongqing Yubei district[D]. Chengdu:Doctor Dissertation of Chengdu University of Technology, 2011.]
[26] VERBURG P H, DE NIJS T C M, VAN ECK J R, et al. A method to analyse neighbourhood characteristics of land use patterns[J]. Computers, Environment and Urban Systems, 2004, 28(6):667-690.
[27] VERBURG P H, DE KONING G H J, KOK K, et al. A spatial explicit allocation procedure for modelling the pattern of land use change based upon actual land use[J]. Ecological Modelling, 1999, 116(1):45-61.
[28] 杨娟, 蔡永立, 袁涛. 基于CLUE-S模型的崇明县土地利用变化时空动态模拟研究[J]. 中国农学通报, 2014, 30(11):258-264[YANG J, CAI Y L, YUAN T. Dynamic simulation on the spatio-temporal patterns of land use changes in Chongming County based on CLUE-S model[J]. Chinese Agricultural Science Bulletin, 2014, 30(11):258-264.]
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