基于最坏情景理论的连云港土地利用变化情景模拟
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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 km~2,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。
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 km~2;(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.
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 km~2;(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.
引文
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[2]李亦秋,邓欧,张冬有,等.丹江口库区土地利用及其生态系统服务价值情景模拟[J].农业工程学报,2011,27(5):329-335.[Li Y Q,Deng O,Zhang D Y,et al.Land use and ecosystem service value scenarios simulation in Danjiangkou Reservoir Area[J].Transactions of the Chinese Society of Agricultural Engineering,2011,27(5):329-335.]
[3]Chen L G,Yang X Y,Chen L Q,et al.Impact assessment of land use planning driving forces on environment[J].Environmental Impact Assessment Review,2015,55:126-135.
[4]Chen L G,Yang X Y,Chen L Q,et al.A state-impact-state methodology for assessing environmental impact in land use planning[J].Environmental Impact Assessment Review,2014,46(4):1-12.
[5]许小娟,刘会玉,林振山,等.基于CA-MARKOV模型的江苏沿海土地利用变化情景分析[J].水土保持研究,2017,24(1):213-218.[Xu X J,Liu H Y,Lin Z S,et al.Scenario Analysis of land use change in Jiangsu coast based on CA-Markov model[J].Research of Soil and Water Conservation,2017,24(1):213-218.]
[6]曾永年,靳文凭,王慧敏,等.青海高原东部土地利用变化模拟与景观生态风险评价[J].农业工程学报,2014,30(4):185-194.[Zeng Y N,Jin W P,Wang H M,et al.Simulation of land-use changes and landscape ecological assessment in eastern part of Qinghai Plateau[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(4):185-194.]
[7]刘明皓,李东鸿.ANN-CA模型改进及城市用地动态模拟[J].重庆邮电大学学报(自然科学版),2014,26(5):720-726.[Liu M H,Li D H.Simulation of urban land use change based on the improved ANN-CA[J].Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition),2014,26(5):720-726.]
[8]何丹,金凤君,周璟.基于Logistic-CA-Markov的土地利用景观格局变化:以京津冀都市圈为例[J].地理科学,2011,31(8):903-910.[He D,Jin F J,Zhou J.The changes of land use and landscape pattern based on Logistic-CA-Markov model:A case study of Beijing-Tianjin-Hebei metropolitan region[J].Scientia Geographica Sinica,2011,31(8):903-910.]
[9]邓祥征,刘纪远,战金艳,等.区域土地利用变化的多情景分析:以内蒙古自治区太仆寺旗为例[J].地球信息科学,2004,6(1):81-88.[Deng X Z,Liu J Y,Zhan J Y,et al.Scenarios analyses on the spatio-temporal patterns of land use change:A case study in Taips County of Inner Mongolia[J].Geo-information Science,2004,6(1):81-88.]
[10]刘小平,黎夏,艾彬,等.基于多智能体的土地利用模拟与规划模型[J].地理学报,2006,61(10):1101-1112.[Liu X P,Li X,Ai B,et al.Multi-agent systems for simulating and planning land use development[J].Acta Geographica Sinica,2006,61(10):1101-1112.]
[11]马金卫,吴晓青,周迪,等.海岸带城镇空间扩展情景模拟及其生态风险评价[J].资源科学,2012,34(1):185-194.[Ma J W,Wu X Q,Zhou D,et al.Scenario simulation of urban spatial expansion and its ecological risks assessment in coastal zones[J].Resources Science,2012,34(1):185-194.]
[12]刘瑾,田永中,田林,等.快速城镇化区域用地扩张模拟的规划约束对比研究[J].地理与地理信息科学,2019,35(1):82-88.[Liu J,Tian Y Z,Tian L,et al.A comparative study on planning constraints of the rapid urbanization area expansion simulation[J].Geography and Geo-Information Science,2019,35(1):82-88.]
[13]李靖,廖和平,蔡进.基于风险评价的低丘缓坡土地开发建设适宜性情景模拟:以重庆市巴南区为例[J].资源科学,2018,40(5):967-979.[Li J,Liao H P,Cai J.Simulation of utilization and construction suitability of gentle hillsides based on risk evaluation in Banan District of Chongqing[J].Resources Science,2018,40(5):967-979.]
[14]李益敏,管成文,郭丽琴,等.基于生态敏感性分析的江川区土地利用空间格局优化配置[J].农业工程学报,2018,34(20):267-276.[Li Y M,Guan C W,Guo L Q,et al.Optimization of land use spatial pattern in Jiangchuan District based on ecological sensitivity analysis[J].Transactions of the Chinese Society of Agricultural Engineering,2018,34(20):267-276.]
[15]陈龙高,李英奎,陈龙乾,等.土地生态利用视角下的连云港空间管制分区研究[J].应用基础与工程科学学报,2014,22(4):685-697.[Chen L G,Li Y K,Chen L Q,et al.Spatial regulation zoning of Lianyungang City:A perspective from the ecological land-use management[J].Journal of Basic Science and Engineering,2014,22(4):685-697.]
[16]Mccready D.Development and communication of worst-case scenarios for the EPA risk management program[J].Process Safety Progress,1996,15(2):95-103.
[17]Schneider S.The worst-case scenario[J].Nature,2009,458(7242):1104-1105.
[18]Chen L G,Li L,Yang X Y,et al.A worst-case scenario based methodology to assess the environmental impact of land use planning[J].Habitat International,2017,67:148-163.
[19]张斌,雍岐东,肖芳淳.模糊物元分析[M].北京:石油工业出版社,1997.[Zhang B,Yong Q D,Xiao F C.Fuzzy-Material Element Analysis[M].Beijing:Petroleum Industry Press,1997.]
[20]蔡文.物元分析[M].广州:广东高等教育出版社,1987.[Cai W.Matter Element Analysis[M].Guangzhou:Guangdong Higher Education Publishing House,1987.]
[21]赵海涛,张兵,左正立,等.中国及周边区域ASTER GDEM与SRTM DEM高程对比分析及互补修复[J].测绘科学,2012,37(1):8-11.[Zhao H T,Zhang B,Zuo Z L,et al.Elevation comparison and complementary repair of ASTER GDEM and SRTM DEMin China and surrounding areas[J].Science of Surveying and Mapping,2012,37(1):8-11.]
[22]Yang X Y,Li L,Chen L G,et al.Improving ASTER GDEM accuracy using land use-based linear regression methods:A case study of Lianyungang,east China[J].ISPRS International Journal of Geo-Information,2018,DOI:10.3390/ijgi7040145.
[23]连云港市统计局.连云港统计年鉴[M].北京:中国统计出版社,2001-2017.[Lianyungang Statistical Bureau.Lianyungang Statistical Year Report[M].Beijing:China Statistical Publishing House,2001-2017.]
[24]中华人民共和国住房和城乡建设部.CJJ 83-2016城乡建设用地竖向规划规范[M].北京:中国建筑工业出版社,2016.[Ministry of Housing and Urban-Rural Construction of the People’s Republic of China.CJJ 83-2016 China’s Criterion for Vertical Planning of Urban Land Use[M].Beijing:China Architecture&Building Press,2016.]
[25]全国农业区划委员会.土地利用现状调查技术规程[EB/OL].(1984-09-08)[2018-10-17].https://wenku.baidu.com/view/5b1411a8905f804d2b160b4e767f5acfa0c78306.html.[National Commission for Agricultural Regionalization.China’s Technical Regulation for Land Use Investigation[EB/OL].(1984-09-08)[2018-10-17].https://wenku.baidu.com/view/5b1411a8905f804d2b160b4e767f5acfa0c78306.html.]
[26]苏珊.基于GIS的海口市建设用地生态适宜性评价[D].海口:海南师范大学,2013.[Su S.GIS Based Evaluation on Ecological Suitability of Construction Land Use in Haikou City[D].Haikou:Hainan Normal University,2013.]
[27]张丽娟,姜蓝齐,张学珍,等.19世纪末黑龙江省的耕地覆盖重建[J].地理学报,2014,69(4):448-458.[Zhang L J,Jiang L Q,Zhang X Z,et al.Reconstruction of cropland over Heilongjiang Province in the late 19th century[J].Acta Geographica Sinica,2014,69(4):448-458.]
[28]岑湘荣.基于GIS的城镇建设用地生态适宜性评价研究[D].长沙:中南大学,2008.[Cen X R.Evaluating Ecological Suitability for Construction Land Using Geographical Information System[D].Changsha:Central South University,2008.]
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