[1]黄 强,黄 海*,刘 学.基于混合蛙跳算法的土地利用空间格局优化[J].山地学报,2018,(01):163-170.[doi:10.16089/j.cnki.1008-2786.000312]
 HUANG Qiang,HUANG Hai*,LIU Xue.Optimization of Land Use Spatial Pattern Based on Shuffled Frog Leaping Algorithm[J].Mountain Research,2018,(01):163-170.[doi:10.16089/j.cnki.1008-2786.000312]
点击复制

基于混合蛙跳算法的土地利用空间格局优化()
分享到:

《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2018年01期
页码:
163-170
栏目:
山地技术
出版日期:
2018-01-30

文章信息/Info

Title:
Optimization of Land Use Spatial Pattern Based on Shuffled Frog Leaping Algorithm
文章编号:
1008-2786-(2018)1-153-08
作者:
黄 强黄 海*刘 学
重庆交通大学 地理信息与国土资源系,重庆400074
Author(s):
HUANG Qiang HUANG Hai* LIU Xue
Department of geographic information and land resources, Chongqing Jiaotong University, Chongqing 400074, China
关键词:
土地利用规划 混合蛙跳算法 土地利用格局优化 重庆 渝北区
Keywords:
land use planning Shuffled Frog Leaping Algorithm(SFLA) optimization of land use spatial pattern Yubei district Chongqing
分类号:
F301.23
DOI:
10.16089/j.cnki.1008-2786.000312
文献标志码:
A
摘要:
针对传统优化模型难以将土地利用数量结构与空间布局优化有效统一的问题,本文提出基于混合蛙跳算法的土地利用优化模型,以地理栅格为基本操作单元,引入首尾排序分组、智能学习算子与变异算子改进算法,实现土地利用空间格局优化。以重庆市渝北区2016年的土地利用数据对2030年土地利用空间格局进行优化,优化前生态系统服务价值为2.012×109元,优化后为2.099×109元,区域经济总产出优化前为1.263×1011元,优化后为2.148×1011元,土地利用集约度优化前为0.654,优化后为0.812,增长幅度分别为4.3%、70.1%、26.3%。研究表明利用混合蛙跳算法建立土地利用优化模型,能够在多个优化目标与限制条件下,同时进行土地利用数量与空间格局优化,具有较强的全局寻优能力与较快的收敛速度。
Abstract:
In traditional models, there has been difficulty in effectively optimization of both quantity structure and spatial pattern for land use.This paper put forward a land use optimization model by Shuffled Frog Leaping Algorithm(SFLA).This model was constructed based on geographic grid cells, with a head-to-tail sorting group method, intelligent learning and mutation operators were introduced to improve the algorithm, and the Yubei district of Chongqing city was taken as a case study.The land use spatial pattern of study area in 2030 was optimized by the model, with its land use data in 2016.The value of ecosystem services in this region was 2.012×109 Yuan before optimization, whereas the number increased to 2.099×109 Yuan after the optimization.The gross economic output before and after optimization was 1.263×1011 Yuan and 2.148×1011 Yuan respectively.The land use intensity before and after optimization was 0.654 and 0.812 respectively.The growth rates of ecosystem services value, gross economic output and land use intensity were 4.3%, 70.1% and 26.3% respectively.The result showed that land use optimization model based on the SFLA could effectively optimize the quantity structure and spatial pattern of land use at the same time under several optimization objectives and restrictive factors.This method was proved to possess strong global optimization ability and fast convergence.

参考文献/References:

[1] YANG X, ZHENG X Q, LV L N.A spatiotemporal model of land use change based on ant colony optimization, Markov chain and cellular automata [J].Ecological Modelling, 2012, 233(2):11-19
[2] ARSANJANI J C, KAINZ W, MOUSIVAND A J.Tracking dynamic land-use change using spatially explicit Markov chain based on cellular automata: the case of Tehran[J].International Journal of Image & Data Fusion, 2011, 2(4):329-345
[3] PARKER D C, MANSON S M, JANSSEN M A, et al.Multi-agent systems for the simulation of land-use and land-cover change: areview[J].Annals of the Association of American Geographers, 2003, 93(2):314-337
[4] LE Quangbao, PARK S J, VLEK P L G.Land Use Dynamic Simulator(LUDAS): A multi-agent system model for simulating spatio-temporal dynamics of coupled human-landscape system [J].Ecological Informatics, 2010, 5(3):203-221
[5] AERTS J C J H, EISINGER E, HEUVELINK G B M, et al.Using linear integer programming for multi-site land-use allocation[J].Geographical Analysis, 2003, 35(2):148-169
[6] SADEGHI S H R,JALILI K, NIKKAMI D.Land use optimization in watershed scale[J].Land Use Policy, 2009, 26(2):186-193
[7] INESSR, MARCOS B M, RAFAEL C M, et al.Algorithm based on simulated annealing for land-use allocation[J].Computers & Geosciences, 2008, 34(3):259-268
[8] DUHJD, BROWN DG.Knowledge-informed Pareto simulated annealing for multi-objective spatial allocation[J].Computers Environment & Urban Systems, 2007, 31(3):253-281
[9] 郭小燕,刘学录,王联国.基于混合蛙跳算法的土地利用格局优化[J].农业工程学报,2015,31(24):281-288[GUO Xiaoyan, LIU Xuelu, WANG Lianguo.Land use pattern optimization based on shuffled frog leaping algorithm[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(24):281-288]
[10] 赵东娟,齐伟,赵胜亭,曲衍波.基于GIS的山区县域土地利用格局优化研究[J].农业工程学报,2008,24(2): 101-106[ZHAO Dongjuan, QI Wei, ZHAO Shengting, et al.Landuse pattern optimization in mountainous areas at county level based on GIS[J].Transactions of the CSAE, 2008,24(2):101-106]
[11] 许泉立, 杨昆, 王桂林,等.基于蚁群算法的洱海流域土地利用变化模拟[J].农业工程学报, 2014, 30(19):290-299 [XU Quanli, YANG Kun, WANG Guilin, et al.Simulation of land use change of Erhai Lake Basin based on antcolony optimization[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE), 2014,30(19):290-299]
[12] 马世发, 何建华, 俞艳.基于粒子群算法的城镇土地利用空间优化模型[J].农业工程学报, 2010, 26(9):321-326[MA Shifa, HE Jianhua, YU Yan.Model of urban land-use spatial optimization based on particle swarm optimization algorithm[J].Transactions of the CSAE, 2010, 26(9):321-326]
[13] 张鸿辉,曾永年,刘慧敏.多目标土地利用空间优化配置模型及其应用[J].中南大学学报(自然科学版),2011,42(04):1056-1065 [ZHANG Honghui, ZENG Yongnian, LIU Huimin.Multi-objective spatial optimization model for land use allocation and its application[J].Journal of Central South University(Science and Technology),2011,42(04):1056-1065]
[14] 袁满, 刘耀林.基于多智能体遗传算法的土地利用优化配置[J].农业工程学报, 2014, 30(1):191-199[YUAN Man, LIU Yaolin.Land use optimization allocation based on multi-agent genetic algorithm[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2014,30(1):191-199]
[15] XU Q L, YANG K, WANG GL, et al.Agent-based modeling and simulations of land-use and land-cover change according to ant colony optimization: a case study of the Erhai Lake Basin, China[J].Natural Hazards, 2015, 75(1):95-118
[16] DUAN H B, WANG D B, ZHU J Q, et al.Development on ant colony algorithm theory and its application[J].Control & Decision, 2004, 19(12):1321-1320
[17] 许方, 张桂珠.一种改进的混合蛙跳和K均值结合的聚类算法[J].计算机工程与应用, 2016, 49(1):176-180[XU Fang, ZHANG Guizhu.Clustering algorithm based on modified shuffled frog leaping algorithm and k-means[J].Computer Engineering and Applications,2013,49(1):176-180]
[18] EUSUFF M M, LANSEY K E.LANSEYK.Optimization of water distribution network design using the shuffled frog leaping algorithm[J].Journal of Water Resources Planning & Management, 2003, 129(3):210-225
[19] SUN P, JIANG Z Q, WANG T T, et al.Research and application of parallel normal cloud mutation shuffled frog leaping algorithm in cascade reservoirs optimal operation[J].Water Resources Management, 2016, 30(3):1-17
[20] JORDAAN J A, ZIVANOVIC R.Frequency estimation in power systems using the Dynamic Leapfrog method[J].Measurement, 2006, 39(5):451-457
[21] ZHONG Q, XUE S,WANG Z, et al.Environmental and economic dispatch model for smart microgrid based on shuffled frog leap algorithm optimized by random nelder mead[J].Przeglad Elektrotechniczny,2016,89(3):147-151
[22] HENSHALL P, PALMER P.A leapfrog algorithm for coupled conductive and radiative transient heat transfer in participating media[J].International Journal of Thermal Sciences, 2008, 47(4):388-398
[23] EUSUFF M,LANSEY K, PASHA F.Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization [J].Engineering Optimization, 2006, 38(2):129-154
[24] 武汉大学.一种土地利用空间布局人工免疫优化模型的并行化方法: 201610424814.3[P].2016-12-11.
[25] 张佰林, 杨庆媛, 鲁春阳,等.不同经济发展阶段区域土地利用变化及对经济发展的影响--以重庆市40个区县为例[J].经济地理, 2011, 31(9):1539-1544[ZHANG Bailin, YANG Qingyuan, LU Chunyang, et al.Effect on economic development of regional land use change in different development phase: forty counties in chongqing as the research object[J].Economic Geography,2011,31(9):1539-1544]
[26] 王晓妹, 吴九兴.区域土地集约利用程度及其时空差异研究--以安徽省11个地级市为样本[J].土壤通报, 2016, 47(6):1294-1299[WANG Xiaomei, WU Jiuxing.Analysis on regional land intensive utilization degree of regional land, and its temporal and spatial difference variation: taking the 11 prefecture-level cities in Anhui province as samples [J].Chinese Journal of Soil Science,2016, 47(6):1294-1299]
[27] NELSON E, MENDOZA G, REGETZ J, et al.Modeling multiple ecosystem services, biodiversity conservation, commodity production, and tradeoffs at landscape scales[J].Frontiers in Ecology & the Environment, 2009, 7(1):4-11
[28] 谢莹, 匡鸿海, 吴晶晶,等.基于CLUE-S模型的重庆市渝北区土地利用变化动态模拟[J].长江流域资源与环境, 2016, 25(11):1729-1737[XIE Ying, KUANG Honghai, WU Jingjing, et al.Dynamic simulation of land use change in yubei district of chongqing based on CLUE-S model[J].Resources and Environment in the Yangtze Basin,2016,25(11):1729-1737]
[29] 李伯虎, 柴旭东, 朱文海,等.现代建模与仿真技术发展中的几个焦点[J].系统仿真学报, 2004, 16(9):1871-1878[LI Bohu, CHAI Xudong, ZHU Wenhai, et al.Some focusing points in development of modern modeling and simulation technology[J].Journal of Systems Simulation,2004,16(9):1871-1878]
[30] 传俊,黄红兵,金士尧.基于涌现视角的MAS信任模型仿真分析方法[J].计算机研究与发展,2010,47(12):2090-2099[CUAN Jun, HUANG Hongbing, JIN Shiyao.A simulation approach based on the notion of emergence for analyzing MAS trust model[J].Journal of Computer Research and Development,2010,47(12):2090-2099]

备注/Memo

备注/Memo:
收稿日期(Received date):2017-06-07; 改回日期(Accepted date):2017-11-8
基金项目(Foundation item):重庆市教委项目(15SKG089)。[Chongqing Municipal Education Commission Project(15SKG089)]
作者简介(Biography):黄强(1993-),男,重庆云阳人,硕士生,主要从事土地利用规划与GIS应用研究。[Huang Qiang(1993-), male, born in Yunyang, Chongqing, M.Sc.candidate, research on land use planning and GIS] E-mail: 1296190476@qq.com
*通讯作者(Corresponding author):黄海(1972-),男,重庆梁平人,博士,副教授,主要从事土地评价、规划与GIS应用研究。[Huang Hai(1972-), male, born in Liangping, Chongqing, Ph.D., associate professor, specialized in land evaluation and planning, and application of GIS] E-mail: lottery98@163.com
更新日期/Last Update: 2018-01-30