Journal of Jilin University(Earth Science Edition) ›› 2019, Vol. 49 ›› Issue (6): 1795-1804.doi: 10.13278/j.cnki.jjuese.20180312

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Dynamic Change and Predictive Analysis of Land Use Types in Changchun City Based on FLUS Model

Wang Mingchang1,2, Guo Xin1, Wang Fengyan1, Zhang Xinyue1   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Land and Resources, Shenzhen 518000, Guangdong, China
  • Received:2018-11-27 Published:2019-11-30
  • Supported by:
    Supported by National Natural Science Foundation of China(41430322),Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources(KF-2018-03-020)and the Opening Fund of Key Laboratory of Land Subsidence Monitoring and Prevention,Ministry of Land and Resources of China (KLLSMP201901)

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Abstract: Studying the pattern and driving factors of urban and rural land use change is conducive to the sustainable development of regional land resources. Taking Changchun City as an example, combined with manual interpretation, the overall accuracy of the Landsat satellite supervised classification images in 1997, 2007 and 2017, is 93.06%, 90.70%,and 94.12%, respectively. From 1997 to 2017, the grassland, cultivated land and other land area decreased by 354.74 km2, 922.11 km2,and 55.35 km2 respectively, and the construction land, water area, and forest land increased by 1 154.14 km2, 70.38 km2, and 107.54 km2 respectively. The overall trend is that the construction land expanded to the periphery and encroached on the area of other land types. Based on the 2007 classification data, combined with the driving factors of land use change of terrain, traffic location and social economy, the land use pattern was simulated for 2017 with FLUS (future land use simulation) model. The simulation is in good agreement with the real results. The simulation accuracy is 85.10%, Kappa coefficient is 0.821 2, and the verification model and the driving factors are reliable and consistent with the trend of land use change. The model is used to predict the land use pattern of 2027, showing that the construction land will slowly invade the area of cultivated land, forest land, grassland and other land around the town, and the area of forest land and water will increase.

Key words: dynamic change, FLUS model, scenario simulation, predictive analysis, Changchun City

CLC Number: 

  • P237
[1] 赵冬玲,杜萌,杨建宇,等.基于CA-Markov模型的土地利用演化模拟预测研究[J].农业机械学报, 2016, 47(3):278-285. Zhao Dongling, Du Meng, Yang Jianyu, et al. Simulation and Forecast Study of Land Use Change Based on CA-Markov Model[J]. Transactions of the Chinese Society for Agricultural Machinery, 2016, 47(3):278-285.
[2] Lu J, Guldmann J. Landscape Ecology, Land-Use Structure, and Population Density:Case Study of the Columbus Metropolitan Area[J]. Landscape and Urban Planning, 2012,105(1/2):74-85.
[3] Clark M L, Aide T M, Riner G. Land Change for All Municipalities in Latin America and the Caribbean Assessed from 250 m MODIS Imagery (2001-2010)[J]. Remote Sensing of Environment, 2012, 126:84-103.
[4] Lambin E F, Geist H J, Lepers E. Dynamics of Land-Use and Land-Cover Change in Tropical Regions[J]. Annual Review of Environment and Resources, 2003, 28:205-241.
[5] Anil A P, Ramesh H. Analysis of Climate Trend and Effect of Land Use Land Cover Change on Harangi Stream-Flow, SouthIndia:A Case Study[J]. Sustainable Water Resources Management, 2017, 3(3):257-267.
[6] 王明常,何月,许军强,等.基于GIS的长白山景观格局演化信息图谱分析[J]. 测绘科学, 2008, 33(6):33-35. Wang Mingchang, He Yue, Xu Junqiang, et al. Analysis on Geo-Info-Spectrum of Landscape Pattern Evolvement in Changbai Mountain Based on GIS[J]. Science of Surveying and Mapping, 2008, 33(6):33-35.
[7] Mu J E, Sleeter B M, Abatzoglou J T, et al. Climate Impacts on Agricultural Land Use in the USA:The Role of Socio-Economic Scenarios[J]. Climatic Change, 2017, 144(2):329-345.
[8] 崔敬涛.基于Logistic-CA-Markov模型的临沂市土地利用变化模拟预测研究[D].南京:南京大学,2014. Cui Jingtao. Simulation and Prediction of Land Use Change in Linyi City Based on Logistic-CA-Markov Model[D]. Nanjing:Nanjing University, 2014.
[9] 王明常,牛雪峰,杨毅恒,等.长白山地区景观格局过程模拟预测研究[J].吉林大学学报(地球科学版),2009, 39(5):947-952. Wang Mingchang, Niu Xuefeng, Yang Yiheng, et al. Simulation and Predicted Research on Changbai Mountain Landscape Pattern Process[J]. Journal of Jilin University (Earth Science Edition), 2009, 39(5):947-952.
[10] 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.
[11] 黎夏,刘小平,何晋强,等.基于耦合的地理模拟优化系统[J].地理学报,2009,64(8):1009-1018. Li Xia, Liu Xiaoping, He Jinqiang, et al. A Geographical Simulation and Optimization System Based on Coupling Strategies[J]. Acta Geographica Sinica, 2009, 64(8):1009-1018.
[12] Liu X P, Liang X, Li X, et al. A Future Land Use Simulation Model (FLUS) for Simulating Multiple Land Use Scenarios by Coupling Human and Natural Effects[J]. Landscape and Urban Planning, 2017, 168:94-116.
[13] 王秀兰.土地利用/土地覆盖变化中的人口因素分析[J].资源科学,2000,22(3):39-42. Wang Xiulan. Analysis on Demographic Factors and Land Use/Land Cover Change[J]. Resources Science, 2000, 22(3):39-42.
[14] 孟祥萍,王圣镔,王欣欣.基于蚁群算法和轮盘算法的多AgentQ学习[J].计算机工程与应用,2009,45(16):60-62. Meng Xiangping, Wang Shengbin, Wang Xinxin. Multiagent Q-Learning Based on Ant Colony Algorithm and Roulette Algorithm[J]. Computer Engineering and Applications, 2009,45(16):60-62.
[15] 骆剑承,周成虎,杨艳.人工神经网络遥感影像分类模型及其与知识集成方法研究[J].遥感学报,2001,5(2):122-129. Luo Jiancheng, Zhou Chenghu, Yang Yan. ANN Remote Sensing Classification Model and Its Integration Approach with Geo-Knowledge[J]. Journal of Remote Sensing, 2001, 5(2):122-129.
[16] 范晓锋.基于ANN-CA模型的珲春市土地利用格局模拟研究[D].长春:吉林大学,2016. Fan Xiaofeng. The Simulation Study of the Land Use Pattern of Hunchun City Based on the Model ANN-CA[D].Changchun:Jilin University, 2016.
[17] 张宝光.人工神经网络在遥感数字图像分类处理中的应用[J].国土资源遥感,1998(1):23-29. Zhang Baoguang. The Application of Artificial Neural Network to Classification Processing of Remote Sensing Digital Images[J]. Remote Sensing for Land & Resources, 1998(1):23-29.
[18] 朱光明.长春市土地利用结构变化及优化研究[D].长春:东北师范大学,2012. Zhu Guangming. Research on Land Use Structure Change and Optimization in Changchun[D]. Changchun:Northeast Normal University, 2012.
[19] 王雪微,王士君,宋飏,等.长春市城市建设用地演进的空间识别及影响机制研究[J].地理科学,2015,35(7):873-881. Wang Xuewei, Wang Shijun, Song Yang, et al. Space Recognition and Influence Mechanism of Urban Construction[J].Scientia Geographica Sinica, 2015, 35(7):873-881.
[20] 赵永超.天津市土地利用动态变化及预测分析[D].北京:中国地质大学(北京),2017. Zhao Yongchao. Land Use Dynamic Change and Forecast Analysis in Tianjin[D]. Beijing:China University of Geosciences(Beijing), 2017.
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