基于自组织映射法的时间序列土地利用变化的时空可视化
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摘要
精细尺度下多时间序列土地利用时空演变分析是当前研究的一个趋势,本研究基于2005、2007、2009、2011、2013年5期土地利用数据采用自组织映射方法分析了北京市乡镇级多时间序列土地利用的时空演变规律,实现了乡镇尺度下多时间序列土地利用数据的时空一体化表达和对比分析。通过构建自组织映射神经网络,利用其聚类和降维可视化功能对5个监测时期的土地利用数据同时进行训练,在其输出面板可以发现不同土地利用类型的分布聚集模式以及相互之间的结构比例关系,并对输出神经元进行二次聚类以及土地利用变化轨迹分析,展示出北京市乡镇级5个监测时相的土地利用时空演变规律。结果揭示出北京市平原区、山区及二者过渡的山前结合带的各自不同的土地利用时空变化轨迹与模式:北京市平原区向高建设用地比例的土地利用结构方向演变,山区向高林地比例的土地利用结构方向演变,而山前结合带的土地利用时空演变较为复杂。
Analysis of multiple time series land use of spatio-temporal evolution at fine scale is a hot and important research area currently. In this study, the self-organizing map(SOM)neural network was used to analyze the land use spatio-temporal distribution at township-level in Beijing. The study was based on 5 periods of land use classification data of Beijing in 2005, 2007, 2009, 2011 and 2013. We implemented spatio-temporal integrated expression and comparative analysis of multiple time series land use data at township-level. Through creating and training self-organizing map neural network, we could find out the distribution of different land use types(built-up land, farmland, forest land, grassland, garden, water, and unused land)on the SOM output plane.This represented the proportional relationship of different land use types in land use structure. By second-step clustering and building land use change trajectory, we got the spatio-temporal evolution rules of the land use in township of Beijing. The results revealed that there were five land use change trajectories and three spatiotemporal evolution patterns in Beijing at township level. The plain area is developing to the land use structure of high built-up land proportion. The mountainous area is developing to the land use structure of high forest land proportion, and the land use change of piedmont zone is complex.
Analysis of multiple time series land use of spatio-temporal evolution at fine scale is a hot and important research area currently. In this study, the self-organizing map(SOM)neural network was used to analyze the land use spatio-temporal distribution at township-level in Beijing. The study was based on 5 periods of land use classification data of Beijing in 2005, 2007, 2009, 2011 and 2013. We implemented spatio-temporal integrated expression and comparative analysis of multiple time series land use data at township-level. Through creating and training self-organizing map neural network, we could find out the distribution of different land use types(built-up land, farmland, forest land, grassland, garden, water, and unused land)on the SOM output plane.This represented the proportional relationship of different land use types in land use structure. By second-step clustering and building land use change trajectory, we got the spatio-temporal evolution rules of the land use in township of Beijing. The results revealed that there were five land use change trajectories and three spatiotemporal evolution patterns in Beijing at township level. The plain area is developing to the land use structure of high built-up land proportion. The mountainous area is developing to the land use structure of high forest land proportion, and the land use change of piedmont zone is complex.
引文
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[14]王谦.基于乡镇尺度的大冶市LUCC及其景观格局变化研究[D].南宁:广西师范学院,2014.[Wang Q.Studies on land use/land cover change and landscape pattern change of town level in Daye city based on RS and GIS[D].Nanning:Guangxi Teachers Education University,2014.]
[15]Long H,Tang G,Li X,et al.Socio-economic driving forces of land-use change in Kunshan,the Yangtze River Delta economic area of China[J].Journal of Environmental Management,2007,83(3):351-364.
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[17]黄勇,王凤友,蔡体久,等.环渤海地区景观格局动态变化轨迹分析[J].水土保持学报,2015,29(2):314-319.[Huang Y,Wang F Y,Cai T J,et al.Landscape pattern dynamic analysis based on change trajectory method in Bohai rim area[J].Journal of Soil and Water Conservation,2015,29(2):314-319.]
[18]Feng H,Zhao X,Chen F,et al.Using land use change trajectories to quantify the effects of urbanization on urban heat island[J].Advances in Space Research,2014,53(3):463-473.
[19]Lee A C D,Rinner C.Visualizing urban social change with self-organizing maps:Toronto neighbourhoods,1996-2006[J].Habitat International,2015,45:92-98.
[20]Augustijn E,Zurita-Milla R.Self-organizing maps as an approach to exploring spatiotemporal diffusion patterns[J].International Journal of Health Geographics,2013,12(1):1-14.
[21]Chen N,Ribeiro B,Vieira A,et al.Clustering and visualization of bankruptcy trajectory using self-organizing map[J].Expert Systems with Applications,2013,40(1):385-393.
[22]Kohonen T.Self-organized formation of topologically correct feature maps[J].Biological Cybernetics,1982,43(1):59-69.
[23]Ju H,Zhang Z,Zuo L,et al.Driving forces and their interactions of built-up land expansion based on the geographical detector-a case study of Beijing,China[J].International Journal of Geographical Information Science,2016,30(11):1-20.
[2]鲁春阳,杨庆媛,靳东晓,等.中国城市土地利用结构研究进展及展望[J].地理科学进展,2010,29(7):861-868.[Lu C Y,Yang Q Y,Jin D X,et al.Research progress and prospects of the researches on urban land use structure in China[J].Progress in Geography,2010,29(7):861-868.]
[3]Sun J,Zhang L,Peng C,et al.CA-based urban land use prediction model:A case study on orange county,Florida,U.S.[J].Journal of Transportation Systems Engineering and Information Technology,2012,12(6):85-92.
[4]Liu H,Zhou Q.Developing urban growth predictions from spatial indicators based on multi-temporal images[J].Computers,Environment and Urban Systems,2005,29(5):580-594.
[5]冯健.杭州城市形态和土地利用结构的时空演化[J].地理学报,2003,58(3):343-353.[Feng J.Spatial-temporal evolution of urban morphology and land use structure in Hangzhou[J].Acta Geographica Sinica,2003,58(3):343-353.]
[5]Estoque R C,Murayama Y.Spatio-temporal urban land use/cover change analysis in a hill station:The case of Baguio city,Philippines[J].Procedia-Social and Behavioral Sciences,2011,21:326-335.
[7]Wu J,Jenerette G D,Buyantuyev A,et al.Quantifying spatiotemporal patterns of urbanization:The case of the two fastest growing metropolitan regions in the United States[J].Ecological Complexity,2011,8(1):1-8.
[8]徐丽华,王欢欢,张结存,等.近15年来杭州市土地利用结构的时空演变[J].经济地理,2014,34(7):135-142.[Xu L H,Wang H H,Zhang J C,et al.Spatial-temporal dynamics of land use in the Hangzhou city during the recent 15years[J].Economic Geography,2014,34(7):135-142.]
[9]鲁春阳,文枫,杨庆媛,等.地级以上城市土地利用结构特征及影响因素差异分析[J].地理科学,2011,31(5):600-607.[Lu C Y,Wen F,Yang Q Y,et al.Characteristics and driving factors of urban land use structure of cities at provincial level and above[J].Scientia Geographica Sinica,2011,31(5):600-607.]
[10]Deng J S,Wang K,Hong Y,et al.Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization[J].Landscape and Urban Planning,2009,92(3-4):187-198.
[11]周生路,朱青,赵其国.近十几年来南京市土地利用结构变化特征研究[J].土壤,2005,37(4):394-399.[Zhou S L,Zhu Q,Zhao Q G.Variation of land-use structure in Nanjing over the last decade[J].Soils,2005,37(4):394-399.]
[12]Tan R,Liu Y,Zhou K,et al.A game-theory based agentcellular model for use in urban growth simulation:A case study of the rapidly urbanizing Wuhan area of central China[J].Computers,Environment and Urban Systems,2015,49:15-29.
[13]Yang X,Zheng X,Lv L.A spatiotemporal model of land use change based on ant colony optimization,Markov chain and cellular automata[J].Ecological Modelling,2012,233:11-19.
[14]王谦.基于乡镇尺度的大冶市LUCC及其景观格局变化研究[D].南宁:广西师范学院,2014.[Wang Q.Studies on land use/land cover change and landscape pattern change of town level in Daye city based on RS and GIS[D].Nanning:Guangxi Teachers Education University,2014.]
[15]Long H,Tang G,Li X,et al.Socio-economic driving forces of land-use change in Kunshan,the Yangtze River Delta economic area of China[J].Journal of Environmental Management,2007,83(3):351-364.
[16]Fan Q,Ding S.Landscape pattern changes at a county scale:A case study in Fengqiu,Henan Province,China from 1990 to 2013[J].CATENA,2016,137:152-160.
[17]黄勇,王凤友,蔡体久,等.环渤海地区景观格局动态变化轨迹分析[J].水土保持学报,2015,29(2):314-319.[Huang Y,Wang F Y,Cai T J,et al.Landscape pattern dynamic analysis based on change trajectory method in Bohai rim area[J].Journal of Soil and Water Conservation,2015,29(2):314-319.]
[18]Feng H,Zhao X,Chen F,et al.Using land use change trajectories to quantify the effects of urbanization on urban heat island[J].Advances in Space Research,2014,53(3):463-473.
[19]Lee A C D,Rinner C.Visualizing urban social change with self-organizing maps:Toronto neighbourhoods,1996-2006[J].Habitat International,2015,45:92-98.
[20]Augustijn E,Zurita-Milla R.Self-organizing maps as an approach to exploring spatiotemporal diffusion patterns[J].International Journal of Health Geographics,2013,12(1):1-14.
[21]Chen N,Ribeiro B,Vieira A,et al.Clustering and visualization of bankruptcy trajectory using self-organizing map[J].Expert Systems with Applications,2013,40(1):385-393.
[22]Kohonen T.Self-organized formation of topologically correct feature maps[J].Biological Cybernetics,1982,43(1):59-69.
[23]Ju H,Zhang Z,Zuo L,et al.Driving forces and their interactions of built-up land expansion based on the geographical detector-a case study of Beijing,China[J].International Journal of Geographical Information Science,2016,30(11):1-20.