Evolutionary driving mechanism of greenspace in central Beijing City based on the PLSR model

Li Fangzheng; Xie Shuang; Li Xiong

doi:10.13332/j.1000-1522.20180250

Journal of Beijing Forestry University > 2019 > 41(4): 116-126. > DOI: 10.13332/j.1000-1522.20180250

Li Fangzheng, Xie Shuang, Li Xiong. Evolutionary driving mechanism of greenspace in central Beijing City based on the PLSR model[J]. Journal of Beijing Forestry University, 2019, 41(4): 116-126. DOI: 10.13332/j.1000-1522.20180250

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Evolutionary driving mechanism of greenspace in central Beijing City based on the PLSR model

School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China

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Received Date: August 02, 2018
Revised Date: January 22, 2019
Available Online: April 29, 2019
Published Date: March 31, 2019

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Abstract

Abstract

ObjectiveThe greenspace composed of urban green space, farmland, woodland, wetland and water area is of great significance to ensure social harmony, economic efficiency, ecological comfort and living comfort, so as to maintain the sustainable development of the city. It is of great significance to clarify the dynamic change of landscape and its driving mechanism to guide the reasonable planning of green space in central Beijing so as to improve its large ecological environment.
MethodIn this study, the central Beijing City was taken as the research area, and four time nodes of 1992, 2000, 2008 and 2016 were selected to study the driving mechanism of green space evolution. The influence of social and economic factors, natural factors and policy factors on the evolution of greenspace was investigated by partial least squares regression analysis.
ResultPartial least-squares regression analysis results of social and economic factors and the evolution of regional area showed that the four influencing factors of regional gross output value, per capita GDP, permanent population and construction land area to the variable importance VIP value of the evolution of regional area were all greater than 1. Among the natural factors, the variable projection importance VIP value affecting the evolution of the area index of the type of plaques in various regions was less than 1.
ConclusionThe research shows that social economy is the direct driving force of the green space evolution in the central Beijing City, and the increase of population scale, the growth of regional economy and the adjustment of industrial structure are the important factors leading to the green space evolution. The influence of natural factors on the evolution of green space is relatively static and less obvious than that of social and economic factors. This study scientifically and rationally clarifies the key factors affecting the development of green space, and provides a reference for formulating reasonable and scientific policies on green space development and protection.
- central Beijing City,
- greenspace,
- evolution,
- driving mechanism

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References

[1]	Oszlanyi J. Forest health and environmental pollution in Slovakia[J]. Environmental Pollution, 1997, 98(3): 389−392. doi: 10.1016/S0269-7491(97)00155-3
[2]	Szepesi A. Forest health status in Hungary[J]. Environmental Pollution, 1997, 98(3): 393−398. doi: 10.1016/S0269-7491(97)00147-4
[3]	陈彩虹, 胡锋, 张落成. 南京市城乡交错带景观格局研究[J]. 应用生态学报, 2003, 14(8):1363−1368. doi: 10.3321/j.issn:1001-9332.2003.08.034 Chen C H, Hu F, Zhang L C. Landscape pattern of Nanjing urbanrural ecotone[J]. Chinese Journal of Applied Ecology, 2003, 14(8): 1363−1368. doi: 10.3321/j.issn:1001-9332.2003.08.034
[4]	高峻, 宋永昌. 基于遥感和GIS的城乡交错带景观演变研究: 以上海西南地区为例[J]. 生态学报, 2003, 23(4):805−813. doi: 10.3321/j.issn:1000-0933.2003.04.024 Gao J, Song Y C. On landscape dynamics of the urban-rural ecotone based on remote sensing and GIS: a case study of southwest Shanghai[J]. Acta Ecologica Sinica, 2003, 23(4): 805−813. doi: 10.3321/j.issn:1000-0933.2003.04.024
[5]	邬建国. 景观生态学: 格局、过程、尺度与等级[M]. 北京: 高等教育出版社, 2000. Wu J G. Landscape ecology: pattern, process, scale and grade[M]. Beijing: Higher Education Press, 2000.
[6]	穆博, 李华威, Mayer A L, et al. 基于遥感和图论的绿地空间演变和连通性研究: 以郑州为例[J]. 生态学报, 2017, 37(14):4883−4895. Mu B, Li H W, Mayer A L, et al. Dynamic changes of green-space connectivity based on remote sensing and graph theory: a case study in Zhengzhou, China[J]. Acta Ecologica Sinica, 2017, 37(14): 4883−4895.
[7]	邵大伟, 吴殿鸣. 基于景观指数的南京主城区绿色空间演变特征研究[J]. 中国园林, 2016, 32(2):103−107. doi: 10.3969/j.issn.1000-6664.2016.02.023 Shao D W, Wu D M. Landscape pattern evolvement of green space: a case study of the central area of Nanjing[J]. Chinese Landscape Architecture, 2016, 32(2): 103−107. doi: 10.3969/j.issn.1000-6664.2016.02.023
[8]	谭博文, 宋伟. 新型城镇化实验区土地利用及景观格局时空变化研究: 以河北省定州市为例[J]. 地理科学研究, 2018, 7(1):46−54. Tan B W, Song W. Spatio-temporal change of land use and landscape pattern in new-type urbanization experimental area[J]. Geographical Science Research, 2018, 7(1): 46−54.
[9]	韩贵锋, 郭建明, 赵一凡, 等. 重庆市主城区绿色空间的演变及驱动机制研究[J]. 三峡生态环境监测, 2017, 2(2):34−44. Han G F, Guo J M, Zhao Y F, et al. Evolution and driving mechanism of green space in urban Chongqing[J]. Ecology and Environmental Monitoring of Three Gorges, 2017, 2(2): 34−44.
[10]	Liu S H, Wang D Y, Li H, et al. Ecological land fragmentation evaluation and dynamic change of a typical black soil farming area in Northeast China[J/OL]. Sustainability, 2017, 9(2): 300 [2018−03−20]. http://doi.org/10.3390/su9020300.
[11]	李卫锋, 王仰麟, 彭建, 等. 深圳市景观格局演变及其驱动因素分析[J]. 应用生态学报, 2004, 15(8):1403−1410. doi: 10.3321/j.issn:1001-9332.2004.08.020 Li W F, Wang Y L, Peng J, et al. Landscape spatial changes in Shenzhen and their driving factors[J]. Chinese Journal of Applied Ecology, 2004, 15(8): 1403−1410. doi: 10.3321/j.issn:1001-9332.2004.08.020
[12]	巫涛. 长沙城市绿地景观格局及其生态服务功能价值研究[D]. 长沙: 中南林业科技大学, 2005. Wu T. The research on landscape pattern and ecosystem service in Changsha[D]. Changsha: Central South University of Forestry and Technology, 2005.
[13]	洪冬晨. 哈萨克斯坦土地利用景观格局演变及驱动因素分析[D]. 杭州: 浙江大学, 2015. Hong D C. Analysis of land use and landscape pattern change and its driving factors in Kazakhstan[D]. Hangzhou: Zhejiang University, 2015.
[14]	孙才志, 闫晓露. 基于GIS-Logistic耦合模型的下辽河平原景观格局变化驱动机制分析[J]. 生态学报, 2014, 34(24):7280−7292. Sun C Z, Yan X L. Driving mechanism analysis of landscape pattern change in the lower reach of Liaohe River Plain based on gis-logistic coupling model[J]. Acta Ecologica Sinica, 2014, 34(24): 7280−7292.
[15]	恭映壁. 长沙城市湿地景观格局时空演变与驱动机制研[D]. 长沙: 中南林业科技大学, 2013. Gong Y B. The spatial-temporal pattern evoluation of wetland landscape and its driving mechanism in Changsha[D]. Changsha: Central South University of Forestry and Technology, 2013.
[16]	Jia Z M, Ma B R, Zhang J, et al. Simulating spatial-temporal changes of land-use based on ecological redline restrictions and landscape driving factors: a case study in Beijing[J/OL]. Sustainability, 2018, 10(4): 1299[2018−02−25]. https://doi.org/10.3390/su10041299.
[17]	肖瑶, 王艳慧, 尹川. 北京城区近20年土地利用变化及其驱动力分析[J]. 测绘与空间地理信息, 2013, 36(7):29−32. Xiao Y, Wang Y H, Yin C. Driving force analysis of land use Chang of Beijing Urban Areas in the past 20 years[J]. Geomatics & Spatial Information Technology, 2013, 36(7): 29−32.
[18]	林坚, 汤晓旭, 黄斐玫, 等. 城乡结合部的地域识别与土地利用研究: 以北京中心城地区为例[J]. 城市规划, 2007, 31(8):36−44. doi: 10.3321/j.issn:1002-1329.2007.08.006 Lin J, Tang X X, Huang F M, et al. Spatial identification and land use of urban-rural linkage area: a case study on Beijing ’s center city[J]. City Planning Review, 2007, 31(8): 36−44. doi: 10.3321/j.issn:1002-1329.2007.08.006
[19]	北京市人民政府. 北京城市总体规划(2004年—2020年)[J]. 北京规划建设, 2005(2):5−51. doi: 10.3969/j.issn.1003-627X.2005.02.001 People’s Government of Beijing Municipality. General plan for Beijing (2004−2020) [J]. Beijing Planning and Construction, 2005(2): 5−51. doi: 10.3969/j.issn.1003-627X.2005.02.001
[20]	张亚芹, 周嗣恩, 孔令铮, 等. 北京市中心城道路网规划实施评估与政策机制[J]. 城市交通, 2016, 14(3):43−47. Zhang Y Q, Zhou S E, Kong L Z, et al. Evaluating roadway network implementation and policy in Beijing central district[J]. Urban Transport of China, 2016, 14(3): 43−47.
[21]	王晓轩, 夏丽华, 邓珊珊, 等. 基于STIRPAT模型的广州市耕地变化社会经济驱动力分析[J]. 中国农学通报, 2010, 26(20):339−343. Wang X X, Xia L H, Deng S S, et al. Cultivated land area change and its socio-economic driving forces based on STIRPAT model[J]. Chinese Agricultural Science Bulletin, 2010, 26(20): 339−343.
[22]	阳文锐. 北京城市景观格局时空变化及驱动力[J]. 生态学报, 2015, 35(13):4357−4366. Yang W R. Spatiotemporal change and driving forces of urban landscape pattern in Beijing[J]. Acta Ecologica Sinica, 2015, 35(13): 4357−4366.
[23]	何春阳, 史培军, 陈晋, 等. 北京地区城市化过程与机制研究[J]. 地理学报, 2002, 57(3):363−371. doi: 10.3321/j.issn:0375-5444.2002.03.013 He C Y, Shi P J, Chen J, et al. Process and mechanism of urbanization in Beijing area[J]. Acta Geographica Sinica, 2002, 57(3): 363−371. doi: 10.3321/j.issn:0375-5444.2002.03.013
[24]	马明德, 马学娟, 谢应忠, 等. 宁夏生态足迹影响因子的偏最小二乘回归分析[J]. 生态学报, 2014, 34(3):682−689. Ma M D, Ma X J, Xie Y Z, et al. Analysis the relationship between ecological footprint (EF) of Ningxia and influencing factors: analysis the relationship between ecological footprint (EF) of Ningxia and influencing factors: Partial Least-Squares Regression (PLS)[J]. Acta Ecologica Sinica, 2014, 34(3): 682−689.
[25]	张瑜, 王天巍, 蔡崇法, 等. 干旱区耕地景观格局碎化特征及社会经济驱动因素分析[J]. 水土保持研究, 2016, 23(4):179−184. Zhang Y, Wang T W, Cai C F, et al. Characteristics of arable land fragmentation and the socioeconomic drivers in the arid area[J]. Research of Soil and Water Conservation, 2016, 23(4): 179−184.
[26]	孙杨, 许承明, 夏锐. 研发资金投入渠道的差异对科技创新的影响分析: 基于偏最小二乘法的实证研究[J]. 金融研究, 2009(9):165−174. Sun Y, Xu C M, Xia R. An empirical study on the influence of R&D funding channels on technological innovation based on Partial Least Square Method[J]. Journal of Financial Research, 2009(9): 165−174.
[27]	王惠文, 吴载斌, 孟洁. 偏最小二乘回归的线性与非线性方法[M]. 北京: 国防工业出版社, 2006. Wang H W, Wu Z B, Meng J. Linear and nonlinear methods for Partial Least Squares Regression[M]. Beijing: National Defense Industry Press, 2006.
[28]	高惠璇. 两个多重相关变量组的统计分析(3): 偏最小二乘回归与PLS过程[J]. 数理统计与管理, 2002, 21(2):58−64. Gao H X. Statistical analyses for multiple correlation variables of two sets (3): Partial Least-Square Regression and PLS procedure[J]. Journal of Applied Statistics and Management, 2002, 21(2): 58−64.
[29]	张恒喜. 小样本多元数据分析方法及应用[M]. 西安: 西北工业大学出版社, 2002. Zhang H X. Methods and applications of small sample multivariate data analysis[M]. Xi’an: Northwestern Polytechnical University Press, 2002.
[30]	Trap J, Hättenschwiler S, Gattin I, et al. Forest ageing: an unexpected driver of beech leaf litter quality variability in European forests with strong consequences on soil processes[J]. Forest Ecology & Management, 2013, 302(6): 338−345.
[31]	李方正, 解爽, 李雄. 基于多源数据分析的北京市中心城绿色空间时空演变研究(1992—2016)[J]. 风景园林, 2018(8):46−51. Li F Z, Xie S, Li X. The Spatio-temporal evolution of green spaces in central Beijing based on multisource data (1992−2016)[J]. Landscape Architecture, 2018(8): 46−51.

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Evolutionary driving mechanism of greenspace in central Beijing City based on the PLSR model