• Geographical Research
  • Vol. 39, Issue 8, 1725 (2020)
Jiansheng WU1、2、*, Keyu LUO1, and Yuhao ZHAO1、2
Author Affiliations
  • 1Key Laboratory for Urban Habitat Environmental Science and Technology, School of Urban Planning and Design, Shenzhen Graduate School of Peking University, Shenzhen 518055, Guangdong, China
  • 2Key Laboratory for Earth Surface Processes of Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
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    DOI: 10.11821/dlyj020190539 Cite this Article
    Jiansheng WU, Keyu LUO, Yuhao ZHAO. The evolution of urban landscape pattern and its driving forces of Shenzhen from 1996 to 2015[J]. Geographical Research, 2020, 39(8): 1725 Copy Citation Text show less
    Administrative division of Shenzhen
    Fig. 1. Administrative division of Shenzhen
    Landscape of Shenzhen during 1996-2015
    Fig. 2. Landscape of Shenzhen during 1996-2015
    Changes of landscape metrics in class level of Shenzhen during 1996-2015
    Fig. 3. Changes of landscape metrics in class level of Shenzhen during 1996-2015
    Changes of landscape metrics in landscape level of Shenzhen during 1996-2015
    Fig. 4. Changes of landscape metrics in landscape level of Shenzhen during 1996-2015
    The map of main landscape type transfer by stage during 1996-2010
    Fig. 5. The map of main landscape type transfer by stage during 1996-2010
    The process of urban expansion in Shenzhen during 1996-2015
    Fig. 6. The process of urban expansion in Shenzhen during 1996-2015
    景观格局指数指标名称指标意义
    CA斑块类型面积,单位:hm²反映景观中优势斑块类型。
    PLAND斑块类型所占景观面积的比例,单位:%反映景观面积的比例
    NP斑块个数,单位:个反映景观异质性和破碎度。
    PD斑块密度,单位:个/100 hm2斑块数量特征,反映景观异质性和破碎度。PD值越大,表明景观斑块破碎度越大。
    ED边缘密度,单位:m/hm²表征景观被边界分割的程度,ED值越大,表明斑块形状越复杂,景观被边界分割的程度越高。
    AREA_MN平均斑块面积,单位:hm²表征景观的破碎化程度,值减小说明景观的破碎化程度上升,反之则下降。
    AI聚集度指数反映景观要素的聚集程度。AI的取值范围为[0, 100]。当AI接近于100时,斑块聚集越紧密,景观内部以少量大斑块为主或者斑块高度相连;当AI趋近于0时,景观中斑块离散程度越大,该类型景观由越多离散的小斑块组成。
    PAFRAC周长面积分维数反映形状的复杂性,其值范围为[1, 2],PAFRAC接近于1表明景观边界形状非常简单,如正方形,接近于2表明边界形状非常复杂。
    SHDI香农多样性指数体现景观水平复杂程度,斑块丰富度越大或不同斑块面积分布越均匀时,SHDI值越大。
    SHEI香农均匀度指数表征城市土地利用的均质性的强弱。SHEI取值范围为[0, 1],SHEI越接近1表明斑块类型分布越均匀,多样性越强;SHEI趋于0时,景观分布极不均匀,优势斑块控制度强。
    Table 1. Landscape pattern index
    变量类别变量单位
    社会经济GDP密度万元/km2
    人口密度万人/km2
    土地政策基本生态控制线-
    自然条件高程m
    坡度°
    至水库、湖泊的距离m
    至河流水系的距离m
    可达性至铁路、轻轨的距离m
    至公路的距离m
    局地邻近距离居街道居委会距离m
    Table 2. Driving forces of urban landscape change in Shenzhen
    景观类型CA(km²)PLAND(%)
    1996年2000年2006年2010年2015年1996年2000年2006年2010年2015年
    耕地70.6890.7550.3943.8550.413.614.632.542.202.51
    园地221.19185.22269.73236.83207.8611.289.4413.7611.8710.39
    林地736.02571.96581.57586.62578.4337.5229.0329.6829.4128.92
    草地4.165.3310.2632.8825.030.210.270.521.651.25
    建筑用地502.55461.54774.37752.35828.7025.6223.4839.5137.7241.43
    交通用地27.1778.9791.8388.29100.441.394.024.694.435.02
    水域230.64226.82172.56167.56157.6411.7611.568.808.407.88
    其他未利用地169.083349.0686.0951.608.6217.020.464.322.58
    Table 3. Changes of landscape area and proportion in Shenzhen during 1996-2015
    时期飞地式(km2)蔓延式(km2)填充式(km2)总计(km2)占比(%)
    1996—2000年8.29139.2351.05198.5723.18
    2000—2006年7.24252.57166.58426.3949.78
    2006—2010年4.4576.3753.69134.5115.71
    2010—2015年1.7855.9039.3797.0511.33
    总计21.76524.07310.69856.52100.00
    占比(%)2.5461.1936.27100.00
    Table 4. The area and proportion of different urban expansion modes during 1996-2015
    深圳区宝安区大鹏新区福田区光明区龙岗区龙华区罗湖区南山区坪山区盐田区
    系数P系数P系数P系数P系数P系数P系数P系数P系数P系数P系数P
    常数项1.7152620.000-1.1642490.1434.2616770.051-10.0560600.2622.8868540.0104.2616000.0000.5000710.6771.6310170.5514.9873780.001-2.1668070.2441.0793300.864
    GDP密度0.0000490.0000.0001280.0000.0000350.643-0.0002760.2580.0000060.9030.0000060.7220.0000010.9690.0000300.8270.0001430.0310.0000910.024-0.0001500.452
    人口密度0.0006520.0960.0024230.0190.0023190.4460.0213650.1250.0008220.671-0.0012770.1210.0039530.002-0.0053640.165-0.0122420.0000.0022010.2750.0125480.075
    生态控制线-0.2023010.000-0.1392870.0040.1552350.201-0.5928630.065-0.1543200.006-0.2655780.000-0.2955520.0000.1873900.383-0.3836310.001-0.1340580.055-0.3290090.481
    高程-0.0075990.000-0.0057880.007-0.0237060.000-0.0267960.204-0.0063540.250-0.0139530.000-0.0111810.002-0.0131200.003-0.0209430.000-0.0174510.000-0.0253010.001
    坡度-0.1231760.000-0.1421930.000-0.0590520.038-0.1333120.171-0.1577020.000-0.1426110.000-0.0932190.000-0.0530110.108-0.0974480.002-0.0794020.003-0.1344230.010
    至水库、湖泊距离0.0000020.7690.0000050.789-0.0003040.0010.0003390.330-0.0000990.005-0.0000030.859-0.0000190.6630.0001530.3980.0001940.0460.0001330.1650.0005270.074
    至河流水系距离-0.0000180.3920.0001440.018-0.0004160.001-0.0003300.483-0.0001260.155-0.0000480.4780.0002410.0250.0010810.041-0.0000680.641-0.0001380.114-0.0002850.563
    至铁路、轻轨距离-0.0000530.0000.0000850.106-0.0000900.0210.0017890.248-0.0000950.187-0.0002510.000-0.0000310.613-0.0010130.004-0.0000330.8510.0003070.000-0.0003750.359
    至公路距离-0.0001510.0000.0000950.276-0.0010150.001-0.0015840.097-0.0004490.000-0.0002510.010-0.0002390.2170.0003860.486-0.0000240.8800.0000660.6710.0006960.219
    至街道居委会距离-0.0314930.1800.0361570.5070.2531030.196-0.2153210.6220.0770010.442-0.0133480.801-0.0736380.2320.0850240.7350.1078350.3860.0505660.613-1.0601360.096
    LRstatistic2449696310632576953285324137588
    P值(LR-statistic)0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
    ROC0.84490.84810.84720.91350.84380.82530.80910.81140.85908.86120.8664
    Table 5. Parameters and tests of Binary Logit regression models
    变量深圳区宝安区大鹏新区福田区光明区龙岗区龙华区罗湖区南山区坪山区盐田区
    GDP密度
    人口密度
    生态控制线
    高程
    坡度
    至水库、湖泊距离
    至河流水系距离
    至铁路、轻轨距离
    至公路距离
    至街道居委会距离
    Table 6. Driving forces of landscape evolution in Shenzhen and its districts
    Jiansheng WU, Keyu LUO, Yuhao ZHAO. The evolution of urban landscape pattern and its driving forces of Shenzhen from 1996 to 2015[J]. Geographical Research, 2020, 39(8): 1725
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