基于城市化进程的宜兴市景观演变与预测

doi:10.3969/j.issn.1000-2006.201811016

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南京林业大学学报（自然科学版） ›› 2019, Vol. 43 ›› Issue (6): 105-112.doi: 10.3969/j.issn.1000-2006.201811016

基于城市化进程的宜兴市景观演变与预测

刘智丽¹(), 岳德鹏¹^,^*(), 杨慧², 张启斌¹, 于强¹, 徐小东³

1.北京林业大学精准林业北京市重点实验室,北京 100083
2.中国矿业大学资源与地球科学学院,江苏徐州 221116
3.东南大学建筑学院,江苏南京 210096

收稿日期:2018-11-07 修回日期:2019-04-02 出版日期:2019-11-30 发布日期:2019-11-30
通讯作者: 岳德鹏
基金资助:
国家自然科学基金项目(51678127)

Evolvement and prediction of landscape pattern in Yixing City based on urbanization process

LIU Zhili¹(), YUE Depeng¹^,^*(), YANG Hui², ZHANG Qibin¹, YU Qiang¹, XU Xiaodong³

1. Beijing Key Laboratory of Precision Forestry, Beijing Forestry University, Beijing 100083, China
2. School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China
3. School of Architecture, Southeast University, Nanjing 210096, China

Received:2018-11-07 Revised:2019-04-02 Online:2019-11-30 Published:2019-11-30
Contact: YUE Depeng

摘要/Abstract

摘要：

【目的】在城市化进程不断加速的背景下进行区域景观变化预测,对宜兴市近年来景观格局分布演变情况进行分析,探索城市化水平与景观格局变化之间的联系,为当地以及周边地区的景观规划研究提供借鉴。【方法】选用1996—2016年宜兴市的遥感影像数据,通过利用景观指数、转移矩阵分析在此期间景观分布的演变过程,并采用灰色预测模型估算其未来主要景观类型的变化趋势。【结果】在景观的演变过程中,建设用地、林草地持续扩张,面积分别增加了168.13、375.76 km²,且分布逐渐复杂,耕地、未利用地不断缩减,耕地与林草地在前期变动较大,动态度分别为-4.72%、10.18%,但耕地在后期面积几乎不再减少,分布也趋于规整;在城市化水平不断提升的过程中,耕地、林草地、建设用地的变化与城市化水平之间的联系十分紧密,相关性均高于0.8;在未来景观的发展过程中,耕地面积将处于动态稳定的状态,随着时间的推移,建设用地与林草地不断扩张,预测2016—2024年的涨幅分别为15.1%、35.4%。【结论】宜兴市1996—2016年景观格局变化明显,且城市化进程对建设用地、林草地、耕地的范围和分布产生了较大影响。

关键词: 景观指数, 景观格局, 灰色预测模型, 区域景观, 宜兴市

Abstract:

【Objective】Under the background of the accelerating urbanization process, the prediction of regional change can be used as a reference to study landscape planning in local and surrounding areas. To analyze the evolution of landscape pattern distribution in Yixing City in recent years, we explored the relationship between urbanization level and landscape pattern change. 【Method】The changing process of landscape distribution in Yixing was analyzed using landscape index and transfer matrix based on remote sensing image data from 1996 to 2016. Then, the gray prediction model was used to estimate the trend of the main types of landscapes in the future. 【Result】 Results showed that during the evolution of the landscape, construction land, forest and grassland continued to expand with the complication of distribution and the area increased by 168.13 and 375.76 km², respectively. Further, cultivated and unutilized lands were shrinking constantly. The cultivated land, forest and grassland changed greatly in the early period, and the ratios were -4.72% and 10.18%, respectively. However, the area of cultivated land did not considerably decrease from 2006 to 2016, and its distribution tended to be regular. With the continuous improvement of the urbanization level, connection between the urbanization level and cultivated land, grassland and construction land is close; the correlation is higher than 0.8. In the future evolution of the landscape, the arable land will be in a dynamic and stable state. With time, the construction land and forest and grassland would continue to be in an ever-expanding state, and the growth rate is predicted to be 15.1% and 35.4%, respectively, in 2016 and 2024. 【Conclusion】The landscape pattern of Yixing City changed significantly from 1996 to 2016 and the process of urbanization had a great impact on the scope and distribution of the construction land, cultivated land, forest and grassland, which could provide a general reference for the development of Yixing City and the surrounding areas.

Key words: landscape index, landscape pattern, gray prediction model, regional landscape, Yixing City

中图分类号:

P901

刘智丽,岳德鹏,杨慧,等. 基于城市化进程的宜兴市景观演变与预测[J]. 南京林业大学学报（自然科学版）, 2019, 43(6): 105-112.

LIU Zhili, YUE Depeng, YANG Hui, ZHANG Qibin, YU Qiang, XU Xiaodong. Evolvement and prediction of landscape pattern in Yixing City based on urbanization process[J].Journal of Nanjing Forestry University (Natural Science Edition), 2019, 43(6): 105-112.DOI: 10.3969/j.issn.1000-2006.201811016.

图/表 12

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表6

检验精度等级表"

精度 precision	均方差比值 mean square error ratio	小误差概率 small error probability	平均相对误差 average relative error
一级 first level	0< $C i$ ≤0.35	0.95 ≤ P_i ≤1	0< \| $Δ ?$ \| ≤0.01
二级 second level	0.35< $C i$ ≤0.5	0.80 ≤ P_i <0.95	0.01< \| $Δ ?$ \| ≤0.05
三级 third level	0.5< $C i$ ≤0.65	0.70 ≤ P_i <0.80	0.05<\| $Δ ?$ \|≤0.10
四级 fourth level	C_i >0.65	P_i <0.70	\| $Δ ?$ \|>0.10

表6

表7

图5

参考文献 19

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时期 period	景观类型 landscape type	面积/km² area						变化率/% rate of change
时期 period	景观类型 landscape type	CLL	CL	FG	W	UL	总计sum	变化率/% rate of change
1996—2006	CLL	305.18	114.46	107.96	7.43	133.70	668.73	54.36
	CL	10.97	293.60	98.42	15.21	21.40	439.60	33.21
	FG	2.22	20.94	196.07	0.57	19.83	239.63	18.18
	W	0.85	12.74	0.72	388.27	1.46	404.04	3.90
	UL	34.16	67.42	80.44	5.97	112.49	300.49	62.56
	总计sum	353.38	509.16	483.61	417.46	288.88	2 052.49
2006—2016	CLL	216.64	68.98	64.03	2.71	1.02	353.38	38.69
	CL	18.98	378.92	73.65	36.74	0.87	509.16	25.58
	FG	32.91	87.39	354.72	2.62	5.96	483.61	26.65
	W	1.65	11.58	1.99	402.21	0.02	417.46	3.65
	UL	72.94	60.85	121.01	3.76	30.32	288.88	89.50
	总计sum	343.13	607.73	615.39	448.04	38.20	2 052.49

景观类型 landscape type	动态度/% dynamic degree
景观类型 landscape type	1996—2006	2006—2016
CLL	-4.72	-0.29
CL	1.58	1.94
FG	10.18	2.72
W	0.33	0.73
UL	-0.39	-8.68

景观类型 landscape type	年份 year	斑块面积占比/% PLAND	景观形状指数 LSI	周长面积分维数 PAFRAC	边缘密度/ (m·hm^-2) ED	聚集度指数 AI	最近距离/m ENN
CLL	1996	32.58	130.89	1.39	65.67	84.91	86.87
	2006	17.22	146.79	1.42	53.69	76.68	86.32
	2016	16.22	132.41	1.38	47.72	78.68	93.81
CL	1996	21.42	151.47	1.41	61.74	78.44	85.94
	2006	24.81	154.43	1.43	67.74	79.57	94.49
	2016	29.61	163.23	1.43	78.17	80.23	90.23
FG	1996	11.68	146.05	1.52	43.86	71.83	106.43
	2006	23.56	166.30	1.50	70.98	77.40	81.12
	2016	29.98	166.79	1.49	80.22	79.92	77.62
W	1996	19.69	14.72	1.37	5.34	97.95	172.82
	2006	20.34	26.26	1.34	10.02	96.28	130.47
	2016	21.83	40.35	1.37	16.20	94.41	112.23
UL	1996	14.64	202.22	1.53	68.15	65.11	83.91
	2006	14.08	245.43	1.55	81.20	56.74	75.14
	2016	1.86	61.52	1.39	7.40	70.41	164.77

景观类型 landscape type	面积/km² area
景观类型 landscape type	1996	1998	2000	2002	2004	2006	2008	2010	2012	2014	2016
CLL	668.73	605.66	542.59	479.52	416.45	353.38	351.33	349.28	347.23	345.18	343.13
CL	439.60	453.51	467.42	481.34	495.25	509.16	528.88	548.59	568.30	588.01	607.73
FG	239.63	288.43	337.22	386.02	434.81	483.61	509.96	536.32	562.68	589.03	615.39
W	404.04	406.72	409.40	412.09	414.77	417.46	423.57	429.69	435.81	441.93	448.04
UL	300.49	298.17	295.84	293.52	291.20	288.88	238.74	188.61	138.47	88.33	38.20

项目 item	1996	1998	2000	2002	2004	2006	2008	2010	2012	2014	2016
x₀	668.73	605.66	542.59	479.52	416.45	353.38	351.33	349.28	347.23	345.18	343.13
y₀	6.505 4	6.406 3	6.296 4	6.172 8	6.031 8	5.867 5	5.861 7	5.855 9	5.850 0	5.844 1	5.838 1
y₁	6.505 4	12.911 7	19.208 1	25.380 9	31.412 6	37.280 2	43.141 9	48.997 8	54.847 8	60.691 8	66.530 0
z₁		9.708 5	16.059 9	22.294 5	28.396 7	34.346 4	40.211 0	46.069 8	51.922 8	57.769 8	63.610 9

基于城市化进程的宜兴市景观演变与预测

Evolvement and prediction of landscape pattern in Yixing City based on urbanization process

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指标 index	耕地 CLL	建设用地 CL	林草地 FG
均方差比值 mean square error ratio	0.36	0.18	0.12
小误差概率 small error probability	0.91	1	1
平均相对误差 average relative error	-0.027	0.010	0.007
预测精度 precision of prediction	二级 second level	一级 first level	一级 first level

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