The evolution and driving mechanism of urban green space system: a case study of Xuchang City, Henan Province, China

doi:10.12302/j.issn.1000-2006.202208012

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2024, Vol. 48 ›› Issue (3): 275-284.doi: 10.12302/j.issn.1000-2006.202208012

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The evolution and driving mechanism of urban green space system: a case study of Xuchang City, Henan Province, China

LIU Jie¹(), ZHANG Lang¹^,^*(), ZHANG Qingping²^,^*()

1. Shanghai Academy of Landscape Architecture Science and Planning,Shanghai 200232,China
2. College of Landscape Architecture,Nanjing Forestry University,Nanjing 210037,China

Received:2022-08-03 Revised:2022-11-23 Online:2024-05-30 Published:2024-06-14

Abstract

Abstract:

【Objective】 Owing to tighter resource constraints and intensive land development, we analyzed the ecological, social, and economic functions of urban green space system (UGSS), and determined its evolutionary characteristics and driving mechanism. To provide a basis for efficient urban land allocation and decision-making support for urban construction. 【Method】 Xuchang City (Henan Province) was selected as a case study, using time nodes data from 2010, 2014 and 2019. We applied the backtracking method with a land use simulation model and random forest regression; driving factors such as policy, natural and socioeconomic factors were analyzed. 【Result】 (1) From 2010 to 2019, Xuchang’s UGSS developed from the northeast and north, which was consistent with the guidance of urban planning policies. (2) The impact of planning policy on UGSS could either be positive protection or negative erosion. The GeoSOS-FLUS model and the backtracking method could simulate the changes in the UGSS, which could then be used to determine the impacts of the planning policy and establish an analytical framework for policy failure. (3) Socioeconomic factors had a significant impact on changes in the areas of township-level UGSS and the landscape pattern index, whereas natural factors had lower impacts. In Xuchang, which located on a plain, topography, had the smallest impact on changes in UGSS. The patch density changes in the UGSS had a high goodness of fit with each driving factor, which reflects the correlations between the UGSS landscape pattern and its driving factors. 【Conclusion】 Planning policy is the guiding driver of changes in UGSS, whereas socioeconomic factors directly drive changes in UGSS and natural factors have relatively little impact. Determining the evolution law of UGSS is necessary for enhancing scientific and forward-looking planning for UGSS under the new territorial spatial planning system.

Key words: urban green space system, evolution characteristics, driving mechanism, socioeconomic factors, policy factors, Xuchang City, Henan Province

CLC Number:

TU986

LIU Jie, ZHANG Lang, ZHANG Qingping. The evolution and driving mechanism of urban green space system: a case study of Xuchang City, Henan Province, China[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2024, 48(3): 275-284.

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References 29

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编号 No.	政策名称 policy name	年份 year	编号 No.	政策名称 policy name	年份 year
1	自然资源部关于以“多规合一”为基础推进规划用地“多审合一、多证合一”改革的通知	2019	13	许昌市城市绿地系统规划(2015—2030)	2015
1	自然资源部关于以“多规合一”为基础推进规划用地“多审合一、多证合一”改革的通知		14	许昌市城市总体规划(2015—2030)
2	矿产资源规划编制实施办法		14	许昌市城市总体规划(2015—2030)
2	矿产资源规划编制实施办法		15	许昌市建设节约型城市园林绿化指导意见	2014
3	节约集约利用土地规定		15	许昌市建设节约型城市园林绿化指导意见	2014
3	节约集约利用土地规定		16	许昌市林业生态建设提升工程规划(2013—2017)	2013
4	土地复垦条例实施办法		16	许昌市林业生态建设提升工程规划(2013—2017)	2013
4	土地复垦条例实施办法		17	许昌新区总体规划	2011
5	许昌市城乡规划条例		17	许昌新区总体规划	2011
6	构建“多规合一”的国土空间规划体系		18	许昌市人民政府关于建立完善产业集聚区推进工作机制的通知	2010
7	河南省国土资源厅关于加强土地利用计划精细化管理促进经济高质量发展的通知		18	许昌市人民政府关于建立完善产业集聚区推进工作机制的通知	2010
7	河南省国土资源厅关于加强土地利用计划精细化管理促进经济高质量发展的通知		19	土地复垦规定	2009
8	自然资源部关于做好占用永久基本农田重大建设项目用地预审的通知	2018	19	土地复垦规定
			20	基本农田保护条例
			21	土地调查条例系列解读	2008
9	许昌市主城区景观绿化提升规划(2018—2020)		21	土地调查条例系列解读
10	许昌市人民政府办公室关于印发中心城区商改居土地手续办理办法的通知	2017	22	《国务院关于加强土地调控有关问题的通知》系列解读
11	河南省人民政府关于进一步加强节约集约用地的意见	2015	22	《国务院关于加强土地调控有关问题的通知》系列解读
			23	许昌市土地利用总体规划(2006—2020)	2006
			24	许昌市城市总体规划(2005—2020)	2005
12	节约集约利用土地规定		24	许昌市城市总体规划(2005—2020)	2005

分类 classification	政策编号 policy No.	政策作用强弱和正负引导 degree of action	政策赋值 assignment	分类 classification	政策编号 policy No.	政策作用强弱和正负引导 degree of action	政策赋值 assignment
UN-UN	1	I-S(+)	1	N-UN/N-N/UN-UN	13	D-S(+)	9
UN-UN	2	I-W(-)	1	N-UN/N-N/UN-UN	14	D-S(+)	9
N-N/N-UN	3	D-S(+)	1	N-UN/N-N/UN-UN	15	D-W(+)	5
N-N/N-UN	4	I-W(+)	5	N-UN/N-N/UN-UN	16	D-S(+)	9
N-UN	5	I-W(+)	1	N-UN/N-N/UN-UN	17	I-S(+)	5
N-UN	6	I-S(+)	5	N-UN/N-N/UN-UN	18	D-S(+)	9
N-N/N-UN	7	I-S(+)	1	N-UN/N-N/UN-UN	19	D-S(+)	9
N-UN	8	I-W(-)	5	UN-UN	20	D-W(-)	5
UN-UN	9	D-W(-)	5	N-UN	21	D-S(+)	9
N-UN	10	I-S(+)	1	N-UN	22	D-S(+)	9
N-UN	11	D-W(+)	1	N-UN	23	I-S(+)	1
N-UN/N-N/UN-UN	12	D-S(+)	9	N-UN	24	I-S(+)	1

用地类型 land use types		模拟误差/% simulation error
用地类型 land use types		初始参数下 initial parameter	最终参数下 final parameter
生态空间 ecological space	绿地	-10.70	3.64
生态空间 ecological space	农林用地	3.60	4.85
非生态空间 non-ecological space	居住用地	0.95	0.00
	商服用地	7.99	0.89
	工业用地	-23.70	-0.16

类型 type	政策及其作用机制影响程度 degree of policies and their mechanisms of action				作用机制 mechanism
有效政策 effective policy	4-I-W(+)	8-I-W(-)	21-D-S(+)	22-D-S(+)	农田保护
	6-I-S(+)	14-D-S(+)	18-D-S(+)	19-D-S(+)	生态空间保护
	9-D-W(-)	-	-	-	商服用地转为居住用地
	12-D-S(+)	13-D-S(+)	-	-	农林用地转为绿地居住用地转为绿地商服用地转为绿地工业用地转为绿地
	15-D-W(+)	17-I-S(+)	-	-	其他建设用地转为绿地
	16-D-S(+)	-	-	-	林地保护
	20-D-W(-)	-	-	-	其他建设用地转为工业用地
失效政策 ineffective policy	1-I-S(-)	5-I-W(+)	23-I-S(+)	24-I-S(+)	条例解读
	2-I-W(-)				非生态空间调控
	3-D-S(+)	7-I-S(+)	10-I-S(+)	11-D-W(+)	总量调控

年份 year	因子 factor	均方误差增加率/% IncMSE	节点纯度增加量 IncNode purity
2010—2014	国内生产总值GDP	6.296 427	222 353.9
	年均降水量AAP	2.933 845	185 177.9
	年均气温AAT	1.663 668	155 472.5
	高程DEM	1.382 070	173 299.4
2014—2019	国内生产总值GDP	4.040 780	124 029 70.0
	年均气温AAT	3.597 955	676 130.2
	年均降水量AAP	3.512 343	574 503.3
	高程DEM	1.601 235	900 787.1

The evolution and driving mechanism of urban green space system: a case study of Xuchang City, Henan Province, China

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景观格局指数 landscape pattern metric	驱动因子 driving factor	2010—2014		2014—2019
景观格局指数 landscape pattern metric	驱动因子 driving factor	均方误差增加率/% Inc- MSE	节点纯度增加量 IncNode- purity	均方误差增加率/% Inc- MSE	节点纯度增加量 IncNode- purity
LPI	GDP	4.785 551	7 108.098	3.143 433	3 693.219
	AAP	3.388 449	5 304.884	0.546 604	3 797.038
	AAT	3.065 449	6 344.464	2.418 124	5 692.126
	DEM	2.199 469	5 475.079	0.349 812	3 917.018
PARA_AM	GDP	5.988 872	11 540.961	2.680 116	5 021.900
	AAP	2.362 884	9 358.769	1.482 322	6 732.288
	AAT	5.243 314	11 577.319	2.084 016	10 582.374
	DEM	1.784 031	8 602.880	0.754 283	6 576.693
PD	GDP	5.202 802	7 392.534	4.018 368	3 287.379
	AAP	0.861 838	5 373.772	1.405 345	4 611.290
	AAT	5.729 898	7 079.472	3.975 995	5 921.176
	DEM	2.466 206	6 326.952	0.601 584	4 332.067
PLAND	GDP	5.992 632	6 861.103	4.779 373	3 983.923
	AAP	1.098 695	5 448.096	1.970 885	4 118.814
	AAT	4.316 799	6 559.269	4.653 497	5 974.842
	DEM	0.087 791	5 677.042	0.072 797	3 635.386

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