Evolution and change of an urban greenspace: A case study on the outer ring of Shanghai

doi:10.3969/j.issn.1000-5641.2021.02.010

Abstract

Abstract:

Urban greenspace is an important part of the urban green system and urban landscape, with important ecological, social, psychological, and economic functions. The evolutionary trajectories and change patterns of urban greenspaces are of great significance to the sustainable development of urban green space systems and the optimization of the urban ecological network. There is ongoing emphasis on urban greenspace research; most previous research studies on greenspace changes have used landscape indices and spatial analysis methods, which struggle to accurately reflect the change process, change types, and spatial distribution patterns of greenspace. In our paper, seven types of greenspace evolution were defined, including continuous, expansion, contraction, dissipation, creation, merging, and splitting. Then, an evolution graph was constructed by defining greenspace patches as nodes and greenspace evolution relations as edges. Based on the greenspace evolution graph, the greenspace evolution process and its corresponding evolutionary trajectory were further extracted and visualized. Taking the Shanghai city center as a case study area, the spatial distribution pattern and change process of the urban greenspace for 2008, 2012, and 2016 were extracted. Results indicated that the most dominant greenspace evolution types were creation and dissipation. The newly added urban greenspace patches were more evenly distributed compared with those patches involved with an evolution type of dissipation. Small patches were more likely to be located in the urban center, while large patches tended to be concentrated in rural areas. The location of greenspace patches that disappeared were mostly concentrated in non-central areas, particularly in the Pudong New Area. Compared with the urban greenspace changes between 2008 and 2012, locations where new greenspace appeared between 2012 and 2016 were more evenly distributed, while locations where greenspace disappeared were more concentrated.

Key words: urban greenspace, types of evolution, evolutionary graph/evolution track, greenspace change

CLC Number:

K909

Qiong WANG, Bin WU, Shenjun YAO, Jianping WU, Ying ZHOU, Jing ZHANG. Evolution and change of an urban greenspace: A case study on the outer ring of Shanghai[J]. Journal of East China Normal University(Natural Science), 2021, 2021(2): 100-109.

Figures/Tables 10

Fig.1

Table 1

Fig.2

Fig.3

Fig.4

Fig.5

Table 2

Fig.6

Fig.7

Fig.8

References 34

1	郑西平. 北京城市绿地系统功能评价与发展策略 [D]. 北京: 北京林业大学, 2011.
2	王娟, 蔺银鼎. 城市绿地生态效应. 草原与草坪, 2004, (4): 24- 27. doi: 10.3969/j.issn.1009-5500.2004.04.006
3	王保忠, 王彩霞, 何平, 等. 城市绿地研究综述. 城市规划学刊, 2004, (2): 62- 68. doi: 10.3969/j.issn.1000-3363.2004.02.014
4	贾刘强. 城市绿地缓解热岛的空间特征研究 [D]. 西安: 西南交通大学, 2009.
5	柳云龙, 朱建青, 施振香. 上海城市绿地净化服务功能及其价值评估. 中国人口·资源与环境, 2009, 19 (5): 28- 32. doi: 10.3969/j.issn.1002-2104.2009.05.006
6	邹晓东. 城市绿地系统的空气净化效应研究 [D]. 上海: 上海交通大学, 2007.
7	陆旭蕾, 刘艳, 粟志峰, 等. 城市绿地对减弱环境噪声作用的探讨. 石河子科技, 2003, (5): 17- 18. doi: 10.3969/j.issn.1008-0899.2003.05.006
8	郭伟, 申屠雅瑾, 邓巍, 等. 城市绿地对小气候影响的研究进展. 生态环境学报, 2008, 17 (6): 2520- 2524. doi: 10.3969/j.issn.1674-5906.2008.06.074
9	武文婷. 杭州市城市绿地生态服务功能价值评估研究 [D]. 南京: 南京林业大学, 2011.
10	孟宪章, 温长宽. 论徐州城市绿地与环境效益. 环境科技, 1990, (3): 25- 27.
11	赵春黎. 城市绿地系统规划存在的问题及建议. 价值工程, 2014, (27): 296- 297. doi: 10.3969/j.issn.1006-4311.2014.27.156
12	STIGSDOTTER U K. Use of small public urban green spaces (SPUGS). Urban Forestry & Urban Greening, 2012, 11 (3): 235- 244.
13	SAPHORESABCC J D. Estimating the value of urban green areas: A hedonic pricing analysis of the single family housing market in Los Angeles, CA. Landscape & Urban Planning, 2012, 104 (3): 373- 387.
14	孔繁花, 尹海伟. 城市绿地功能的研究现状、问题及发展方向. 南京林业大学学报(自然科学版), 2010, 34 (2): 119- 124. doi: 10.3969/j.issn.1000-2006.2010.02.027
15	PESCHARDT K K, STIGSDOTTER U K. Associations between park characteristics and perceived restorativeness of small public urban green spaces. Landscape & Urban Planning, 2013, 112 (112): 26- 39.
16	ULRICH R S. View through a window may influence recovery from surgery. Science, 1984, 224 (4647): 420- 421. doi: 10.1126/science.6143402
17	李铮生. 城市园林绿地规划与设计 [M]. 2版. 北京: 中国建筑工业出版社, 2006.
18	梁东成, 战国强, 许文安. 快速城市化下现代城镇绿地系统建设的思考与对策. 林业与环境科学, 2006, 22 (3): 140- 142. doi: 10.3969/j.issn.1006-4427.2006.03.034
19	张亚男. 长沙市城市绿地景观格局与连通性研究 [D]. 长沙: 中南林业科技大学, 2009.
20	李江平, 许捍卫, 顾祖新. 基于GIS与RS的城市绿地动态变化及驱动力分析. 地理空间信息, 2017, 15 (8): 53- 56. doi: 10.3969/j.issn.1672-4623.2017.08.016
21	李莹莹. 城镇绿色空间时空演变及其生态环境效应研究 [D]. 上海: 复旦大学, 2012.
22	GRIFFITH J A, MARTINKO E A, PRICE K P. Landscape structure analysis of Kansas at three scales. Landscape & Urban Planning, 2000, 52 (1): 45- 61.
23	刘志强, 林存晖, 王俊帝. 中国县城城市绿地建设水平演变分析. 华中建筑, 2019, 37 (6): 14- 17.
24	王雪娜. 基于航空影像的广州市海珠区绿地演变分析. 国土与自然资源研究, 2018, (3): 61- 64. doi: 10.3969/j.issn.1003-7853.2018.03.018
25	王快, 徐元龙. 重庆市城市绿地变化监测方法研究. 中国城市林业, 2017, (5): 50- 53. doi: 10.3969/j.issn.1672-4925.2017.05.011
26	田晓春. 兰州市安宁区城市绿地演变及城市森林服务效应分析[D]. 兰州: 甘肃农业大学, 2017.
27	穆博, 李华威, 何瑞珍, 等. 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. 生态学报, 2017, 37 (14): 4883- 4895.
28	王越, 林箐. 城乡绿地空间破碎化格局研究与启示——以北京市海淀区为例. 中国城市林业, 2018, 16 (2): 10- 15. doi: 10.3969/j.issn.1672-4925.2018.02.003
29	王子维, 程朋根, 喻晓娟. 基于MSPA的景观网络格局时空变化分析: 以抚州市东乡区为例. 江西科学, 2018, (1): 79- 86.
30	王铭子. 基于连接度的城市绿地生态网络研究 [D]. 北京: 北京林业大学, 2010.
31	赵春燕, 李际平, 王国华, 等. 森林资源动态变化的时空拓扑分析. 西北林学院学报, 2010, 25 (2): 216- 220.
32	高金萍, 陆守一. 森林资源小班数据更新管理中时空一体化数据模型研究. 西北林学院学报, 2008, 23 (5): 188- 192.
33	CHEUNG A K L, O’SULLIVAN D, BRIERLEY G. Graph-assisted landscape monitoring. International Journal of Geographical Information Science, 2015, 29 (4): 580- 605. doi: 10.1080/13658816.2014.989856
34	吴宾. 基于对象的地理时空演变分析与知识发现 [D]. 上海: 华东师范大学, 2018.

编号	演化类型	含义
1	连续	绿地斑块没有发生变化
2	扩张	绿地斑块面积增加
3	收缩	绿地斑块面积减少
4	消失	绿地斑块不再存在
5	新增	新增一个绿地斑块
6	合并	2 个或多个绿地斑块合并为一个绿地斑块
7	分解	一个绿地斑块分解为 2 个或多个绿地斑块

年份	扩张	新增	收缩	合并	分解	消失
2008—2012年	6682(1.7%)	81026(20.7%)	11406(2.9%)	978(0.2%)	1493(0.4%)	54085(13.8%)
2012—2016年	6297(1.5%)	59653(14.2%)	10556(2.5%)	1295(0.3%)	1935(0.5%)	44806(10.7%)

[1]	Hui YANG, Jin ZENG, Nai YANG, Fanmin KONG. Effect of compulsory education school quality on housing prices from a spatial perspective [J]. Journal of East China Normal University(Natural Science), 2022, 2022(1): 97-108.
[2]	LYU Zhen-hua, WU Jian-ping, YAO Shen-jun, ZHU Li. FCD-based analysis of taxi operation characteristics: A case of Shanghai [J]. Journal of East China Normal University(Natural Sc, 2017, (3): 133-144.
[3]	CHEN Duan-wei;SHU Jiong;WANG Qiang;DUAN Yu-sen. Analysis of Remote Sensing Image Format —— GeoTIFF(Chinese) [J]. Journal of East China Normal University(Natural Sc, 2006, 2006(2): 18-26.
[4]	MENG Fei;;LIU Min;ZHANG Xin-yi. Extracting Urban Cover and Background Information on ETM Images(Chinese) [J]. Journal of East China Normal University(Natural Sc, 2005, 2005(4): 59-65,8.
[5]	WANG Feng-xia;ZHANG Chao. Studies on Standardization of GIS in Shanghai [J]. Journal of East China Normal University(Natural Sc, 2004, 2004(1): 61-66.