Evaluating the social media attributes of urban blue-green open space using a back propagation neural network

doi:10.12302/j.issn.1000-2006.202306020

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2024, Vol. 48 ›› Issue (6): 193-200.doi: 10.12302/j.issn.1000-2006.202306020

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Evaluating the social media attributes of urban blue-green open space using a back propagation neural network

XU Haishun(), QIAN Chen, QIN Xue

College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China

Received:2023-06-19 Revised:2023-11-09 Online:2024-11-30 Published:2024-12-10

Abstract

Abstract:

【Objective】Through the analysis of the needs and activity patterns of urban blue-green open space (BGOS) users, the social media attributes of urban BGOS can best serve people were identified. The aim was to construct a scientifically based evaluation system that enhanced the “People-BGOS-Society” relationship and provide a reference for corresponding management planning.【Method】Based on literature research, field surveys, and network data collection, from the perspective of BGOS as the urban social medium, an evaluation model of the social media attributes of urban BGOS was constructed based on four dimensions: space background, connection type, participation mode, and spatial significance. Taking three urban parks in Nanjing as an examples, a back propagation (BP) neural network model was used for model verification and a weighted quantitative analysis.【Result】By studying the survey data, the BP neural network evaluated the social media attributes of urban BGOS. The evaluation model included four first-level indicators and 12 second-level indicators. The first-level indicators included spatial background, connection type, participation mode, and spatial significance, among which spatial background (weight 0.440) was the key factor for evaluating the social media attributes. Among the secondary indicators, the natural support level (weight 0.157) had the greatest impact, followed by infrastructure perfection (weight 0.127), microclimate comfort (weight 0.125), and local identity (weight 0.121), while the remaining parameters showed relatively little impact. The quality of the spatial background was the basis for attracting users to carry out social activities. The close “People-BGOS-Society” relationship helped to improve the spatial level of social media attributes.【Conclusion】This study combined sociology with the field of landscape architecture. From the perspective of the relationship between people and space, the application of a BP neural network model was a novel research concept and methods were developed for the identification and evaluation of the social benefits of BGOS.

Key words: blue-green open space (BGOS), BP neural network, social media, attribute evaluation, Nanjing City

CLC Number:

TU984.115

XU Haishun, QIAN Chen, QIN Xue. Evaluating the social media attributes of urban blue-green open space using a back propagation neural network[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY, 2024, 48(6): 193-200.

Figures/Tables 9

Fig. 1

Table 1

Assessment indicator model and data sources of BGOS"

目标层 target layer	要素层 factor ayer	指标层 indicator layer	指标描述与量化标准(方法) standard (methodology) for indicator description and quantification	调查途径 investigative approach
本底质量 basis of space	蓝/绿视率		蓝/绿色在人视野里的面积占人视野总面积的比例	实地调研
	微气候舒适度		游憩环境中人们感受到的舒适程度(舒适度指数K)	实地调研
	基础设施完善度		与环境的协调度、基础设施的功能性	问卷
	景观美感		人们能够体验到的视觉景观美的程度	问卷
连接方式 connection type	自然支持	交通可达性	居民以适宜交通方式到达公园所用的时间,选择:<10 min,≥10~30 min,≥0.5~1.5 h,>1.5 h	问卷
		参观频率	游客到访蓝绿空间的频率,选择:每天都来,每周2~3次,每周1次,每月1次,每年2~3次	问卷
		停留时间	游客自然体验的停留时间,选择:1 h以内,≥1~3 h,≥3~5 h,≥5 h	问卷
	社会支持	与他人接触强度	出行人员关系,反映交往双方情感与联系紧密程度,包括:视听接触,偶然接触,熟人、朋友、家人	问卷,微博数据
		与他人接触广度	以接触总人数和游客出行组织方式表征,包括:独自出行,2~4人,5人及以上;分别对应个人活动、小团体活动与群体活动	问卷,微博数据
参与方式 way of participation	认知型参与	公园的重要性与象征性	游客对公园的重视程度及借助游览公园表达或传递某种意义或信息的意愿程度	问卷
	情感型参与	参与的愉悦性	游客在公园游览中获得的乐趣多少	问卷,实地调研
	行为型参与	活动类型意向	健身、休闲游乐、交流与扩展交际3类活动的活动意向	问卷
		游后行为意向	重游意向和推荐意向	问卷
空间意义 meaning of space	地方依赖		功能层面,游客对公园资源、设施、活动等需求的满意程度	问卷
	地方认同		精神层面,游客对公园产生的情感依恋与归属感	问卷

Table 1

Table 2

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Table 3

Table 4

Fig. 4

Table 5

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目标层 target layer	指标层 indicator layer	指标等级及对应值阈indicator level and corresponding value range
目标层 target layer	指标层 indicator layer	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅴ
本底质量 basis of space	蓝视率/%	≥40	[30,40)	[0,5)或[20,30)	[5,10)或[15,20)	[10,15)
	绿视率/%	≤7	[7,15)	[15,30)	[30,50)	≥50
	微气候舒适度	<25或≥85	[25,40)或[80,85)	[40,50)或[75,80)	[50,60)或[70,75)	[60,70)
	基础设施完善度	<1.500	[1.500,2.500)	[2.500,3.500)	[3.500,4.500)	[4.500,5.000)
	景观美感	<1.500	[1.500,2.500)	[2.500,3.500)	[3.500,4.500)	[4.500,5.000)
连接方式 connection type	自然支持	<0.600	[0.600,1.200)	[1.200,1.800)	[1.800,2.400)	[2.400,3.000)
	社会支持	<0.400	[0.400,0.800)	[0.800,1.200)	[1.200,1.600)	[1.600,2.000)
参与方式 way of participation	认知型参与	<1.500	[1.500,2.500)	[2.500,3.500)	[3.500,4.500)	[4.500,5.000)
	情感型参与	<1.500	[1.500,2.500)	[2.500,3.500)	[3.500,4.500)	[4.500,5.000)
	行为型参与	<1.500	[1.500,2.500)	[2.500,3.500)	[3.500,4.500)	[4.500,5.000)
空间意义 meaning of space	地方依赖	<1.500	[1.500,2.500)	[2.500,3.500)	[3.500,4.500)	[4.500,5.000)
	地方认同	<1.500	[1.500,2.500)	[2.500,3.500)	[3.500,4.500)	[4.500,5.000)

指标 indicator	水平 level	蓝视率 blue- vision ratio	绿视率 green- vision ratio	舒适度 micro- climate comfort	基础设施 basic facility	景观美感 landscape aesthetics	自然支持 nature support	社会支持 social support	认知参与 cognitive part	情感参与 emotion parti	行为参与 behavior part	地方依赖 place dependence	地方认同 place identity
水平level	1.000
蓝视率blue-vision ratio	-0.263	1.000
绿视率green-vision ratio	0.445^*	-0.070	1.000
舒适度microclimate comfort	-0.459^*	-0.115	-0.258	1.000
基础设施infrastructure	0.475^*	0.068	0.204	-0.242	1.000
景观美感landscape aesthetics	0.262	-0.015	-0.047	-0.017	0.568^**	1.000
自然支持nature support	0.346	-0.175	0.624^**	0.007	-0.011	-0.224	1.000
社会支持social support	0.428^*	-0.373	0.234	-0.020	-0.154	-0.283	0.212	1.000
认知参与cognitive part	0.514^*	-0.238	0.448^*	-0.277	0.482^*	0.542^**	0.351	-0.136	1.000
情感参与emotion part	0.574^**	-0.411^*	0.313	-0.213	0.180	0.267	0.471^*	0.203	0.601^**	1.000
行为参与behavior part	0.352	-0.157	0.269	-0.166	0.229	0.279	0.258	0.120	0.625^**	0.681^**	1.000
地方依赖place dependence	0.548^**	-0.498^*	0.110	-0.120	0.378	0.387	0.304	0.062	0.500^*	0.613^**	0.383	1.000
地方认同place identity	0.549^**	-0.500^*	0.112	-0.125	0.381	0.391	0.297	0.062	0.502^*	0.612^**	0.386	1.000^**	1.000

指标 indicator	R²	Durbin-Watson检验 DW test	F	显著性 sig.	常数 constant	回归系数 B
微气候舒适度microclimate comfort	0.166	1.650	4.382	0.048	0.773	-0.065
自然支持nature support	0.201	1.732	5.521	0.028	0.633	0.178
社会支持social support	0.453	1.903	18.242	<0.001	0.681	0.160
认知型参与cognitive participation	0.163	1.711	4.288	0.050	0.709	0.062
情感型参与emotion participation	0.316	1.861	10.157	0.004	0.681	0.089
地方依赖place dependence	0.186	1.213	5.020	0.035	0.704	0.057
地方认同place identity	0.186	1.212	5.041	0.035	0.678	0.079

Evaluating the social media attributes of urban blue-green open space using a back propagation neural network

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一级指标 first indicator	二级指标 secondary indicator	神经网络输出权重 neural network output weight	综合权重 combined weight
空间本底 basis of space	蓝视率	0.045
	绿视率	0.091
	微气候舒适度	0.125	0.440
	基础设施完善度	0.127
	景观美感	0.052
连接方式 connection type	自然支持	0.157	0.216
	社会支持	0.059
参与方式 way of participation	认知型参与	0.039
	情感型参与	0.061	0.160
	行为型参与	0.060
空间意义 meaning of space	地方依赖	0.063	0.184
	地方认同	0.121

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