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Remote Sensing for Natural Resources    2024, Vol. 36 Issue (3) : 88-95     DOI: 10.6046/zrzyyg.2023107
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Assessment of urban ecological quality based on the remote sensing green index: A case study of Nanjing City
PAN Jinyin1(), WANG Shidong1, FAN Qinhe2()
1. School of Surveying,Mapping and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
2. Party School of Jiaozuo Municipal Committee of CPC, Jiaozuo 454000, China
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Abstract  

The monitoring and assessment of urban ecological quality holds critical significance for sustainable urban development. To assess the ecological quality of developed coastal cities in China in recent years, this study investigated Nanjing City based on the Sentinel-2A remote sensing images obtained in 2021. It constructed a novel remote sensing green index (RSGI) model involving green spaces, blue spaces, buildings, and impervious surfaces for assessing the ecological quality of Nanjing. First, neural network supervised classification was applied to the Sentinel-2A remote sensing images, constructing the RSGI to assess the ecological quality of various districts in Nanjing. Then, the correlations between the RSGI and urban ecological factors were analyzed using the Pearson correlation coefficient. Finally, the ecological similarity between the districts was analyzed using the agglomerative hierarchical clustering method. The results of this study are as follows: (1) The ecological quality of Nanjing presented a pattern of low RSGI values in the central portion and high RSGI values in the surrounding areas, with the highest and lowest RSGI values (0.86 and 0.38) observed in Luhe and Qinhuai districts, respectively, differing by 0.48; (2) The RSGI exhibited a positive correlation with the density of green spaces and negative correlations with the densities of population, buildings, and impervious surfaces, all at the 0.01 level; (3) With the ecological similarity of 70% as the threshold, 11 districts in Nanjing were categorized into four clusters: Qinhuai, Gulou, and Jianye districts in the first cluster, Yuhuatai and Qixia districts in the second cluster, Xuanwu and Gaochun districts in the third cluster, and the rest four districts in the fourth cluster. The results of this study can provide a scientific basis for subsequent urban planning and sustainable development of Nanjing.
Keywords RSGI      ecological quality      Pearson correlation coefficient      urban blue-green space      Nanjing City     
ZTFLH:  TP79  
Issue Date: 03 September 2024
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Jinyin PAN
Shidong WANG
Qinhe FAN
Cite this article:   
Jinyin PAN,Shidong WANG,Qinhe FAN. Assessment of urban ecological quality based on the remote sensing green index: A case study of Nanjing City[J]. Remote Sensing for Natural Resources, 2024, 36(3): 88-95.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2023107     OR     https://www.gtzyyg.com/EN/Y2024/V36/I3/88
Fig.1  Geographical location of the study area
数据类型 数据名称 时间 来源
栅格数据 Sentinel-2A遥感影像 2021年 欧洲航天局哥白尼开放数据访问中心
矢量数据 县界矢量边界 2015年 中国科学院资源环境科学与数据中心
栅格数据 人口密度1 km×
1 km网格数据		 2019年 中国科学院资源环境科学与数据中心
栅格数据 GDP分布1 km×
1 km网格数据		 2019年 中国科学院资源环境科学与数据中心
Tab.1  Data sources
生态环境质量等级 RSGI值范围
低生态环境质量 [0.0,0.2)
较低生态环境质量 [0.2,0.5)
较高生态环境质量 [0.5,0.8)
高生态环境质量 [0.8,1.0]
Tab.2  Classification standards for ecological environment quality
Fig.2  Land cover types in Nanjing City
地区 BGIP BGBP RSGI 绿色空间密度 蓝色空间密度
秦淮区 0.51 0.25 0.38 0.16 0.03
鼓楼区 0.59 0.27 0.43 0.16 0.06
建邺区 0.68 0.49 0.59 0.23 0.15
雨花台区 0.74 0.51 0.62 0.39 0.03
栖霞区 0.81 0.60 0.71 0.39 0.12
玄武区 0.84 0.62 0.73 0.50 0.04
高淳区 0.78 0.76 0.77 0.51 0.10
江宁区 0.87 0.75 0.81 0.60 0.05
溧水区 0.88 0.79 0.83 0.57 0.11
浦口区 0.89 0.80 0.84 0.61 0.09
六合区 0.91 0.82 0.86 0.66 0.08
南京市 0.86 0.75 0.81 0.57 0.08
Tab.3  Statistics of RSGI values in Nanjing and its districts
Fig.3  Ecological environment quality level map of various districts in Nanjing City
地区 RSGI 人口密度/
(人·km-2)		 建筑
密度		 不透水地
表面密度		 蓝色空
间密度		 绿色空
间密度
秦淮区 0.38 14 490 0.58 0.19 0.03 0.16
鼓楼区 0.43 17 423 0.60 0.15 0.06 0.16
建邺区 0.59 3 283 0.40 0.18 0.15 0.23
雨花台区 0.62 1 835 0.40 0.15 0.03 0.39
栖霞区 0.71 1 101 0.34 0.11 0.12 0.39
玄武区 0.73 6 755 0.33 0.10 0.04 0.50
高淳区 0.77 542 0.19 0.17 0.10 0.51
江宁区 0.81 607 0.22 0.10 0.05 0.60
溧水区 0.83 394 0.18 0.10 0.11 0.57
浦口区 0.84 650 0.18 0.08 0.09 0.61
六合区 0.86 602 0.17 0.08 0.08 0.66
Tab.4  Statistical table of ecological elements in various districts of Nanjing City
生态要素 指标 RSGI 人口密度 建筑密度 不透水地表
面密度		 蓝色空间
密度		 绿色空间
密度
RSGI 皮尔逊相关性 1 -0.867**① -0.981** -0.783** 0.297 0.969**
Tab.5  Pearson correlation coefficient analysis between RSGI and ecological elements
分级 人口密度/(人·km-2) GDP/(万元·km-2)
低 [0,600) [0,5 000)
较低 [600,1 000) [5 000,15 000)
中等 [1 000,2 000) [15 000,30 000)
较高 [2 000,10 000) [30 000,50 000)
高 [10 000,∞) [50 000,∞)
Tab.6  Population density and GDP grading standards
Fig.4  Population density and GDP level distribution map of Nanjing City
Fig.5  Family tree of aggregated hierarchical clustering analysis in various districts of Nanjing
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