Indexing coordination of ecosystem and urban economic vitality in coastal cities: An observation in yangtze river delta

Advanced geographic technologies provide an opportunity to understand the urban forest landscape and guide the governance of the urban ecosystem. However, only few studies stressed the importance of data techniques in understanding urban sustainability, especially urban forest landscape. Therefore, this study makes an analysis of urban forest resources in a city of Yangtze River Delta with the help of multi-source data techniques and further data analysis of different forest landscape pattern indices in the study area with the help of SPSS (Statistical Product and Service Solutions). The following conclusions are drawn: 1) According to the visual analysis, the spatial distribution of forest patches in the study area has a great difference. 2) All the seven landscape pattern indices are positively correlated with the distribution density of POI (Point of Interest), which represents the urban economic vitality. The correlation coefficients are NP (R2 = 0.3063), PD (R2 = 0.0079), ED (R2 = 0.3955), AREA (R2 = 0.5408), CONTIG (R2 = 0.0323), PAFRAC (R2 = 0.3662) and AI (R2 = 0.2014), respectively. This indicates that the higher the economic vitality is, the more fragmented and complex the urban forest patches are. 3) According to the geographically weighted regression model, the goodness of fit between the spatial distribution density of POI and NP, PD, ED, and AI reaches 0.804, 0.771, 0.634, and 0.619, respectively, and the explanatory power of the model is more than twice that of the corresponding linear regression model. The data illustrates that the correlation between economic vitality and urban forest landscape pattern indices has significant spatial heterogeneity.

Abstract licence: CC BY

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