Zhengxi Fan

Urban green space (UGS) provides critical ecosystem services and alleviates environmental problems caused by rapid urbanization. The Analytic Hierarchy Process (AHP) method is recognized as a traditional technique to identify the weight of the UGS suitability evaluation. We reveal the limitations of the AHP method for its subjectivity and uncertainty. Then, we introduce the AHP and coefficient of variation (AHP-CV) combined weight method to better evaluate the suitability of UGS. Based on the principle of minimum information entropy, the AHP-CV combined weight method takes advantage of both the AHP and CV methods, thus keeping a good balance between subjectivity and objectivity. We used the green space system planning of Fuping County in China as a case study. A new evaluation index system was established using 4 aspects. Our results show that high-suitability areas are mainly distributed around the northern mountainous regions, 2 important rivers and the outer areas of the central city. By comparing the UGS suitability evaluation results obtained by the AHP, CV, and AHP-CV combined weight methods, we found that the AHP-CV method was optimal. Therefore, the AHP-CV combined weight method will not only enrich spatial Multi-Criteria Decision-Making techniques but also have a wide application in the related fields of land-use planning.

The potential of urban waterfronts as vibrant urban spaces has become a focus of urban studies in recent years. However, few studies have examined the relationships between urban vitality and built environment characteristics in urban waterfronts. This study takes advantage of emerging urban big data and adopts hourly Baidu heat map (BHM) data as a proxy for portraying urban vitality along the Yangtze River in Nanjing. The impact of built environment on urban vitality in urban waterfronts is revealed with the ordinary least squares (OLS) and geographically weighted regression (GWR) models. The results show that (1) the distribution of urban vitality in urban waterfronts shows similar agglomeration characteristics on weekdays and weekends, and the identified vibrant cores tend to be the important city and town centers; (2) the building density has the strongest positive associations with urban vitality in urban waterfronts, while the normalized difference vegetation index (NDVI) is negative; (3) the effects of the built environment on urban vitality in urban waterfronts have significant spatial variations. Our findings can provide meaningful guidance and implications for vitality-oriented urban waterfronts planning and redevelopment.