A multi-criteria spatial approach for mapping urban ecosystem services demand. (May 2020) - Li, Fangzheng; Guo, Shiyi; Li, Di; Li, Xiong; Li, Jing; Xie, Shuang
Highlights: A multi-criteria approach integrating demand for ecological and cultural services. We quantified the consumption of green spaces using check-in data. We applied the demand for ES to optimize the ecological security pattern in central Beijing. Abstract: A growing number of studies have mapped the demand for ecosystem services (ES). Recently, demand for ES has been broadened to include cultural services in addition to ecological services, especially for urbanized areas. In this study, a multi-criteria approach is proposed that synthesizes the available ecological and cultural services to map the demand for ES: including 1) soil erosion sensitivity, 2) geological hazard sensitivity, 3) water management, 4) vegetation coverage, 5) permanent farmland, 6) accessibility, 7) population density, 8) direct use of green spaces, and 9) cultural heritage. The cultural services demand describes the desire or preference, and consumption or direct use of cultural services, e.g. recreation and cultural heritage. Most studies discussed only the desire or preference for cultural services because of the difficulty quantifying the actual consumption of these cultural services. This research gap was filled using the check-in data collected from WeChat (a major social network in China). Each criterion was assigned a weight so that the ecological services demand, the cultural services demand, and the overall ES demand could be quantified. The results suggest that in general, the mountainous areas, farmlands, and suburban areas have high demand for ecological services while public parks in urban areas show high demand for cultural services. However, the ES demand in the availability of some small green spaces in highly urbanized areas may be higher than that for large green spaces in suburban areas. This multi-criteria analysis is necessary to obtain a comprehensive assessment of ES demand, which will contribute to improving the applicability of ES in real-world decision making, e.g. green space planning and conservation.