Spatial distribution of cultural ecosystem services demand and supply in urban and suburban areas: A case study from Shanghai, China

Bing, Zhenhua; Qiu, Yishu; Huang, Heping; Chen, Tingzhen; Zhong, Wei; Jiang, Hong

doi:10.1016/j.ecolind.2021.107720

Cited by 55 publications

(22 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study adopted a four-step approach ( Figure 2 ), as follows: (1) we established a supply-and-demand coordination evaluation index system; (2) we quantified and spatially visualized the carrying capacity of medical resources; (3) we calculated the coupling coordination degree; and (4) we performed a matching analysis of the spatial supply and demand of medical resources. This paper utilized a spatial autocorrelation tool (local Moran index) to identify high- and low-value spatial clusters of supply levels and populations in Shenzhen [ 23 , 24 ]. To further refine the spatial distribution of medical resources in terms of demand, this study collected workload indicators for 64 hospitals that largely corresponded to hospital supply points, including total visits, outpatient visits, emergency visits, inpatient visits, and hospital discharges.…”

Section: Methodsmentioning

confidence: 99%

Identifying Spatial Matching between the Supply and Demand of Medical Resource and Accessing Carrying Capacity: A Case Study of Shenzhen, China

Wang

et al. 2022

IJERPH

View full text Add to dashboard Cite

Previous Studies, such as the evaluation of the supply of and demand for regional medical resources and carrying capacity assessments, require further development. This paper aims to evaluate the carrying capacity and spatial distribution of medical resources in Shenzhen from the perspective of supply and demand, and to conduct a time-series variation of the coupling coordination degree from 1986 to 2019. The two-step floating catchment area method was employed to quantify the carrying capacity and coupling coordination degree method and spatial autocorrelation analysis were applied to analyze spatial distribution between supply and demand. The results were as follows. (1) The carrying capacity index in more than 50% of the districts was classified as low-grade. The percentage of regions with good grades was 8.27%. The regions with a high carrying capacity were distributed in the central and southeastern areas. (2) The coupling coordination continued to rise, increasing from 0.0058 in 1986 to 0.3352 in 2019. (3) The level of supply and demand for medical resources in Shenzhen increased from 1986 to 2019, and the highest degree of compatibility between the supply and the population size was largely concentrated in the western and eastern regions. This research can provide a theoretical reference for Shenzhen to rationally plan medical resources and improve the carrying capacity of medical resources.

show abstract

Section: Methodsmentioning

confidence: 99%

Identifying Spatial Matching between the Supply and Demand of Medical Resource and Accessing Carrying Capacity: A Case Study of Shenzhen, China

Wang

et al. 2022

IJERPH

View full text Add to dashboard Cite

show abstract

“…[ 1 , 2 , 29 ]. In the meantime, another study demonstrated CES variations between the urban center and suburban areas [ 6 ]. However, there is little in-depth discussion on the difference in spatial patterns of CES among diverse agricultural land use types.…”

Section: Discussionmentioning

confidence: 99%

“…Due to their intangible and subjective characteristics, CES values are difficult to measure [ 1 , 4 ]. As researchers and practitioners have recognized the crucial role of CES in promoting human well-being and exceptionally motivated environmental action [ 5 ], a growing number of studies have started to address CES [ 1 , 2 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Revealing Spatial Patterns of Cultural Ecosystem Services in Four Agricultural Landscapes: A Case Study from Hangzhou, China

et al. 2022

IJERPH

View full text Add to dashboard Cite

Monitoring and mapping agricultural cultural ecosystem services (CES) is essential, especially in areas with a sharp contradiction between agricultural land protection and urban development. Despite research assessing CES increasing exponentially in recent years, our knowledge of the CES of agricultural landscapes is still inadequate. This study used four types of agricultural landscapes in Hangzhou, China, as the study area, analyzed their CES spatial patterns, and explored their societal preferences by integrating the multi-sourced datasets, clustering algorithms, and Maxent model. The results indicated that hot spots of agricultural CES correspond to river valley plains, which were also easily vulnerable to urbanization. Moreover, we found that the CES level of paddy field and dry farmland were higher than tea garden and orchard. Based on the above spatial patterns of supply, demand, and flow of CES, we identified four groups of agricultural land by cluster analysis, distinguishing between significant, unimportant, little used, and potential CES. Further, our results showed that natural and human factors could explain societal preferences. This study can provide a valuable basis for stakeholders to develop balanced strategies by the aforementioned results.

show abstract

“…For example, the human activities of urban construction, forest, and grassland into an impermeable surface, resulting in the decline of the ability to provide ES. Payments for Environmental Services (PES) practices around the world, such as China's "conversion of cropland to forest and grassland" and the South African government's Working for Water program, have improved soil conservation (SC) and water yield (WY) in the region (Wei et al, 2017;Wu et al, 2019;Bing et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Temporal and Spatial Patterns of Ecosystem Services and Exploring the Spatial Differentiation of Driving Factors: a Case Study of Sichuan Basin, China

Wang

et al. 2022

Front. Environ. Sci.

View full text Add to dashboard Cite

Exploring the factors that drive the change of ecosystem services (ES) is very important for maintaining ES function and zoning ecological management, especially in the Sichuan Basin area with high spatial heterogeneity such as natural and socio-economic characteristics. Taking the Sichuan Basin in China as an example, the PCA-MGWR model was constructed to explore the temporal and spatial patterns of ES in the Sichuan Basin from 2000 to 2015. The potential driving factors including anthropogenic factors, geomorphological factors, climate factors, and vegetation factors would be analyzed by principal component analysis (PCA). To illustrate the impact of spatial dependence in the data, the multi-scale geographically weighted regression (MGWR) technology was selected to explore the spatial differentiation of the impact of these four dimensions on ES to reflect the local differences of ecosystem service driving mechanisms in more detail. The results showed that 1) from the perspective of time series evolution, carbon storage (CS) and soil conservation (SC) in ES in the Sichuan Basin showed an upward trend, while water yield (WY) showed a downward trend; from the perspective of spatial patterns, except the main urban areas of Chengdu and Chongqing, the CS service level of other regions was high; The spatial distribution characteristics of SC services were “low in the middle and high in the periphery”; the high value area of WY service was located in Northeast Sichuan. 2) Among natural factors, elevation (DEM), slope (SLO), NDVI, annual average temperature (TEM), and annual average precipitation (PRE) had a higher contribution rate to ES, while among socio-economic factors, GDP density (GDP), night light (LIG), and population density (POP) had a higher contribution rate to ES, while other factors had a lower contribution rate. 3) Combined with the PCA-MGWR model, we analyzed the comprehensive response and spatial differentiation of driving factors to ES in the Sichuan Basin and explained in detail the influence of anthropogenic factors, geomorphological factors, climatic factors, and vegetation factors and their spatial heterogeneity in ES. It is expected that the spatial differences in the impact degree of different indicators can be considered when formulating the countermeasures of ES in the Sichuan Basin, to provide theoretical support for the implementation of regional ecological management and control.

show abstract

Spatial distribution of cultural ecosystem services demand and supply in urban and suburban areas: A case study from Shanghai, China

Cited by 55 publications

References 59 publications

Identifying Spatial Matching between the Supply and Demand of Medical Resource and Accessing Carrying Capacity: A Case Study of Shenzhen, China

Identifying Spatial Matching between the Supply and Demand of Medical Resource and Accessing Carrying Capacity: A Case Study of Shenzhen, China

Revealing Spatial Patterns of Cultural Ecosystem Services in Four Agricultural Landscapes: A Case Study from Hangzhou, China

Quantifying the Temporal and Spatial Patterns of Ecosystem Services and Exploring the Spatial Differentiation of Driving Factors: a Case Study of Sichuan Basin, China

Contact Info

Product

Resources

About