Spatial heterogeneous relationship between ecosystem services and human disturbances: A case study in Chuandong, China

Han, Rui; Feng, Chen‐Chieh; Xu, Nuanyin; Guo, Luo

doi:10.1016/j.scitotenv.2020.137818

Cited by 99 publications

(45 citation statements)

References 34 publications

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“…Hence, it is necessary to study the relationship between LF and human activities in suburban rural communities. Although the interaction between LFs and human activities is extremely strong according to previous studies [ 39 , 66 ], the focus is on how humans affect LF (especially ecological service function) without considering the positive and negative impacts of LFs on human activities. In this study, multi-source data were used to study the correlation and mechanism of human activity intensity and LF in suburban rural communities at regional scale, which can better highlight the characteristics of suburban rural communities.…”

Section: Discussionmentioning

confidence: 99%

Exploring Spatial Variations in the Relationships between Landscape Functions and Human Activities in Suburban Rural Communities: A Case Study in Jiangning District, China

Zheng

Chen

Zhang

et al. 2021

IJERPH

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There is a complicated and contradictory relationship between landscape functions and human activities, especially in the suburban rural communities of metropolises. Previous studies focused on human interference to landscape function, ignoring the impact of landscape functions on human activities. Hence, the present study is focused on the impact of landscape function (based on ecosystem services) on human activities in suburban rural communities of China. The study evaluated the intensity of human activities based on big data; furthermore, the authors analyzed the spatial distribution characteristics through spatial autocorrelation, and probed into the spatial variations in the relationship between human activities and landscape functions using ordinary least squares (OLS) and geographically weighted regression (GWR) models. The result indicates that there are obvious spatial distribution differences in the intensity of human activities in suburban rural communities; that is, the intensity decreases from the inner to the outer suburban areas. Positive influencing factors of human activities are construction area, bus station, road network density, and leisure entertainment, among which, construction area is the principal driver; cultural heritage, hydrological regulation, and provision of aesthetics are negatively or positively correlated with human activities in various regions. The results offer insights for the sustainable development of rural environment in suburban areas and the big data-driven rural research.

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Section: Discussionmentioning

confidence: 99%

Exploring Spatial Variations in the Relationships between Landscape Functions and Human Activities in Suburban Rural Communities: A Case Study in Jiangning District, China

Zheng

Chen

Zhang

et al. 2021

IJERPH

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“…The spatial models that estimate the cold and hot spots of spatial aggregation are calculated by Getis-Ord Gi � . Getis-Ord Gi � is a spatial statistical method that can describe and create visualizations of spatial distributions, find local spatially related patterns, identify heterogeneous units, and suggest spatial states [26]. The calculation of the REL for Fuzhou from 2015 to 2019 based on cold and hot spots shows spatial aggregations of similar values (Fig 3).…”

Section: Plos Onementioning

confidence: 99%

Spatial heterogeneity in and distributional characteristics of rural ecological livability in China——The case of Fujian Province

Xiao-li

Wang

et al. 2020

PLoS ONE

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With the outbreak of COVID-19, the importance of rural areas has been gradually highlighted, and the importance of rural ecological livability has been gradually recognized. A growing body of literature recognizes the importance of building a rural ecological livability (REL) system. It is urgent that we clarify the status quo and spatial-temporal differences in and distributional characteristics of rural ecological livability and that we carry out targeted and differentiated construction to promote rural ecological livability in post-epidemic China. This study proposes a conceptual model that incorporates various economic, social and environmental factors and develops a comprehensive multifactor (production-living-ecology) evaluation system. Using Fujian Province as an example, the entropy weight method is used to measure the REL level of 55 counties and cities, which are comprehensively evaluated from 2015 to 2019. Moran's I and Getis-Ord Gi* are used to analyze the spatial and distributional characteristics of the REL level in Fujian. The results show that the level of REL in Fujian Province has been relatively flat over the past five years, with a slight downward trend. The overall value of the rural ecological livability index in 2015 was 0.345, and its overall value in 2019 was 0.334, with an average value of 0.343. The REL of Fujian Province is spatially correlated, with high levels of livability in the southeast and low levels in the northeast. The autocorrelation in the level of ecological livability in Fujian's counties and cities continues to increase.

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“…Thus, Nanjing City may be at a later stage of development and thus will fall on the right side of the Ushaped curve. Similarly, the relationships among population, light index, and ESVs are also controversial [45][46][47][48] For example, Han found that the influence trend of the population on ESV is different in the high-ESV region and low-ESV region [45]. Studies on the relationships between ESVs and urbanization generally indicate that urban expansion has positive or negative correlations with the values of different ecosystem services [47,48].…”

Section: Plos Onementioning

confidence: 99%

Deep learning: To better understand how human activities affect the value of ecosystem services—A case study of Nanjing

Liu

Wang

et al. 2020

PLoS ONE

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The value of ecosystem services is affected by increasing human activities. However, the anthropogenic driving mechanisms of ecosystem services are poorly understood. Here, we established a deep learning model to approximate the ecosystem service value (ESV) of Nanjing City using 23 socioeconomic factors. A multi-view analysis was then conducted on feasible impact mechanisms using model disassembly. The results indicated that certain factors had their own significant and independent effects on ESV, such as the proportion of water areas in the land-use structure and the output value of the secondary industry. The proportion of ecological water should be increased as much as possible, whereas the output value of the secondary industry should be reasonably controlled in Nanjing. Other intrinsically related factors were likely to be composited together to affect ESV, such as industrial water consumption and industrial electricity consumption. In Nanjing, simultaneously optimizing socioeconomic factors related to city size, resources, and energy use efficiency likely represents an effective management strategy for maintaining and enhancing regional ecological service capabilities. The results of this work suggest that deep learning is an effective method of deepening studies on the prediction of ESV trends and human-driven mechanisms.

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Spatial heterogeneous relationship between ecosystem services and human disturbances: A case study in Chuandong, China

Cited by 99 publications

References 34 publications

Exploring Spatial Variations in the Relationships between Landscape Functions and Human Activities in Suburban Rural Communities: A Case Study in Jiangning District, China

Exploring Spatial Variations in the Relationships between Landscape Functions and Human Activities in Suburban Rural Communities: A Case Study in Jiangning District, China

Spatial heterogeneity in and distributional characteristics of rural ecological livability in China——The case of Fujian Province

Deep learning: To better understand how human activities affect the value of ecosystem services—A case study of Nanjing

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