Ecosystem services response to urbanization in metropolitan areas: Thresholds identification

Peng, Jian; Lan, Tian; Liu, Yanxu; Zhao, Mingyue; Hu, Yi’na; Wu, J.

doi:10.1016/j.scitotenv.2017.06.218

Cited by 419 publications

(169 citation statements)

References 49 publications

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“…And transformation factors including age, education level as well as location have significant influence on both rural and urban resident ecological well-being but the degree of influence is different. Rural residents and urban residents have different perception of the ecological services provided by agricultural land because they have a different degree of linkage with agricultural land and different knowledge of agroecosystem functions [60,84,85]. Rural resident ecological well-being experiences greater decline compared to urban residents, because they have closer and more direct contact with agricultural land [82].…”

Section: Discussionmentioning

confidence: 99%

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How does the Ecological Well-Being of Urban and Rural Residents Change with Rural-Urban Land Conversion? The Case of Hubei, China

2018

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Human well-being can be affected by the loss of ecosystem services from conversion of agricultural lands. Uncovering negative ecological consequences of rural-urban conversion is important for regulating rural-urban land conversion. This paper evaluates the impacts of rural-urban land conversion on the ecological well-being of different interest groups in China and makes policy recommendations for mitigating them. This research empirically quantifies and compares changes in the ecological well-being of rural and urban residents due to rural-urban land conversion and examines how transformation factors affect such changes in Hubei, China using the Fuzzy Synthetic Evaluation Model. Results show that compared with urban residents, rural resident ecological well-being level declines more obviously with rural-urban land conversion. Two socio-demographic characteristics, age and education level, as well as zoning characteristics, influence both rural and urban resident well-being changes. It is argued that there is a need for quantitative measurement of agricultural ecosystem services changes and that the construction of ecological compensation policies in areas undergoing rural-urban land conversion is essential for regulating rural-urban land conversion and for maintaining resident ecological well-being.

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Section: Discussionmentioning

confidence: 99%

“…Rural-urban conversion destroys the nutrient recycling capacity of agroecosystem [59][60][61][62]. Therefore, this paper investigates the satisfaction of rural and urban residents with their daily consumption of staple food, vegetables and meat to measure the change in their capability of obtaining enough nutrition.…”

Section: Healthmentioning

confidence: 99%

How does the Ecological Well-Being of Urban and Rural Residents Change with Rural-Urban Land Conversion? The Case of Hubei, China

2018

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“…Regarding the former, some studies concentrate on the direct habitat problem, such as natural habitat loss and degradation [9,12,14,15] while others use an ecological index to indirectly represent habitat loss and degradation, such as the landscape fragment index [15,16] or the habitat pressure index [17]. Recently, ES are increasingly used to reflect urban expansion's influence on ecology [16,[18][19][20]. Those studies select ES types according to their importance and the data collection situation in their study areas.…”

Section: Introductionmentioning

confidence: 99%

Biodiversity constraint indicator establishment and its optimization for urban growth: framework and application

Sun

et al. 2019

Environ. Res. Lett.

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Urbanization causes tremendous pressure on biodiversity and ecosystems at the global scale. China is among the countries undergoing the fastest urban expansion. For a long time, ecological environment protection has not been a priority in China's urban planning process. Current urban growth optimization research has some limitations regarding the selection of more scientific ecological constraint indicators and the interaction between urban expansion and ecological factors. This paper at first aimed to establish a reasonable comprehensive biodiversity constraint indicator based on the indicators of net primary productivity, habitat connectivity and habitat quality, and then conducted a case study in Beijing and compared biodiversity loss and urban growth patterns under different developing situations. The integrated valuation of ecosystem services and trade-offs model and GISrelated methods were used to obtain biodiversity and ecological spatial distribution layers. Then an ecological priority-oriented urban growth simulation method was proposed to search for minimum biodiversity loss. The results showed that the important biodiversity security areas were mostly distributed in the western part of the study area and that the ecological degradation in 2000 had a radial pattern and was well in line with the urban construction and ring road distribution patterns. Meanwhile, biodiversity loss with the biodiversity constraint was much less than actual urban growth in 2000-2010. Under the guidance of ecological optimization, urban growth in the research results reflects decentralized and multi-center spatial development characteristics. This type of urban growth not only provides a new model for breaking the inertia of urban sprawl but also proposes 'biodiversity security' as an applicable regulatory tool for urban planning and space governance reforming.

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“…As mentioned above, rapid urbanization has created a high demand for land resources, and the municipal government is now faced with a land crisis (Grimm et al, ; Peng et al, ). After a period of overexploitation of land, there has been extensive land reclamation from the sea in Shenzhen over the past few decades.…”

Section: Discussionmentioning

confidence: 99%

Monitoring ecosystem service change in the City of Shenzhen by the use of high‐resolution remotely sensed imagery and deep learning

Huang

Han

et al. 2019

Land Degrad Dev

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Information concerning land‐use change is imperative for improving conservation policies that promote sustainable land development. However, to date, most of the previous studies have largely focused on the use of coarse‐ or moderate‐resolution data, with which it may not be possible to identify the land‐use classes in urban environments. Due to the improved spatial details, high‐resolution (HR) remote sensing imagery provides us with an opportunity for the semantic interpretation of urban landscapes. Therefore, in this study, we took the City of Shenzhen (1997 km2) in China as an example to assess the detailed land‐use change and its effect on ecosystem services (ESs), based on HR satellite data from 2005 to 2017. In particular, deep learning was used to obtain accurate land‐use maps, because this technique is able to model the hierarchical representations of features and can thus effectively characterize urban scenes. The results revealed the following findings: (a) The overall accuracy of the proposed approach was 96.9% and 97.1% for 2005 and 2017, respectively, outperforming state‐of‐the‐art semantic classification models; (b) residential and commercial areas in Shenzhen increased dramatically over the study period by 10,416 and 9,168 ha, at the expense of ecological land; (c) supply capacity of the ecosystem decreased by 13.7%, but demand for ESs showed an increase of 23.5%. By courtesy of HR images, detailed land‐use changes and the associated ESs can be monitored, which facilitates the in‐depth understanding of urban environmental systems.

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Ecosystem services response to urbanization in metropolitan areas: Thresholds identification

Cited by 419 publications

References 49 publications

How does the Ecological Well-Being of Urban and Rural Residents Change with Rural-Urban Land Conversion? The Case of Hubei, China

How does the Ecological Well-Being of Urban and Rural Residents Change with Rural-Urban Land Conversion? The Case of Hubei, China

Biodiversity constraint indicator establishment and its optimization for urban growth: framework and application

Monitoring ecosystem service change in the City of Shenzhen by the use of high‐resolution remotely sensed imagery and deep learning

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