Ecosystem services response to rural-urban transitions in coastal and island cities: A comparison between Shenzhen and Hong Kong, China

Xu, Chao; Wei-yu, Jiang; Huang, Qianyuan; Wang, Yutao

doi:10.1016/j.jclepro.2020.121033

Cited by 50 publications

(24 citation statements)

References 48 publications

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“…Many scholars have paid attention to the ESs in different urban space divisions. For example, the research results of Xu et al (2020) and Hou et al (2020) were similar to our study, which showed that ESs gradually decreased from urban centers to rural areas. However, few scholars have studied the relationship between ESs and urbanization in different urban space divisions, and most of them have analyzed the relationship between ESs and urbanization on the city scale.…”

Section: The Relationship Between Ess and Urbanizationsupporting

confidence: 86%

“…Along with urbanization, cities will gradually spread to the rural-urban fringe, even rural areas, which will affect ESs in these areas. For two regions with the same degree of urbanization, the effect of natural environment on the carrying capacity for urbanization may be different (Dietz and Rosa, 1994), leading to the unbalanced spatial distribution of ESs (Xu et al, 2020). Thus, the impact of urbanization on ESs in urban area differed from that in rural area.…”

Section: Introductionmentioning

confidence: 99%

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What’s the relationship between urbanization and ecosystem services from urban to rural area

Wu¹,

He²,

Zhao³

2021

Preprint

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Ecosystem services (ESs) are closely bound up with human welfare. To propose regional exploitive tactics for the harmonious relationship between urbanization and ecological environment, it is essential to sort out the relationship between urbanization and ESs, and to untangle the urban-rural differences of the ecological environment effects. Regarding Beijing as an example, this study firstly explored the spatiotemporal characteristics of the ESs and the urbanization. Secondly, this study applied the latest methods based on nighttime light and K-means algorithm to identify the urban area, urban-rural fringe and rural area in Beijing. Then we explored the spatiotemporal interaction characteristics of urbanization on ESs through decoupling analysis. Finally, the correlation analysis and curve fitting were used to quantify the correlation between urbanization and ESs in urban scale and regional scale. The main conclusions included: (1) ESs declined with the increase of urbanization; (2) In cities or regions, coordinated development was the main trend of ESs and urbanization; (3) The relationship between changes in ESs and changes in urbanization has regional differences.

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Section: The Relationship Between Ess and Urbanizationsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

What’s the relationship between urbanization and ecosystem services from urban to rural area

Wu¹,

He²,

Zhao³

2021

Preprint

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“…Past studies in modeling surface ecological conditions have focused on modeling the impact of human activity, including population growth and urban physical expansion, on the spatiotemporal changes in surface ecological conditions [14,15,26]. Hence, variations in the surface ecological conditions of an area can be caused by natural and unnatural factors [7][8][9][10].…”

Section: Discussionmentioning

confidence: 99%

“…Wetlands and cities are the natural and artificial ecological areas that have the greatest effect on ecosystem conditions. Therefore, modeling the spatiotemporal variation of surface ecological conditions in these areas is of great importance [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

A Remotely Sensed Assessment of Surface Ecological Change over the Gomishan Wetland, Iran

et al. 2020

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Due to the excessive use of natural resources in the contemporary world, the importance of ecological and environmental condition modeling has increased. Wetlands and cities represent the natural and artificial strategic areas that affect ecosystem conditions. Changes in the ecological conditions of these areas have a great impact on the conditions of the global ecosystem. Therefore, modeling spatiotemporal variations of the ecological conditions in these areas is critical. This study was aimed at comparing degrees of variation among surface ecological conditions due to natural and unnatural factors. Consequently, the surface ecological conditions of Gomishan city and Gomishan wetland in Iran were modeled for a period of 30 years, and the spatiotemporal variations were evaluated and compared with each other. To this end, 20 Landsat 5, 7, and 8, and 432 Moderate Resolution Imaging Spectroradiometer (MODIS), monthly land surface temperature (LST) (MOD11C3) and normalized difference vegetation index (NDVI) (MOD13C3) products were utilized. The surface ecological conditions were modeled according to the Remote Sensing-based Ecological Index (RSEI), and the spatiotemporal variation of the RSEI values in the study area (Gomishan city, Gomishan wetland) were evaluated and compared with each other. According to MODIS products, the mean of the LST and NDVI variance values for the study area (Gomishan city, Gomishan wetland) were obtained to be 6.5 °C (2.1, 12.1) and 0.009 (0.005, 0.013), respectively. The highest LST and NDVI temporal variations were found for Gomishan wetland near the Caspian Sea. According to Landsat images, Gomishan wetland and Gomishan city have the highest and lowest temporal variations in surface biophysical characteristics, respectively. The mean RSEI for the study area (Gomishan city, Gomishan wetland) was 0.43 (0.65, 0.29), respectively. Additionally, the mean Coefficient of Variation (CV) of RSEI for the study area (Gomishan city, Gomishan wetland) was 0.10 (0.88, 0.51), respectively. The surface ecological conditions of Gomishan city were worse than those of the Gomishan wetland at all dates. Temporal variations in the surface ecological conditions of Gomishan wetland were greater than those of the study area and Gomishan city. These results can provide useful and effective information for environmental planning and decision-making to improve ecological conditions, protect the environment, and support sustainable ecosystem development.

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“…In this context, urban forests were considered to play a crucial role in coping with various environmental challenges, such as improving air quality, fixing carbon, mitigating environmental degradation, and providing other ecosystem services (Alonzo et al, 2016;Steenberg et al, 2017), which had been widely researched (Dobbs et al, 2011;Escobedo et al, 2011). For example, Nowak et al (2013) quantified the carbon sequestration of urban forests in USA to assess their magnitude and role concerning climate change and Xu et al (2020) investigated the ecosystem services changes of urban forests caused by urban expansion in Shenzhen and Hong Kong, China. At urban-tree scale, Rahman et al (2015) compared and quantified the growth and cooling effectiveness of five common urban tree species in Germany and Zhang et al (2019) studied how the frequently-planted tree species in Munich coped with drought stress in terms of below-ground process.…”

Section: Introductionmentioning

confidence: 99%

Ecological and Landscape Perspectives on Urban Forest Planning and Construction: A Case Study in Guangdong-HongKong-Macao Greater Bay Area of China

Zhao

Qian

et al. 2020

Front. Sustain. Cities

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Urban forest plays a crucial role in coping with global change and rapid urbanization via providing various ecosystem services. In this context, cities in Guangdong-Hongkong-Macao Greater Bay Area of China (GBA) established increasing investment in urban forest construction since 2000. However, data on the current condition of the planted forests remains scarce, which hampers a comprehensive understanding of how to improve the quality of urban forest planning and construction in the future. Therefore, we selected a core city Guangzhou, an inland city Foshan and a coastal city Zhuhai in GBA as our research objects and classified them into core urban area (CUA), semi urban area (SUA), and urban fringe area (UFA). We launched a field measurement for the tree variables regarding forest structure. Besides, ecological indexes were introduced to evaluate the condition and potential of the forests and florescence data together with tridimensional green quantity data provided different perspectives on landscape diversity and stability. The results show that Guangzhou has a well-planned forest pattern with advantages in forest structures and visible landscape values in different areas. To introduce different tree species in CUA and SUA and to plant more trees of those rare tree species in UFA can effectively increase Guangzhou's forest diversity and evenness. For Foshan, it is advisable to implement a balanced forest-investment policy by making specific recommendations for different areas, such as planting various tree species in CUA and UFA to increase forest diversity. For Zhuhai, it is distinguished for the attractiveness for tourists by the advantages in landscape diversity and stability, but it is still necessary to plant different trees with appropriate classes to enhance the urban forest stability. Overall, it is crucial for city managers to obtain precise knowledge of urban forest conditions from both the ecological and landscape perspectives, which may contribute enormously to the improvement of the quality of urban forest planning and construction in adapting to various environmental challenges.

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Ecosystem services response to rural-urban transitions in coastal and island cities: A comparison between Shenzhen and Hong Kong, China

Cited by 50 publications

References 48 publications

What’s the relationship between urbanization and ecosystem services from urban to rural area

What’s the relationship between urbanization and ecosystem services from urban to rural area

A Remotely Sensed Assessment of Surface Ecological Change over the Gomishan Wetland, Iran

Ecological and Landscape Perspectives on Urban Forest Planning and Construction: A Case Study in Guangdong-HongKong-Macao Greater Bay Area of China

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