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Xiao Ouyang
Hunan Institute of Economic Geography, Hunan University of Finance and Economics, Changsha 410205, China

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Journal article
Published: 03 April 2021 in Ecological Indicators
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Simulation of future land space changes in urban agglomerations is a powerful means to optimize regional spatial structure and improve human well-being. This study highlights the equilibrium between urban development and ecological protection and introduces ecological impact coefficient and land use protection coefficient to measure the degree of sustainable land development. The system dynamic model was used to simulate the dynamics of urban development space, ecological space, and urban agricultural space in the Changsha-Zhuzhou-Xiangtan urban agglomeration from 2019 to 2035. Four development scenarios were used in the simulation, namely, status-quo, economic-centric, environment-centric, and coordinated equilibrium. Simulation results show that for the year 2035, urban development space scale would increase by 678.91 km2 under the status quo, increase by 870.12 km2 under the economic-centric scenario, increase by 740.98 km2 under an environment-centric setting, and increase by 775.54 km2 with coordinated equilibrium. The various scenarios would have significant differences in ecological impact and land use protection coefficients, with the environment-centric scenario yielding the highest values for these indicators. The approach presented in this study shows that the needs for urban development can be achieved while also protecting ecological and urban agricultural spaces and that allocation of production, living, and ecological spaces can be optimized using multi-scenario simulation. The development of ecological impact coefficients and land use protection coefficients, as well as the use of different development scenarios, can be used as reference for the more efficient use of land resources areas and the formulation of land-use and spatial planning.

ACS Style

Jingzhi Li; Xiao Ouyang; Xiang Zhu. Land space simulation of urban agglomerations from the perspective of the symbiosis of urban development and ecological protection: A case study of Changsha-Zhuzhou-Xiangtan urban agglomeration. Ecological Indicators 2021, 126, 107669 .

AMA Style

Jingzhi Li, Xiao Ouyang, Xiang Zhu. Land space simulation of urban agglomerations from the perspective of the symbiosis of urban development and ecological protection: A case study of Changsha-Zhuzhou-Xiangtan urban agglomeration. Ecological Indicators. 2021; 126 ():107669.

Chicago/Turabian Style

Jingzhi Li; Xiao Ouyang; Xiang Zhu. 2021. "Land space simulation of urban agglomerations from the perspective of the symbiosis of urban development and ecological protection: A case study of Changsha-Zhuzhou-Xiangtan urban agglomeration." Ecological Indicators 126, no. : 107669.

Journal article
Published: 22 February 2021 in Energy
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Limited publications were designed to examine the Water-Energy-Carbon (WEC) efficiency of different regions. This study is the first to seek to identify the regional embodied WEC efficiency of China, including 31 of 34 provinces, using the Multiregional Input-Output approach. The provincial embodied WEC coefficients, total amount of embodied WEC, embodied amount of WEC per capita are explored. Results show that: i) Xinjiang (33 Gt/k€), Hebei (34 MJ/€) and Ningxia (5 t/k€) separately dominate the lists of provincial embodied water consumption coefficients, energy consumption coefficients and CO2 emission coefficients; ii) Shandong and Jiangsu consume the most embodied water at 109 Gm3 and 105 Gm3, embodied energy at 21 EJ and 20 EJ, and emit the most CO2 emissions at 2.7 Gt and 2.2 Gt. However, as the more developed province and with higher GDP, Guangdong has lower embodied WEC amount and higher WEC efficiency; ⅲ) The regions that have larger values of embodied WEC per capita, mainly located at the east and north-west of China, including Beijing, Tianjin, Shandong, Jiangsu, Zhejiang, Inner Mongolia and Xinjiang. This study targets the contribution to understanding the regional WEC efficiency performance, highlighting the spots and economies that deserve the uppermost attention for emissions reduction.

ACS Style

Xue-Chao Wang; Jiří Jaromír Klemeš; Xiao Ouyang; Zihan Xu; Weiguo Fan; Hejie Wei; Weize Song. Regional embodied Water-Energy-Carbon efficiency of China. Energy 2021, 224, 120159 .

AMA Style

Xue-Chao Wang, Jiří Jaromír Klemeš, Xiao Ouyang, Zihan Xu, Weiguo Fan, Hejie Wei, Weize Song. Regional embodied Water-Energy-Carbon efficiency of China. Energy. 2021; 224 ():120159.

Chicago/Turabian Style

Xue-Chao Wang; Jiří Jaromír Klemeš; Xiao Ouyang; Zihan Xu; Weiguo Fan; Hejie Wei; Weize Song. 2021. "Regional embodied Water-Energy-Carbon efficiency of China." Energy 224, no. : 120159.

Journal article
Published: 17 February 2021 in International Journal of Environmental Research and Public Health
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Spatio-temporal epidemic simulation, assessment, and risk monitoring serve as the core to establishing and improving the national public health emergency management system. In this study, we investigated Oncomelania hupensis breeding grounds and analyzed the locational and environmental preferences of snail breeding in Dongting Lake (DTL), Hunan, China. Using geographic information systems and remote sensing technology, we identified schistosomiasis risk areas and explored the factors affecting the occurrence and transmission of the disease. Several key conclusions were drawn. (1) From 2006 to 2016, the spatial change of potential O. hupensis breeding risk showed a diminishing trend from the eastern and northern regions to southwest DTL. Environmental changes in the eastern DTL region resulted in the lakeside and hydrophilic agglomerations of the O. hupensis populations. The shift in snail breeding grounds from a fragmented to centralized distribution indicates the weakening mobility of the O. hupensis population, the increasing independence of solitary groups, and the growing dependence of the snail population to the local environment. (2) The spatial risk distribution showed a descending gradient from west Dongting area to the east and an overall pattern of high in the periphery of large lakes and low in other areas. The cold-spot areas had their cores in Huarong County and Anxiang County and were scattered throughout the peripheral areas. The hot-spot areas had their center at Jinshi City, Nanxian County, and the southern part of Huarong County. The areas with increased comprehensive risks changed from centralized and large-scale development to fragmented shrinkage with increased partialization in the core area. The risk distribution’s center shifted to the northwest. The spatial risk distribution exhibited enhanced concentricity along the major axis and increased dispersion along the minor axis.

ACS Style

Jun Xu; Xiao Ouyang; Qingyun He; Guoen Wei. Comprehensive Risk Assessment of Schistosomiasis Epidemic Based on Precise Identification of Oncomelania hupensis Breeding Grounds—A Case Study of Dongting Lake Area. International Journal of Environmental Research and Public Health 2021, 18, 1950 .

AMA Style

Jun Xu, Xiao Ouyang, Qingyun He, Guoen Wei. Comprehensive Risk Assessment of Schistosomiasis Epidemic Based on Precise Identification of Oncomelania hupensis Breeding Grounds—A Case Study of Dongting Lake Area. International Journal of Environmental Research and Public Health. 2021; 18 (4):1950.

Chicago/Turabian Style

Jun Xu; Xiao Ouyang; Qingyun He; Guoen Wei. 2021. "Comprehensive Risk Assessment of Schistosomiasis Epidemic Based on Precise Identification of Oncomelania hupensis Breeding Grounds—A Case Study of Dongting Lake Area." International Journal of Environmental Research and Public Health 18, no. 4: 1950.

Journal article
Published: 06 January 2020 in Sustainability
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In order to analyze the coordination relationship between investment potential and economic development and its driving mechanisms, this study integrated the entropy weight method, coupling coordination degree model, exploratory spatial data analysis, geographic detector, and geographically weighted regression model. The developed approach was applied using data from 51 African countries from 2008 to 2016. The results showed that: (1) While the level of economic development in the African continent has increased steadily, the overall investment potential needs to be improved. The mean economic development index rose from 0.116 to 0.151, but the economic gap among countries was still highly evident. (2) Uncoordinated development and barely coordinated development level were the dominant types of relationship between investment potential and economic development in African countries. The spatial distribution showed significant agglomeration characteristics; the sub-hot spot and sub-cold point regions maintained strong dependence with their hot spot and cold point counterparts. The hot spot areas gradually formed an agglomeration in Southern Africa and highly fragmented distribution in other areas. The cold spot areas formed a spatial distribution pattern of “one core and one belt” with some countries in Western Africa forming the core, while some Central and East African countries constituting the belt. (3) The coordination relationship between investment potential and economic development was influenced mainly by factors including economic base, residents’ living standard, industrial construction level, information support level, and business friendliness. Using geographically weighted regression coefficient distribution of indicators, the driving mechanisms of spatial distribution could be divided into five types: economic base driven, industry-driven, information application-driven, business convenience-driven, and consumer market-driven.

ACS Style

Guoen Wei; Pingjun Sun; Zhenke Zhang; Xiao Ouyang. The Coordinated Relationship between Investment Potential and Economic Development and Its Driving Mechanism: A Case Study of the African Region. Sustainability 2020, 12, 442 .

AMA Style

Guoen Wei, Pingjun Sun, Zhenke Zhang, Xiao Ouyang. The Coordinated Relationship between Investment Potential and Economic Development and Its Driving Mechanism: A Case Study of the African Region. Sustainability. 2020; 12 (1):442.

Chicago/Turabian Style

Guoen Wei; Pingjun Sun; Zhenke Zhang; Xiao Ouyang. 2020. "The Coordinated Relationship between Investment Potential and Economic Development and Its Driving Mechanism: A Case Study of the African Region." Sustainability 12, no. 1: 442.

Journal article
Published: 14 November 2019 in Sustainability
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Coordinating ecosystem service supply and demand equilibrium and utilizing machine learning to dynamically construct an ecological security pattern (ESP) can help better understand the impact of urban development on ecological processes, which can be used as a theoretical reference in coupling economic growth and environmental protection. Here, the ESP of the Changsha–Zhuzhou–Xiangtan urban agglomeration was constructed, which made use of the Bayesian network model to dynamically identify the ecological sources. The ecological corridor and ecological strategy points were identified using the minimum cumulative resistance model and circuit theory. The ESP was constructed by combining seven ecological sources, “two horizontal and three vertical” ecological corridors, and 37 ecological strategy points. Our results found spatial decoupling between the supply and demand of ecosystem services (ES) and the degradation in areas with high demand for ES. The ecological sources and ecological corridors of the urban agglomeration were mainly situated in forestlands and water areas. The terrestrial ecological corridor was distributed along the outer periphery of the urban agglomeration, while the aquatic ecological corridor ran from north to south throughout the entire region. The ecological strategic points were mainly concentrated along the boundaries of the built-up area and the intersection between construction land and ecological land. Finally, the ecological sources were found primarily on existing ecological protection zones, which supports the usefulness of machine learning in predicting ecological sources and may provide new insights in developing urban ESP.

ACS Style

Xiao Ouyang; Zhenbo Wang; Xiang Zhu. Construction of the Ecological Security Pattern of Urban Agglomeration under the Framework of Supply and Demand of Ecosystem Services Using Bayesian Network Machine Learning: Case Study of the Changsha–Zhuzhou–Xiangtan Urban Agglomeration, China. Sustainability 2019, 11, 6416 .

AMA Style

Xiao Ouyang, Zhenbo Wang, Xiang Zhu. Construction of the Ecological Security Pattern of Urban Agglomeration under the Framework of Supply and Demand of Ecosystem Services Using Bayesian Network Machine Learning: Case Study of the Changsha–Zhuzhou–Xiangtan Urban Agglomeration, China. Sustainability. 2019; 11 (22):6416.

Chicago/Turabian Style

Xiao Ouyang; Zhenbo Wang; Xiang Zhu. 2019. "Construction of the Ecological Security Pattern of Urban Agglomeration under the Framework of Supply and Demand of Ecosystem Services Using Bayesian Network Machine Learning: Case Study of the Changsha–Zhuzhou–Xiangtan Urban Agglomeration, China." Sustainability 11, no. 22: 6416.