Abstract:Rapid urbanization and human activities enhanced threats to the degradation of various ecosystem services in modern urban agglomerations. This study explored the response of ecosystem service values (ESVs) to land use changes and the trade-offs among various ESVs in urban agglomerations under different future development scenarios. The patch-general land use simulation (PLUS) model and ESV calculation method were used to simulate the ESVs of Guanzhong Plain Urban Agglomeration under the Business As Usual scena… Show more
“…Spatial auto-correlation is an important indicator to test the correlated significance of the attribute value of an index with the attribute value of its adjacent space [78]. The Global Moran's index reflects the correlation of attribute values of adjacent spatial units of the whole area.…”
In the context of rapid urbanization and limited land amount, it is essential to scientifically evaluate the urban land green use efficiency (ULGUE) to promote regional sustainable development. Current studies are of great value for enriching the theoretical system and application research of ULGUE. Still, most of them only consider industrial pollution but ignore carbon emission as an essential environmental influencing indicator. This paper introduced carbon emissions into the input-output indicator system, measured ULGUE of 57 cities in the Yellow River Basin (YRB) over the 2004–2017 periods using the super-efficiency slacked-based measure (Super-SBM) model, analyzed its spatio-temporal patterns with the kernel density estimation (KDE) model and spatial autocorrelation model, and then identified the influencing factors with the Spatial Durbin model (SDM). As shown by the results, firstly, the ULGUE in the YRB over the 2004–2017 periods showed a trend of first decreasing and then increasing. Secondly, the ULGUE exhibited spatio-temporal imbalance characteristics across the YRB. Thirdly, ULGUE was the interaction of multiple indicators, and its influencing factors had spatial spillover effects. All in all, this paper is fundamental to the high-quality development of cities in the background of the Chinese policy of “carbon peak, carbon neutralization”.
“…Spatial auto-correlation is an important indicator to test the correlated significance of the attribute value of an index with the attribute value of its adjacent space [78]. The Global Moran's index reflects the correlation of attribute values of adjacent spatial units of the whole area.…”
In the context of rapid urbanization and limited land amount, it is essential to scientifically evaluate the urban land green use efficiency (ULGUE) to promote regional sustainable development. Current studies are of great value for enriching the theoretical system and application research of ULGUE. Still, most of them only consider industrial pollution but ignore carbon emission as an essential environmental influencing indicator. This paper introduced carbon emissions into the input-output indicator system, measured ULGUE of 57 cities in the Yellow River Basin (YRB) over the 2004–2017 periods using the super-efficiency slacked-based measure (Super-SBM) model, analyzed its spatio-temporal patterns with the kernel density estimation (KDE) model and spatial autocorrelation model, and then identified the influencing factors with the Spatial Durbin model (SDM). As shown by the results, firstly, the ULGUE in the YRB over the 2004–2017 periods showed a trend of first decreasing and then increasing. Secondly, the ULGUE exhibited spatio-temporal imbalance characteristics across the YRB. Thirdly, ULGUE was the interaction of multiple indicators, and its influencing factors had spatial spillover effects. All in all, this paper is fundamental to the high-quality development of cities in the background of the Chinese policy of “carbon peak, carbon neutralization”.
“…The implementation of the national food security strategy and targeted poverty alleviation strategy proposed at the 2013 Central Rural Work Conference has greatly increased humans' income and improved farmland protection. In addition, Yang Ke et al found that although the annual average PM2.5 concentration in the Guanzhong Plain urban agglomeration showed an overall downward trend from 2015 to 2019, it still exceeded China's air quality Level II (35 µg/m 3 ) [43]. Therefore, human well-being recovered from 2015 to 2018 but did not reach its initial level.…”
Understanding the complex relationship between ecosystem services and human well-being during the rapid development of urban agglomerations can promote the sustainable development of urban agglomerations. In this paper, the InVEST model and ArcGIS10.2 were used to analyze the spatial and temporal evolution characteristics of ecosystem services and human well-being in the Guanzhong Plain urban agglomeration. On this basis, the coupling coordination index is used to reveal the spatiotemporal coupling relationship between them. (1) From 2010 to 2018, the water conservation services, soil conservation services, and carbon sequestration services of the Guanzhong Plain urban agglomeration showed a fluctuating downward trend. The spatial differences of ecosystem services were significant. (2) From 2010 to 2018, human well-being in the Guanzhong Plain urban agglomeration showed a fluctuating downward trend, with a decrease of 17%, and regional differences tended to narrow. (3) The coupling coordination degree between ecosystem services and human well-being has slightly decreased while maintaining the basic coordination state. The results show that there was a significant relationship between the decline of ecosystem services and the rapid development of the Guanzhong Plain urban agglomeration, and policies should be classified according to the coupling coordination types of human well-being and ecosystem services to promote the sustainable development of urban agglomerations.
“…In this study, the patch-level land use simulation model (PLUS) of the integrated development type was used to simulate urban land expansion. Compared with other urban land expansion simulation models, the PLUS model integrates a CA based on multi-type random patch seeds (CARS), the land expansion rule mining framework (LEAS), and a multi-type stochastic seed mechanism, which obtain more accurate patch-level land use type simulation results, especially for natural land use types, such as woodland and grassland [16,35]. The spatiotemporal dynamic evolution characteristics of land use, ESVs, and the coupling relationship between them were quantified.…”
Section: Data Source and Processingmentioning
confidence: 99%
“…In recent years, scholars have achieved a series of productive results in the study of ES and LULC [15]. At the research scale, the relationship between land use and ES in watersheds, coastal wetlands, water-bearing lands, and urbanized areas has been explored [16,17]. In terms of research Land 2022, 11,1934 3 of 23 content, ES is used as a basis for constructing ecological resistance surfaces, ecological safety patterns, and ecological health patterns and for predicting urban land expansion processes.…”
Balancing urban development and ecosystem conservation in the context of natural resource scarcity can provide scientific guidance for land use planning. We integrated research methods, such as ecosystem services (ES) assessment, coastal vulnerability assessment, multi-objective linear planning, and land use change simulation, to develop a new model framework for multi-scenario urban land expansion simulation based on ecosystem services. In relation to the land use scale and constraints, we simulated three types of scenarios in 2035, including a status quo continuity scenario (SCS), economic development scenario (EDS), and ecological protection scenario (EPS), to explore the ideal land use optimization strategies to enhance ES and land use efficiency. The results indicated that the scale of construction land under the three scenarios grew, and arable land and grassland had the largest losses. The continued urban expansion in the Guangdong–Hong Kong–Macao Greater Bay Area has already had a significant negative impact on ecosystem services and could result in a total ESV loss of USD 28.1 billion by 2035 if an economic-first development model is adopted. Based on the hotspots of urban construction land expansion in the ecological–economic priority game, we proposed a classification and optimization strategy for land use, including proactive restoration of damaged ecological spaces with high ESVs (Zhaoqing City and Huizhou City), optimization of green space quality and formation of ecological corridors (Guangzhou City, Shenzhen City, Hong Kong, and Macao), and implementation of natural resource conservation planning and spatial regulation in the urban–rural integration area (Foshan City and Dongguan City). This research framework scientifically allocates the “quality” of ecosystem values and “quantity” of natural resources and provides a reference for regional “bottom-up” territorial spatial planning.
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