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Article

A Study on the Spatiotemporal Characteristics of the Xi’an Metropolitan Area Based on the Coupling and Coordination of Ecosystem Services and Human Well-Being

by
Yunsong Gao
,
Pei Zhang
*,
Yuqian Xu
,
Zhijun Li
and
Kaixi Liu
School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, China
*
Author to whom correspondence should be addressed.
Land 2025, 14(3), 500; https://doi.org/10.3390/land14030500
Submission received: 15 January 2025 / Revised: 20 February 2025 / Accepted: 24 February 2025 / Published: 28 February 2025
(This article belongs to the Special Issue Synergies in Land Use Planning: Advancing Urban-Rural Integration for Sustainable Development)
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Abstract

:
The escalating conflict between ecosystem degradation and the rising demands of humanity has rendered the attainment of a scientific balance between ecosystem services and human well-being a critical concern in research on human–environment coupling and sustainable development. Metropolitan areas are pivotal in long-term sustainable development strategies and regional equity due to rapid urbanization and the tension between ecosystem degradation and human well-being. This study proposes a novel perspective, transitioning from a “cascade” to a “coupling” approach in examining the relationship between ecosystem services and human well-being. Taking the Xi’an metropolitan area as the research subject, the research employs a coupling coordination degree model to analyze the spatiotemporal characteristics of their relationship across multiple scales. The key findings of the paper are as follows: (1) We found a severe shrinkage in the ecosystem service value (2000–2020). The ecosystem services in the Xi’an metropolitan area were significantly compromised under the pressure of homogenized human well-being improvement, resulting in weak coupling and coordination between the two. (2) There was a spatial imbalance between supply and demand. Ecosystem service values displayed a core-to-periphery increasing spatial pattern, while human well-being levels exhibited a core-to-periphery decreasing distribution, indicating a marked spatial mismatch. (3) Diverse coupling dynamics within the region were identified. Driven by factors such as the resource distribution, land use, scale effects, and benefit allocation, the coupling relationships between ecosystem services and human well-being varied across development stages and contexts. Ecosystem services functioned as either flexible facilitators or constraints on human well-being improvement. This research provides a blueprint for sustainable development, offering a framework to balance urban growth with ecological health while ensuring equitable well-being across the Xi’an metropolitan area. The study highlights the need for strict ecological space protection, enhanced urban development quality, and integrated human–environment system management. Efforts should focus on minimizing land use trade-offs and spatial competition, strengthening spatial synergy in supply–demand coupling, and promoting sustainable regional development.

1. Introduction

The natural environment provides diverse contributions, such as opportunities for recreation, spiritual fulfillment, and esthetic experiences, which have a substantial impact on human well-being across different scales [1]. Academics have consistently stressed the significance of elucidating the intricate trade-offs between humans and nature and revealing the ways in which elements of the natural environment intersect with human well-being [2]. Understanding the process and logic by which the service provision of the natural environment is connected to human well-being and devising appropriate interventions to enhance the level of human well-being and mitigate the negative impacts of human activities on the natural environment are essential for sustainable ecosystem management [3,4]. A substantial amount of research has been developed, employing diverse perspectives and approaches in an attempt to shed light on human–nature interactions. Ecosystem services, serving as a crucial bridge between ecosystems and socio-economic systems [5,6], are the benefits that humans derive directly or indirectly from ecosystems and are integrally related to HWB as a whole [7]. They offer one of the most popular perspectives for exploring human–nature relationships [8].
Rapid urbanization and an unprecedented development intensity have led to the emergence of ecosystem services as a core concept in sustainability science, along with human well-being [9]. The expansion of urban built-up land has led to a growing trend of shrinkage and fragmentation of natural ecosystems [10], accompanied by widespread spatial distribution imbalances and inequities in group sharing [11,12]. This has left residents with insufficiently met physical, recreational, health, and well-being needs and has significantly increased the demand for ecosystem services. Ecosystem services include provisioning, regulating, supporting, and cultural services [13] and are essential for improving the diverse needs of high-density urban living, such as space quality, public green space recreation, environmental quality, and emotional well-being. Different types and scales of ecosystem services vary, and there are trade-offs in the service provision as ecosystem services increase or decrease [14], leading to imbalances or inequities in distribution [15,16]. To alleviate the growing scarcity of ecosystem services and support ecosystem management and the implementation of ecological policies, it has become essential to comprehensively assess the value of ecosystem services [17]. Consequently, there has been a surge in research dedicated to evaluating and quantifying ecosystem services [18]. The value of ecosystem services represents a monetary form of ecosystem service [19] and is widely employed to measure the well-being that ecosystems confer upon humans [20,21]. Disturbances in land use patterns by high-intensity human activities directly affect changes in ecosystem patterns and functions and are important drivers of changes in ecosystem service values. The current research on the value of ecosystem services has moved beyond the traditional focus on economic output to emphasize the integrated enhancement of human well-being. This includes the contribution of ecosystem service values to human well-being [22], the feedback from human well-being to ecosystems [23,24], and interactions between ecosystem services and human well-being [25,26].
In ES and HWB research, the cascade framework simplifies their relationship into a linear process, while the coupling framework emphasizes reciprocal interactions, feedback mechanisms, and multi-scale dynamics within socio-ecological systems. This transition from “cascade” to “coupling” represents a shift from linear to systems thinking, contributing to sustainable development. However, studies directly examining service–well-being interactions and coupling metrics are limited, and the spatiotemporal linkages between ESV changes and HWB remain poorly understood. Although research has advanced from theoretical exploration to regional applications, methodological gaps in assessing coupling relationships persist. Most studies are qualitative, lack a spatial heterogeneity analysis, and focus on national or watershed scales, neglecting county-level quantitative investigations. The coupling coordination degree model (CCDM) is a key tool for analyzing dynamic changes, integrating temporal and spatial heterogeneity with robust multi-scale performance, making it ideal for in-depth research, long-term management, and comprehensive decision-making support.
Urbanized areas are characterized by rapid economic and social transformation, as well as a significant conflict between ecosystem degradation and human well-being. This has given rise to an increase in human–land conflicts, which are especially severe in such regions. In China, the metropolitan area constitutes a crucial region for population concentration, economic development, and urban expansion [27]. It is also a model area for improving people’s livelihoods through new people-centered urbanization, which is becoming increasingly pivotal in strategizing for long-term sustainability. In light of the aforementioned research and the actual regional development, this study posits that the spatial mismatch between ESs and HWB manifests more prominently in urban cores than peripheral areas, inducing systemic coupling coordination imbalances. Accordingly, this paper adopts the coupling relationship between ecosystem services and human well-being as a starting point, takes the Xi’an metropolitan area—a typical region experiencing rapid urbanization—as a case study, and employs the CCDM to analyze the spatial pattern of the coupling between ESs and HWB from both an overall perspective and county-level perspective.
The key issue in this paper is to deal with the growing conflict between ecological degradation and the rising demands of human development. This relationship examines how ecosystem services, which are the benefits that humans obtain from natural ecosystems, interact with human well-being, including aspects such as health, economic prosperity, and social stability. The main challenges are as follows: (1) Balancing Supply and Demand—Ecosystem services may not fulfill the growing or changing requirements of human populations, resulting in spatial and temporal mismatches. (2) Mitigating Degradation—Ecosystem degradation diminishes the service capacity, thereby constraining well-being, especially for vulnerable communities that depend on natural resources. (3) Spatial and Temporal Dynamics—The relationship is dynamic; it varies across regions and evolves over time, requiring flexible and adaptive management strategies. (4) Integrated Management—Effective coupling requires integrated planning methods that take into account ecological conservation, land use, and socio-economic development simultaneously. The study of this coupling aims to identify sustainable paths that reconcile ecological health with human development needs, promoting long-term resilience and equitable resource distribution.
The Xi’an metropolitan area represents the core of the Guanzhong Plain urban agglomeration, which is one of the most developed regions in western China in terms of economic and population growth. It provides a framework for the implementation of the New Urbanization Model and the optimization of the regional economic structure. The existing research on the value of ecosystem services in the Xi’an metropolitan area mainly focuses on the city of Xi’an as the research subject. Most studies examine the relationship between land use, landscape patterns, and ecosystem services. Nevertheless, there is a lack of research investigating the correlation between human well-being and ecosystem services. In this regard, research on measuring the coupling relationship between the evolution of ecosystem service values and human well-being in the Xi’an metropolitan area is of great importance for enhancing the quality of life of the regional population and prompting sustainable development. In consideration of the above factors, this study employs a data set from 2000 to 2020 for the Xi’an metropolitan area and applies an ecosystem service value assessment method to clarify the characteristics of the evolution of ecosystem service values. Moreover, a model for evaluating human well-being is developed, and the coupling coordination degree model is employed to measure the coupling and coordination relationship between ecosystem services and human well-being. This study then explores the underlying mechanism that drives the coupling relationship between ecosystem service values and human well-being. The aim is to provide a scientific basis for achieving harmonious coexistence between humans and nature in the new era. In addition, the results will offer a scientific basis and decision-making reference for realizing the sustainable development of cities and towns in a new era of harmony between humans and nature.

2. Materials and Methods

2.1. Study Area

The Xi’an metropolitan area is a region centered around the central city of Xi’an, with numerous towns and cities distributed along the national highway. It encompasses the entire Xi’an City, Xianyang City, Weinan City, and Tongchuan City, along with selected districts and counties within the Yangling Agricultural Hi-Tech Industrial Demonstration Zone. The region’s total land area is approximately 20,600,000 km2, accounting for about 10% of the total area of Shaanxi Province. By the end of 2020, the region had a permanent resident population of 18.02 million and a gross domestic product (GDP) of CNY 1.3 trillion. The land use structure of the Xi’an metropolitan area is composed of arable land (49.07%), forest land (20.90%), grassland (17.07%), waters (1.43%), building land (11.43%), and unused land (0.11%) (Figure 1). The Xi’an metropolitan area is endowed with a plethora of ecological resources, including the Qinling Mountains, the northern Guanzhong Mountains, the Weibei Plateau, and other mountainous regions, and is crisscrossed by a network of rivers. The region has a predominantly temperate monsoon climate, with four distinct seasons of warm, cold, dry, and wet, and a high level of precipitation, concentrated in the summer. The rapid expansion of the Xi’an metropolitan area, driven by high-speed development, has led to a dramatic increase in construction land and a rapid concentration of the population. This has resulted in significant challenges, including the fragmentation and shrinkage of ecological land, as well as substantial disruptions to ecosystem function and structure. The resulting contradiction between people and land has become increasingly prominent.

2.2. Research Framework

This study employs a structured approach, comprising three principal stages (Figure 2). Firstly, the study combines relevant data to determine the value of ecosystem service functions. Secondly, the value of ecosystem services from 2000 to 2020 in the Xi’an metropolitan area is evaluated. The Xi’an metropolitan area underwent a phase of rapid urbanization between 2000 and 2020, marked by population surges that exacerbated human–land system tensions. Thirdly, the characteristics of the evolution of the value of ecosystem services in the Xi’an metropolitan area are analyzed in terms of temporal and spatial dimensions. Then, the study constructs a comprehensive evaluation index system for human well-being in the Xi’an metropolitan area and measures the level of human well-being at the district and county scales within the area. Finally, the coupled CCDM is used to examine the coupled coordination relationship between the value of ecosystem services and human well-being in the Xi’an metropolitan area.

2.3. Data Resource

This study data used land use data with a spatial resolution of 30 m from 2000 to 2020, which were obtained from the Resource and Environmental Science Data Platform (http://www.resdc.cn, accessed on 6 June 2024). Referring to the Classification of Current Land Use classification (GB/T 21010-2017) [28], the land use was reclassified into six primary land classes, arable land, forest land, grassland, watersheds, construction land, and unused land, based on the land resources of the Xi’an metropolitan area and their utilization attributes. The administrative division data were obtained from the National Geomatics Center of China (https://www.ngcc.cn, accessed on 6 June 2024). Grain production data were obtained from China Statistical Yearbook, Xi’an City Statistical Yearbook, Xianyang City Statistical Yearbook, Weinan City Statistical Yearbook, and Tongchuan City Statistical Yearbook.

2.3.1. Calculation of Value of Ecosystem Services

The value of ecosystem services refers to the products that are directly or indirectly derived from ecosystem functions. Costanza [29] assessed the value of ecosystem services globally using the Equivalence Factor Approach. This method has low data requirements and accounting processes, and is commonly used to assess ecosystem services at national, regional, provincial, or watershed scales [30,31,32,33], especially to assess spatial and temporal changes in ecosystem service values due to land use changes [34]. Chinese scholars introduced this method to improve and establish an equivalence table of ecosystem service values per unit area of Chinese ecosystems and then developed spatiotemporal dynamic assessment techniques [35,36]. In this study, based on the study of Xie Gaodi [30] and referring to recent related studies [37], the ESV was modified by farmland yield and vegetation cover. The equivalent value of the ecosystem service function in Xi’an metropolitan area was obtained (Table 1), and the ecosystem service value of Xi’an metropolitan area was calculated by applying the equivalent factor method using panel data.
E S V = ∑ k = 1 6 A k × C k       k = 1,2 , … , 6
where ESV represents the ecosystem service value, Ak represents the area of land in category k, and Ck represents the coefficient of ecosystem service value per unit area of land in category k after adjustment. Table 1 lists the specific calculation equivalents of the adjusted ecosystem service value in the Xi’an metropolitan area.

2.3.2. Human Well-Being Measurement Models

Human well-being mostly refers to health, happiness, prosperity, and a good state of life, which are valued capabilities and states achieved on the basis of a good life [38]. Human well-being consists of three dimensions, economic, environmental, and social, with both subjective and objective attributes [39]. In this study, based on the principle of the multi-level needs of human beings, combined with relevant research findings and the actual development of Xi’an metropolitan area, a comprehensive indicator system of human well-being in Xi’an metropolitan area was constructed, with a total of 12 indicators in two dimensions (Table 2). Safety well-being serves as a foundational pillar, reflecting disparities in regional development levels, while health well-being focuses on the enhancement of service provision, emphasizing the quality of development. The selection of indicators prioritizes their relevance to urban development and social services, with all data being sourced from publicly available statistical yearbooks to ensure transparency and reliability. Considering that the entropy value method is an objective method to determine the weight of each indicator based on the information entropy of the data, the entropy value method was adopted to assign weights to each indicator, and the human well-being index was calculated through the method of summing up the assignments to characterize the level of human well-being in the local area. Given the heterogeneity in regional development foundations and objectives, the application of the entropy weight method for assigning indicator weights mitigated the disproportionate influence of single indicators on the overall assessment of HWB. Simultaneously, the derived weights reflected the relative importance of distinct indicators in shaping HWB levels, thereby providing targeted guidance for enhancing well-being outcomes. The following should be noted: (1) the human well-being measured in this study focused only on objective well-being, mainly considering that subjective well-being is mostly internalized compared with objective well-being [40]; (2) in order to identify the spatial heterogeneity and spatiotemporal evolution of human well-being, the level of human well-being in each district and county of the Xi’an metropolitan area was calculated separately, and the level of human well-being of the Xi’an metropolitan area as a whole was calculated based on the average of the well-being index.

2.3.3. Coupled Coordination Degree Models

Referring to the concept of coupling and the coupling degree function in physics, and drawing on with existing studies [41,42], the coupling coordination relationship between ecosystem services and human well-being was calculated. The CCDM is widely applied in spatial coupling studies [43], effectively characterizing the dynamic interactions between ESs and HWB across temporal and spatial dimensions. However, its capacity to elucidate the spatiotemporal variations and underlying mechanisms driven by policy interventions remains limited. Consequently, this study focused on uncovering the spatiotemporal dynamics of ES and HWB interactions, aiming to address these gaps. The coupling coordination degree model calculation formula is as follows:
C = 2 E × W E + W 2 1 / 2 = E × W 2 E + W
T = α E + β W
D = C × T
In this equation, C denotes the coupling degree; E and W, respectively, represent the comprehensive indices of ecosystem services and human well-being, namely the standardized values of the total ESV or the comprehensive level of human well-being; T represents the comprehensive coordination index of the system; D represents the coupling coordination degree; and α and β are the comprehensive coordination evaluation coefficients for ecosystem services and human well-being in the communication system, respectively, with α + β = 1. In this study, it is considered that the two have the same importance; thus, α = β = 0.5. Referring to the classification basis of existing studies, the coupling coordination types of ecosystem services and human well-being in the Xi’an metropolitan area are divided into 10 categories (Table 3).

3. Results and Analysis

3.1. Temporal and Spatial Change Analysis of Ecosystem Service Value

3.1.1. Analysis of Temporal Changes in Ecosystem Service Value

Based on the improved ecosystem service value coefficients (Table 1), combined with the area of each land use type in each year, we obtained the alterations in ESV of each type of land in the Xi’an metropolitan area (Table 4), as well as the changes in individual ESVs (Table 5) from 2000 to 2020. Overall, the ESV of Xi’an metropolitan area from 2000 to 2020 showed a trend of initially increasing and then decreasing. During the period from 2000 to 2005, it showed a growing trend, while from 2005 to 2020, it continuously declined. The total ESV decreased from CNY 8.765 billion in 2005 to CNY 8.642 billion in 2020, with a total reduction of CNY 123 million. The period from 2005 to 2010 witnessed the most significant decrease in the total ESV, which was mainly caused by the decrease in the area of land use types. Specifically, the decrease in the area of cultivated land had the greatest impact on the decline in the total ESV during this period. From 2010 to 2020, the rate of decrease in the total ESV slowed down, mainly due to the increase in the area of watersheds.
From the perspective of different land use types, the ESV of arable land demonstrated a decreasing trend from 2000 to 2020. The ESV of forest land, grassland, and water areas all exhibited fluctuating changes, with increases and decreases occurring at different times. However, the percentage change in the total ESV relative to the overall ESV was relatively stable. The ESV of construction land showed a steady growth trend, with its percentage in the ESV increasing from 0.43% in 2000 to 0.57% in 2020, and the overall change was relatively stable. Based on the analysis of land use types, the change in arable land was the main factor contributing to the decline of total ESV from 2000 to 2020, while the fluctuating increases and decreases in grassland and water effectively mitigated the decline in the total ESV.
Regarding the individual unidirectional ESV changes, among the four types of primary ecosystem services during 2000–2020, the provisioning services were in a continuous downward trend, while the regulating services, supporting services, and cultural services showed fluctuating trends, which were consistent with the overall ESV change trend in the study area. Among them, the value of regulating services was the highest, the value of supporting services was higher than that of provisioning services, and the value of cultural services was the lowest. In terms of proportion, the proportion of the value of each service fluctuated with increases or decreases. Overall, the supply and support services exhibited negative growth, while the regulating and cultural services showed positive growth during the period of 2000–2020.

3.1.2. Analysis of the Evolution of Spatial Patterns

The spatial distribution of ESVs at the district and county scale in the Xi’an metropolitan area from 2000 to 2020 was calculated using the ArcGIS 10.4 tool (Figure 3). Spatially, the overall distribution pattern of the ESV shows an increasing distribution from the core area to the periphery of the Xi’an metropolitan area. The high-ESV areas in the study area were mainly distributed in Zhouzhi County, Huyi District, Chang’an District, Lantian County, and Huazhou District. The southern part of these districts and counties is the forested area of the Qinling Mountains, which is rich in natural resources. Some of the areas with high ESVs were also mainly distributed in the area s along the Weihe River and the northern mountains. In these regions, the overall ecological and environmental protection is good, and the distribution of rivers and mountains is closely related. The land types are relatively dominated by forest land, grassland, and watersheds, including Yaozhou District, Liquan County, Qian County, Linwei District, Fuping County, and other districts and counties. The medium-ESV areas were mainly distributed in the central part of the study area, where arable land is predominant and is the main distribution area of unutilized land. The low-ESV areas were concentrated in the main urban areas of Xi’an City and Xianyang City. Affected by the increasing level of urbanization, the increasing area of land that is used for construction, and the intensity of human activities, the low-ESV areas are expanding year-by-year.

3.2. Spatial and Temporal Analysis of Human Well-Being

From 2000 to 2020, human well-being in the Xi’an metropolitan area showed an overall upward trend, with the most significant change occurring from 2005 to 2010 and a gradual slowdown in the rate of growth of human well-being from 2010 to 2020 (Figure 4). At the district and county levels, human well-being in all districts and counties in the study area showed a continuous upward trend, with some districts and counties showing fluctuating increases, such as Lantian County, Sanyuan County, Linwei District, and Yangling Demonstration District. The various subsystems of human well-being also showed a fluctuating upward trend, with the rapid improvement in health well-being contributing more to the rise in overall well-being, and the share of health well-being in each district and county increasing significantly. The change in the level of security well-being was relatively small, with the least regional variability. The evolution of the human well-being subsystem reflects the significant contribution of the increase in per capita park green space areas, the green coverage rate of the built-up area, and the level of health care to the growth of human well-being. From a spatial perspective, the level of human well-being showed obvious spatial heterogeneity. The high-value areas of human well-being from 2000 to 2020 were concentrated in districts and counties such as Yanta, Zhouzhi, Chang’an, Weiyang, and Qindu Districts. These areas not only have a good ecological environment base, but also have a better development of social services, which are able to provide more safety and health well-being. The low-value areas of human well-being were mainly distributed in Lantian County, Baqiao District, Jingyang County, and Yaozhou District in the periphery of the Xi’an metropolitan area. In these areas, the level of social service provision is relatively low, and the growth rate of health and well-being is much lower than those of other districts and counties, reflecting regional imbalances in human well-being and a weak regional linkage effect.

3.3. Analysis of Coupled Coordination of Ecosystem Services and Human Well-Being

The coupled coordination of ecosystem services and human well-being in the Xi’an metropolitan area during the period of 2000–2020 showed an overall trend of first increasing and then decreasing. However, the overall coupled coordination relationship improved from moderate to mild dysfunction with a slight improvement (Table 6 and Figure 5). The decline in the value of ecosystem services in the study area showed an inverse relationship with the continuous improvement in the level of human well-being, showing a fluctuating synergistic development process. During 2000–2010, the coupling relationship between ecosystem services and human well-being in the entire study area developed relatively rapidly, improving from moderate dissonance to the primary coordination stage. This reflects that the enhancement of supportive services and cultural services could contribute to the growth of some aspects of human well-being and weaken the coercive effect of well-being demands on ecosystem services. During 2010–2020, the coupling between ecosystem services and human well-being in the study area declined from primary coordination to a mildly dysfunctional stage. As the value of ecosystem services continued to decline, the rapid growth of population and built-up land in the study area slowed down the increase in human well-being levels, and the coercive effect of services on well-being increased.
The coupling between ecosystem services and human well-being in the study area exhibited spatial heterogeneity. From 2000 to 2020, the coupling between ecosystem services and human well-being in the study area fluctuated. The overall coupling degree of the counties in the core area showed a decreasing trend, while the coupling degree of the counties in the periphery had a small increase or remained relatively stable. This reflects that the expansion of the population and the land use for construction site aggravated the conflict between people and the land and increased the coercive effect of the enhancement of human well-being on ecosystem services. For example, Xincheng and Beilin Districts shifted from mild to moderate dissonance, Huyi District shifted from moderate coordination to moderate dissonance, and Lantian County shifted from moderate coordination to moderate dissonance. The small increase in the overall coupling coordination of the outlying districts and counties reflects a corresponding increase in both ecosystem services and human well-being in these districts and a relatively good synergistic relationship between human development and ecosystems. For example, Fuping County improved from mildly dysfunctional to barely coordinated, Qian County improved from moderately dysfunctional to on the verge of dysfunctional, and Sanyuan County improved from severely dysfunctional to mildly dysfunctional.
Overall, the Xi’an metropolitan area exhibits a pronounced “supply–demand mismatch”, resulting in a fragile coupling relationship between the ESs and HWB. Regions with low-value ESs face intensified pressures from population growth and economic expansion, driven by insufficient green space, an uneven spatial distribution of ecological resources, high population density, and concentrated industrial activities. These factors exacerbate the trade-offs between ES provision and urban development, underscoring the critical urgency of enhancing the ES supply capacity to improve HWB in these areas. In contrast, high-value ES regions and counties demonstrate more significant improvements in HWB levels and a higher degree of coupling coordination. This indicates that, over the studied period, the ES-HWB coupling in the region is characterized by HWB as a rigid element and ESs as a flexible facilitator or constraint. Achieving a well-coordinated relationship requires addressing the decline in ES values and mitigating the coercive effects of HWB improvement on ES provision.

4. Discussion

4.1. Multi-Scale Analysis Enhances Accuracy in ESV Evaluation

Previous evaluations of the ecosystem service value (ESV) primarily focused on the provincial and municipal scales, which restricted the depth of analysis. This study presents a refined multi-scale approach, covering both the metropolitan and county levels, for a more comprehensive understanding of the spatiotemporal dynamics of the ESV and its internal interrelations. Zhu Linna [44] identified a temporal decline in ESV across the Xi’an metropolitan area from 1990 to 2018, with a spatial pattern of diminishing values from urban centers to rural peripheries. Although in line with this general trend, the multi-scale analysis presented herein offers a more precise methodology to capture both macroscopic and localized ESV variations over the past two decades. This approach highlights regional heterogeneity more effectively, rendering the findings more consistent with real-world conditions and furnishing robust data support for integrated regional ecosystem management and coordinated development strategies.

4.2. Spatiotemporal Evolution of Ecosystem Service Value

Between 2000 and 2020, the Xi’an metropolitan area experienced an initial increase followed by a decline in ESV over time. Spatially, the ESV demonstrated a radial pattern, decreasing outward from the Xi’an city core. The key factors influencing these alterations are as follows: (1) Urban Expansion: The Xi’an metropolitan area, as the core of the Guanzhong Plain urban cluster, experienced significant population and economic growth from 2010 to 2020. This urban expansion exerted immense pressure on the ecological environment, leading to a gradient decrease in ESV. (2) Land Use Transformation: The conversion of large tracts of arable land into construction land reduced the unit value of ecosystem services, resulting in a net decline in ESV. (3) Human Activities: Higher levels of economic development intensified human activities, placing greater strain on the ecological environment. Services such as soil conservation and climate regulation—high-value components of the ESV—have diminished due to these pressures, creating spatial imbalances in the regional distribution of ESV.

4.3. Coupling Mechanism Between Ecosystem Services and Human Well-Being

Grasping the ES relationship is crucial for enhancing the total ES level and human well-being [45]. The relationship between ecosystem services and human well-being is complex and nonlinear, reflecting dynamic interactions influenced by stage-specific driving factors. During rapid urbanization, human well-being often rises due to the expansion of infrastructure and socio-economic services, giving rise to a coercive and unbalanced relationship with ecosystem services. This results in significant service value shrinkage and an expansion of low-value zones, exacerbating spatial imbalances in intra-regional coupling and coordination.
However, under a people-centered development paradigm, the enhancement of human well-being increasingly focuses on improving ecological quality. This shift promotes a synergistic relationship between ecosystem services and human well-being, fostering mutual enhancement and attaining coordinated development through positive feedback mechanisms. This coupling framework underlines the necessity of integrating ecological and socio-economic strategies for sustainable regional development. Therefore, rapid urbanization areas should strictly control the environmental impact of urban expansion on surrounding areas and weaken competition for space. Suburban urban areas should be developed in a protective manner, mitigating negative impacts and promoting environmental resilience through integrated land use planning. Regional spillovers of ecosystem services and human well-being should be strengthened across a wide range of regions, thereby fostering urban–rural integration and aligning with the Sustainable Development Goals (SDGs).
Building on previous studies, this research primarily focuses on regional-scale ESV and spatial clustering analysis. However, the findings may be influenced by the spatial resolution of underlying data and the selection of evaluation methods. From the perspective of regional sustainable development and ecological civilization construction, the impact of ESs on HWB is evident, exhibiting spatially heterogeneous dynamics. Future research should further explore meso- and micro-scale analyses to comprehensively reveal the intrinsic relationships and driving mechanisms between ESs and HWB.

5. Conclusions

This research investigates the Xi’an metropolitan area by addressing the dynamics between the ecosystem service value and human well-being through a combination of methodologies and frameworks.
Key Approaches: (1) Multi-Scale Analysis: The research assesses the ESV at both metropolitan and county scales, offering a detailed understanding of spatial and temporal changes. This detailed approach enables the identification of heterogeneity within the region, making the analysis more precise compared to broader provincial or municipal studies. (2) Spatiotemporal Evolution: The temporal trends from 2000 to 2020 exhibit an initial increase followed by a decrease in ESV, linked to urbanization and land use changes. The spatial patterns suggest a radial decline in ESV, moving from the urban center outward, driven by construction land expansion and reduced agricultural land. (3) Coupling Ecosystem Services and Human Well-Being: This research explores the intricate relationship between ecosystem services and human well-being. It identifies stages of coercive coupling during rapid urbanization, where infrastructure growth conflicts with ecological balance. The study emphasizes a people-centered development paradigm to foster mutual enhancement of ecosystem services and well-being, tackling imbalances in spatial distribution.
Outcomes for the Xi’an metropolitan area: (1) Urban Pressures: Significant ecological pressure due to population growth, economic development, and land use transformation was identified. Urban expansion led to a decline in high-value ecosystem services such as climate regulation and soil conservation. (2) Spatial Imbalance: Core areas exhibit higher human well-being but diminished ESVs, whereas peripheral areas experience reduced well-being despite potential ecosystem service availability. (3) Policy Implications: Proposals include stricter ecological space protection, land use optimization, and integrated management of human–ecological systems. In spatial planning, enhancing the ecological network connectivity of the Xi’an metropolitan area necessitates establishing greenway systems, ventilation corridors, and riverine restoration, alongside augmenting critical ecological corridors and source areas. These measures foster organic linkages between low- and high-value ES zones, facilitating efficient ES flow between high-supply and high-demand regions to optimize supply–demand matching. At the governance scale, respecting the continuity of natural geographic features (e.g., rivers, mountains) and transcending city/county administrative barriers are essential. This requires scientifically delineating ecological management boundaries and implementing systematic restoration in key areas, such as the Qinling Mountains’ northern foothills and the Wei River basin. Recommendations aim to enhance regional sustainability by aligning ecosystem services with human development goals.
This research provides a blueprint for sustainable development, offering a framework to balance urban growth with ecological health while ensuring equitable well-being across the Xi’an metropolitan area. In addition, owing to the data availability, system complexity, and technological immaturity, this paper has not yet been able to determine the nonlinear interactive coercive effects and transmission dynamics between ecosystem services and human well-being. Future research should focus on dynamic spatiotemporal coupling analysis and long-term monitoring, utilizing advanced tools like random forests and neural networks to explore multi-system stressors and multi-dimensional feedback mechanisms. Such efforts will clarify the complex interactions and feedback dynamics between ESs and HWB, offering robust and comprehensive decision-making support.

Author Contributions

Conceptualization, methodology, software, writing—original draft preparation, and visualization, Y.G. and P.Z.; validation and formal analysis, Y.G. and Z.L.; data curation, Y.X.; writing—review and editing, Y.G., K.L. and P.Z.; supervision, project administration, and funding acquisition, Y.G., P.Z. and Y.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Natural Science Basic Research Program of Shaanxi (Program No. 2023-JC-YB-301).

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Conflicts of Interest

The authors declare no conflicts of interest.

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Land 14 00500 g001
Figure 1. Geographic location and land use in Xi’an metropolitan area.
Figure 1. Geographic location and land use in Xi’an metropolitan area.
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Figure 2. The methodological framework of this study.
Figure 2. The methodological framework of this study.
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Figure 3. Spatial distribution of ecosystem service values.
Figure 3. Spatial distribution of ecosystem service values.
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Figure 4. Human well-being in Xi’an metropolitan area.
Figure 4. Human well-being in Xi’an metropolitan area.
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Figure 5. Coupled coordination of ecosystem services and human well-being at district and county scales in Xi’an metropolitan area.
Figure 5. Coupled coordination of ecosystem services and human well-being at district and county scales in Xi’an metropolitan area.
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Table 1. Calculation of the equivalent value of ecosystem services for various land use types in Xi’an metropolitan area (Unit: CNY/(hm2·a)).
Table 1. Calculation of the equivalent value of ecosystem services for various land use types in Xi’an metropolitan area (Unit: CNY/(hm2·a)).
ESVProvisioning ServicesRegulation ServicesSupporting ServicesCultural Services
Food ProductionRaw Material ProductionGas RegulationClimate RegulationHydrological RegulationSoil ConservationBiodiversityEsthetics
Arable land510.7651.08255.35454.55306.44745.68362.605.08
Forest land51.081327.911787.591378.991634.341991.861664.99653.74
Grassland153.2525.51408.60459.68408.60995.96556.7120.43
Waters51.085.080.00234.9210,408.765.081271.742216.56
Building land47.680.000.000.00150.250.000.0047.68
Unused land5.080.000.000.0015.3010.22173.625.08
Table 2. Multi-dimension index system of HWB in Xi’an metropolitan area.
Table 2. Multi-dimension index system of HWB in Xi’an metropolitan area.
AspectIndexIndex AttributeWeights
Safety well-beingPopulation density-0.069
Ratio of disposable income per capita for urban and rural residents-0.029
Real GDP per capita+0.074
Urban road space per capita+0.055
Annual mean temperature-0.012
Annual precipitation+0.025
Health well-beingParkland area per capita+0.273
Green coverage rate of built-up area+0.089
NDVI+0.079
PM2.5-0.068
Number of beds health institutions+0.147
Health technicians+0.08
Table 3. Divisions of coupling coordination of ecosystem services and human well-being.
Table 3. Divisions of coupling coordination of ecosystem services and human well-being.
Coupling Coordination DegreeCoupling Coordination LevelCoupling Coordination Type
[0.0~0.1)1Extreme Disorder
[0.1~0.2)2Severe disorder
[0.2~0.3)3Moderate disorder
[0.3~0.4)4Mildly dysfunctional
[0.4~0.5)5Nearly dysfunctional
[0.5~0.6)6Barely coordinated
[0.6~0.7)7Elementary coordination
[0.7~0.8)8Intermediate coordination
[0.8~0.9)9Good coordination
[0.9~1.0]10Quality coordination
Table 4. Changes in ecosystem service values of various types of land in Xi’an metropolitan area from 2000 to 2020 (unit: billion).
Table 4. Changes in ecosystem service values of various types of land in Xi’an metropolitan area from 2000 to 2020 (unit: billion).
Type20002005201020152020
Value VolumeProportionValue VolumeProportionValue VolumeProportionValue VolumeProportionValue VolumeProportion
Arable land29.1033.31%28.4632.46%27.8432.08%27.6531.98%26.8031.01%
Forest land44.0850.46%44.1650.39%44.7051.50%44.6451.62%44.4051.37%
Grassland10.6712.21%10.6912.20%10.2211.78%10.2111.81%10.5012.15%
Waters3.123.58%3.924.48%3.534.07%3.443.98%4.154.80%
Building land0.370.43%0.410.47%0.500.58%0.520.60%0.570.66%
Unused land0.000.00%0.000.00%0.000.00%0.000.00%0.000.01%
Total values87.35100.00%87.65100.00%86.80100.00%86.47100.00%86.42100.00%
Table 5. Value and change in individual ecosystem services in Xi’an metropolitan area from 2000 to 2020 (unit: billion).
Table 5. Value and change in individual ecosystem services in Xi’an metropolitan area from 2000 to 2020 (unit: billion).
Type20002005201020152020
Value VolumeProportionValue VolumeProportionValue VolumeProportionValue VolumeProportionValue VolumeProportion
Provisioning services12.5814.4012.4714.2312.4014.2912.3614.2912.1814.09
Regulating services38.2343.7738.6644.1138.2344.0438.0744.0338.3244.34
Supporting services33.1037.9032.9537.5932.6137.5732.5037.5932.2737.34
Cultural services3.433.933.574.073.564.103.544.093.654.22
Total values87.34100.0087.65100.0086.80100.0086.47100.0086.42100.00
Table 6. Coupled coordination of ecosystem services and human well-being in Xi’an metropolitan area.
Table 6. Coupled coordination of ecosystem services and human well-being in Xi’an metropolitan area.
YearCoupling Degree (C)Coordination Index (T)Coupling Coordination Degree (D)Coupling Coordination LevelCoupling Coordination Type
20000.2290.3770.2943Moderate disorder
20050.4380.5210.4785Nearly dysfunctional
20100.9750.4010.6257Elementary coordination
20150.4930.3840.4355Nearly dysfunctional
20200.1990.50.3154Mildly dysfunctional
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Gao, Y.; Zhang, P.; Xu, Y.; Li, Z.; Liu, K. A Study on the Spatiotemporal Characteristics of the Xi’an Metropolitan Area Based on the Coupling and Coordination of Ecosystem Services and Human Well-Being. Land 2025, 14, 500. https://doi.org/10.3390/land14030500

AMA Style

Gao Y, Zhang P, Xu Y, Li Z, Liu K. A Study on the Spatiotemporal Characteristics of the Xi’an Metropolitan Area Based on the Coupling and Coordination of Ecosystem Services and Human Well-Being. Land. 2025; 14(3):500. https://doi.org/10.3390/land14030500

Chicago/Turabian Style

Gao, Yunsong, Pei Zhang, Yuqian Xu, Zhijun Li, and Kaixi Liu. 2025. "A Study on the Spatiotemporal Characteristics of the Xi’an Metropolitan Area Based on the Coupling and Coordination of Ecosystem Services and Human Well-Being" Land 14, no. 3: 500. https://doi.org/10.3390/land14030500

APA Style

Gao, Y., Zhang, P., Xu, Y., Li, Z., & Liu, K. (2025). A Study on the Spatiotemporal Characteristics of the Xi’an Metropolitan Area Based on the Coupling and Coordination of Ecosystem Services and Human Well-Being. Land, 14(3), 500. https://doi.org/10.3390/land14030500

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