Town Scale Research Articles

Measuring Rurality and Analyzing the Drivers of Rurality in Megacities—A Case Study of Shanghai, China

The Rurality Index is an important reference for the formulation of rural development strategies and policies, but the evaluation of the rurality of megacities based on the township scale is relatively limited. Based on the perspective of spatial governance, this study constructed the evaluation index system of Shanghai’s rurality and carried out the evaluation of Shanghai’s rurality at the township scale from 2005 to 2020. The article adopts the MGWR model to analyze the driving effects of five key driving factors (the proportion of foreign population, per capita industrial output value, public finance revenue, social fixed asset investment, and rail transit coverage), and adopts the Geo-Detector model to analyze the interactive driving effects of two factors. The results indicate that the rurality index of megacities and townships as a whole shows a weakening trend, and the above factors have a predominantly negative impact on rurality, with differences in the intensity of the impact in different periods. There is an obvious interactive additive effect between the factors. When formulating policies for township development, government departments need to take into account the functional positioning of the region and comprehensively adopt targeted policies on population, industry, transportation, finance and investment to regulate and guide the transformation or sustainable development of the countryside.

Delineating Ecological Functional Zones and Grades for Multi-Scale Ecosystem Management

Integrating ecosystem services (ESs) to delineate ecological functional zones (EFZs) is fundamental in terrestrial spatial planning and ecosystem management. However, existing studies have largely overlooked the refinement of EFZs at local scales, which hinders targeted and multi-scale ecosystem management. This study introduced a “two-step refinement zoning method” to address this gap, first using a self-organizing feature mapping method to delineate EFZs at a township scale, and then applying a hotspot overlay analysis to refine the resulting EFZs by designating them with different grades at the village scale. The proposed method was applied in Wuhan City, dividing it into five types of EFZs with different ES combinations and land use compositions. Furthermore, 5.23% of villages were identified as level I areas of EFZs, serving as advantageous areas of dominant ESs in the study area. On this basis, diversified management strategies and conservation priorities were proposed. This study provides a theoretical and methodological reference for terrestrial spatial planning and sustainable ecosystem management.

Assessing Building Energy Savings and the Greenhouse Gas Mitigation Potential of Green Roofs in Shanghai Using a GIS-Based Approach

Climate change can significantly affect building energy use and associated greenhouse gas (GHG) emissions in urban areas, as fossil fuels remain a significant energy source. Green roofs can offer multiple benefits to the urban environment, but their effects on GHG mitigation have not been fully investigated, especially under climate change. This study assessed green roofs’ contribution to GHG mitigation by saving building energy and absorbing CO2 under the present (2017–2019) and future (2049–2051) climate scenarios (SSP2-45 and SSP5-85) in Shanghai, China, at the city and township scale. A Geographic Information System (GIS)-based spatial statistical method was developed based on climate change modeling and building energy simulation. The results suggested that installing green roofs can effectively save building energy regardless of building type, yet the amount of savings can vary depending on the weather conditions within the city. The contribution analysis indicated that most saved building energy was attributed to the Heating, Ventilation, and Cooling (HVAC) system, with more energy saved under warmer climate scenarios in the future, particularly during the summer months. More energy was saved from shopping malls on an annual and monthly scale, regardless of the climate scenarios and weather zones. Finally, a case study indicated installing green roofs on all five types of buildings (office, hotel, hospital, shopping mall, apartment) of less than 50 m in height can reduce 8.28% of the CO2 emitted during the building operation stage in the entire city under the present climate scenario. The annual CO2 reduction varied with the location of townships, ranging from 2.18% to 13.78%, depending on the composition of building types and local weather conditions in Shanghai. This study offered policymakers a reference on the environmental benefits and investment values of installing green roofs in large cities.

Small watersheds are the best control and management unit for improving soil conservation services in karst areas

Climate factors and changes in landscape patterns are often recognized as the primary drivers of soil conservation services. The influence mechanism of climate factors and landscape patterns on soil conservation service is scale-dependent and spatial heterogeneous. However, it is not clear whether small watershed scale is more conducive to soil erosion control than large scale such as county scale and township scale. For the purpose of creating land use development plans that take local conditions into account, it is crucial to clarify the effects of climate and landscape pattern factors on soil conservation change. Wujiang River basin (WRB), a typical karst basin located in the catchment of the largest first-level tributary on the upper Yangtze River in China, was used as the study area in this research. Soil conservation services provided by water erosion control (SPC) in WRB from 2005 to 2020 were evaluated using the RUSLE model based on the modified rock exposure rate. By using stepwise regression model and multi-scale geographically weighted regression model (MGWR), the spatial heterogeneity of the influence of different driving factors on soil conservation service was comprehensively studied at the scale of district, township and small watershed. The results show that the SPC fluctuates obviously, but the trend is not significant. Climate factor is the dominant factor affecting SPC. With the change of scale from large to small, the adjusted R2 of the regression model gradually increases, especially the factors related to landscape pattern, and more driving factors can be revealed more comprehensively and effectively. Therefore, the small watershed scale is the best control unit to improve the SPC when formulating the regional management landscape plan. The findings of this research also have benchmark significance for other ecological fragile areas, and can provide more comprehensive suggestions for local ecosystem management and landscape planning.

Tracking sustainable development in mining towns: A novel framework integrating socioeconomic and eco-environmental perspectives through coupling coordination degree

Assessing coupling coordination (CCD) between socioeconomic development (SD) and eco-environmental quality (EQ) is vital for sustainable development blueprints for mining towns. However, previous studies often overlooked the policy context and the asymmetry of SD and EQ impacts on CCD, in the modeling process, leading to a lack of objectivity and generalizability in the current methods. Therefore, this study devised a novel framework for assessing the CCD in mining towns by leveraging Convolutional Autoencoders and the Cusp Catastrophe model. The effectiveness of the framework was verified using Panxi mining town in China as a case study. Results demonstrate: (1) 65% primary coupling coordination indicates lagging SD in the Panxi mining towns in 2020; (2) there is an evident exponential growth trend in CCD of the Panxi mining towns grew exponentially (R2 = 0.94) from −0.351 in 2001 to 0.062 in 2020, and transforming from disorder to primary coupling coordination in 2015; (3) post-2013, effective local policies and measures boosted CCD by 35%, but currently they have not been continuously transformed into a driving force for CCD growth. Therefore, considering the practical challenges associated with different coupling coordination categories, this study provides recommendations for sustainable development at the township scale. The results provides insights for Panxi's sustainable development and aids in developing reliable predictive models for CCD for other mining towns.

Towards an Urban Planning Scenario Model System—A Tool for Exploring Urban Uncertainty: A Case Study of Diaozhen, China

The ‘Urban Interaction’ project aims to develop an urban planning model system at the scale of towns or small cities consisting of three modules: growth forecast, land-use decision, and evaluation. This paper presents the framework of the model system to identify and discuss the assumptions and theoretical basis of the model system. The model system will be driven by scenario planning theory and sustainable urban development principles. It will export land-use planning based on selected urban development scenarios and urban planning theories. This paper takes Diao Town in Jinan as an example. Applying GIS spatial analysis and hierarchical analysis, this paper determines the suitability of land use and the weights of different influencing factors, combined with the land-use conflict identification model, for land-use decision-making. Finally, the assessment module verifies whether the planning scheme complies with laws and regulations to achieve an active, reactive response to uncertainty. The paper discusses the ‘uncertainty’ of urban planning and proposes a creative, flexible, and timely planning platform that allows planners and other participants to model and visualize their scenarios.

Characterization of Rural Spatial Commodification Patterns around Metropolitan Areas and Analysis of Influential Factors: Case Study in Shanghai

Rural areas around developed metropolitan areas continue to attract capital inflows, promoting rural spatial commodification. Taking Shanghai as a case study, this paper analyzes the characteristics of the spatial distribution pattern and the influencing factors of rural spatial commodification (RSC) through kernel density analysis, multiple regression models, and spatial autocorrelation analysis. This study explores four types of RSC at the township scale outside the center of Shanghai: agricultural product-oriented commodification, farm housing commodification, tourism-oriented commodification, and construction land commodification. The results show the following: (1) The four types of RSC show positive spatial correlation, a clear pattern of agglomeration, and an obvious core–edge pattern, with high-density areas distributed in rural areas with specific advantages around metropolitan areas. The distribution of RSC also demonstrates an obvious polarization, forming an uneven distribution pattern. (2) Socio-economic factors, agriculture, transportation location, urbanization, and industrialization are key factors driving RSC. (3) Different types of RSC should be effectively guided at the policy and planning levels according to regional conditions and development stages to enhance the spatial organization of rural regions and achieve the effective revitalization of the countryside surrounding the metropolis.

How is human well-being related to ecosystem services at town and village scales? A case study from the Yangtze River Delta, China

ContextThe relationships between ecosystem services (ES) and human well-being (HWB) have been found to be influenced by geographic locations and socioeconomic development, and vary from local to global scales. However, there is a lack of comparative analyses at fine administrative scales such as town and village scales.ObjectiveThis study took the core region of the Yangtze River Delta (YRD) of China as the study area to examine the spatial characteristics of the values of ES and the subjective satisfaction scores of HWB and then compare their relationships at the town and village scales.MethodsThe values of 9 ES indicators were quantified using the ecosystem service equivalent factor method, and the subjective satisfaction scores of 11 HWB indicators were investigated using the questionnaire survey. The ES-HWB relationships between 9 ES and 11 HWB measures in the study area were investigated using Spearman's correlation analysis.ResultsThe value of ES per unit area in the study area in 2020 was about 15,202.90 USD/ha, nearly three times the average level in China, but the per capita value was relatively low, at 322.11 USD/person. The satisfaction score of HWB was relatively high, especially for the dimensions of social relations (4.46), health (4.26), and safety (4.22), based on a 5-point Likert scale. As spatial scales decreased from town to village scales and thematic scales increased from secondary to primary indicators, the strength of the ES-HWB correlations diminished and their direction changed as well. According to secondary indicators, most of the ES-HWB relationships were positive at the town scale but became negative or nonexistent at the village scale (e.g. the Spearman correlation coefficient between the value of raw material supply and the satisfaction score of leisure and entertainment shifted from 0.9 at the town scale to -0.51 at the village scale).ConclusionsThe correlation strength and direction of the ES-HWB relationships still changed with spatial and thematic scales at the town and village scales. Thus, better understanding the relationships requires studies at multiple and broader scales and calls for caution when using the aggregating indicators, because they can also lead to different ES-HWB relationships.

Spatial-Temporal Evolution of Agricultural Carbon Balance at Township Scale and Carbon Compensation Zoning: A Case Study of Guangshui City, Hubei Province

Optimizing agricultural carbon compensation zoning is crucial for establishing robust mechanisms in agricultural carbon compensation management, with significant implications for achieving national “dual carbon” strategic objectives. This study employs K-means and the three-dimensional magic cube approach to construct a novel evaluation index system for comprehensive carbon compensation zoning. By combining spatial land-use zoning, we delineate carbon compensation zones in Guangshui City, Hubei Province, and analyze the spatiotemporal variations of agricultural carbon balance, proposing optimization strategies. The results show that (1) from 2000 to 2021, agricultural carbon emissions and absorption exhibit a trend of increasing followed by decreasing, with spatial patterns of “higher in the northwest, lower in the southeast” and “higher in the southwest, lower in the northeast”; (2) the Gini coefficient of agricultural carbon emissions averages at 0.24, with economic contribution coefficients and ecological carrying coefficients ranging from 0.04–16.1 and 0.39–1.99, respectively, from 2000 to 2021; and (3) in 2021, Guangshui City comprises seven payment zones, four balance zones, and six compensation zones, ultimately forming eight optimized agricultural carbon compensation zones in alignment with regional agricultural carbon balance objectives. This study provides theoretical references for enhancing county-level agricultural carbon comprehensive compensation management mechanisms.

The Temporal and Spatial Evolution Characteristics and Driving Factors of Ecosystem Service Bundles in Anhui Province, China

Identifying ecosystem service bundles and their long-term evolutionary characteristics is essential for the overall enhancement of regional ecosystem services, as well as the division and management of functional areas, providing a basis for decision-making in formulating ecological and environmental protection policies, as well as regional development planning. Based on land use, remote sensing, and meteorological data obtained from Anhui Province, this study assessed six important ecosystem service functions, including food production (FP), water yield (WY), carbon sequestration (CS), soil conservation (SC), habitat quality (HQ), and landscape aesthetics (LA), at the township scale in 2000, 2010, and 2020. On this basis, the k-means clustering method was used to identify ecosystem service bundles, analyze the spatio-temporal evolution trajectory of service bundles, and explore the driving factors of the spatio-temporal evolution of ecosystem service bundles using GeoDetector 2015 The results indicate the following: (1) At the spatial level, diverse ecosystem services demonstrate pronounced spatial differentiation. The distribution pattern of HQ, carbon fixation, and SC services is generally lower in the north and higher in the south, with areas of high value predominantly located in the western Dabie Mountains and the mountains of Southern Anhui. Conversely, FP services exhibit the reverse pattern, and WY services display a gradual increase from north to south, while cultural services are more dispersed, with areas of high value primarily located in the western Dabie Mountains, the Yangtze River Basin, and other locations. On the temporal scale, WY, SC, and FP services mainly exhibit an increasing trend, marked by a significant increase, whereas other services tend to present a decreasing trend. (2) Anhui Province can be categorized into four distinct types of service bundles: the grain production bundle (GPB), mountain ecological conservation bundle (MECB), urban living bundle (ULB), and core protection bundle (CPB). Ecosystem service bundles exhibit clear spatial differentiation, and identical service bundles demonstrate substantial clustering in space. Between 2000 and 2020, ecosystem service bundles displayed a marked spatio-temporal evolution, with the prevalence of GPBs diminishing, whereas the share of ULBs progressively increased, and the number of MECBs and CPBs remained largely stable. (3) In the spatio-temporal evolution process, the average annual precipitation, the proportion of forest land, and slope constitute the principal natural factors influencing the spatio-temporal evolution of ecosystem service bundles, while the proportion of construction land represents the primary socio-economic factor, with natural factors exerting a more significant influence than socio-economic factors.

Ecological risk assessment and influencing factors in the Wuhan Metropolitan Area based on supply and demand bundles of ecosystem services

In the context of rapid urbanization, metropolitan areas are facing the risk of supply-demand mismatches among ecosystem services. Investigating the patterns, relationships, and driving factors of multiple supply-demand risks is of great significance to support the efficient management of regional ecological risks. We quantified the single/comprehensive supply-demand risk rates of six ecosystem services in Wuhan Metropolitan Area at the township scale in 2000, 2010, and 2020. By applying the self-organizing feature map network and optimal parameter geo-detector, we identified supply-demand risks bundles of ecosystem services and influencing factors of comprehensive risks. The results showed significant spatial variations in the supply-demand risks of typical ecosystem services from 2000 to 2020. The supply-demand risk associated with grain production, water yield, carbon sequestration, and green space recreation increased, while soil conservation and water purification risks decreased. The comprehensive ecosystem services supply-demand risk increased from 0.41 to 0.45, indicating a 'core area increase and periphery decrease' trend. Throughout the study period, the area exhibited bundles of comprehensive extremely high-risk bundles (B1), comprehensive high-risk bundles (B2), water purification high-risk bundles (B3), and grain production-soil conservation risk bundles (B4). The transition of risk types from B3 to B2 and from B2 to B1 suggested an increase in the combination and intensity of supply-demand risk. Vegetation cover, nighttime light index, and population density were the main driving factors for spatial variations in comprehensive supply-demand risk. Ecologi-cal risk assessment based on ecosystem services supply-demand bundles could provide an effective and reliable way to regulate multiple regional risk issues.

Unravelling regional development through the production-living-ecological perspective: Assessing heterogeneity and expert insights

This study delves into the spatial heterogeneity of Production-Living-Ecological Spaces (PLES) at the township scale in Zhejiang, China. By leveraging a comprehensive array of spatial data and advanced analytical methods, we uncover distinct patterns and variations within these spaces. Our analysis brings to light the complex interactions between human activities, land use, and ecological factors in the region. Through grid-based evaluation, significant spatial disparities in land use across Zhejiang Province are identified, reflecting the diverse socio-economic and environmental fabric of the area. Particularly notable is the dominance of ecological considerations in economically developed and coastal regions. Spatial autocorrelation analysis reinforces this finding by confirming functional clustering among neighboring townships. The application of triangular coordinate analysis further underlines the preponderance of ecological factors, pointing to a prevailing trend of environmental prioritization. Complementing the spatial data analysis, insights from expert interviews add depth to our understanding. These discussions with professionals engaged in PLES planning and development elucidate the real-world implications of our findings, offering a nuanced perspective on the challenges and opportunities in managing these spaces. Experts highlight the need for an improved approach to accommodating the functions of production, living, and ecological spaces, addressing both regional needs and sustainable development goals. The study contributes to the field of regional planning and sustainable development, emphasizing the importance of recognizing and addressing spatial heterogeneity in PLES. It provides insights for decision-makers and planners seeking to navigate the delicate balance of socio-ecological landscapes in Zhejiang and similar regions.

Study on the differences and influencing factors of spatial distribution of population aging at township scale: a case study of township research units in Anshun City, China.

An aging population is one of the main features of China's current population structure, and it is a key area that needs attention to achieve high-quality population development. Because of its unique geographical environment, economic conditions, and sociocultural background, the study of population aging in the karst region of southwest China is particularly important. However, there is a lack of research exploring the regional differentiation of population aging and its influencing factors in the karst regions of southwest China. In light of this, we chose Anshun City, located in Guizhou Province's southwest area, as the case study area. We used the Lorenz curve and spatial autocorrelation to study the differences in the spatial distribution pattern of population aging and introduced multi-scale geographical weighted regression to explore its influencing factors. The results show that Anshun City's older people population proportion (OPP) is generally high with more than 7% of the older people there, making it part of an aging society. The OPP appeared high in the east and low in the west in spatial distribution; the older people population density (OPD) revealed a gradually increasing trend from south to north. At the township scale, both the OPP and the OPD showed significant spatial positive correlation, and the spatial agglomeration characteristics were obvious. OPD and OPP have a positive spatial correlation at the global level, and townships with similar OPP or OPD were spatially adjacent. The spatial distribution characteristics of population aging are the consequence of complex contributions such as natural, social, economic, and karst factors. Further, the spatial distribution pattern of aging is determined by a variety of influencing factors, which have different directions and intensities. Therefore, it is necessary to formulate and implement corresponding policies and strategies to deal with the aging problem in the future.

Refined landslide susceptibility mapping in township area using ensemble machine learning method under dataset replenishment strategy

Landslide susceptibility mapping (LSM) warrants considerable attention as a prerequisite for risk assessment and prevention in response to the increasing global occurrences of landslides. However, refined LSM at the township scale still faces the problem of the limited number of landslides and the oversight of relevant factors associated with different landslide types. This work is dedicated to propose a novel dataset replenishment strategy designed to address landslide sample scarcity, and to identify dominant factors in high landslide susceptibility zones to refine LSM at township scale for decision makers. Herein, the Wuling County in the Three Gorges Reservoir area of China was taken as taken as the research case. Initially, field investigation and calibration of 21 landslides yielded accumulation and rock areas, and the corresponding impact factors were therefore proposed to construct input features for machine learning facilitated by factor diagnosis using Pearson correlation coefficient (PCC) and multicollinearity test. Subsequently, a training and validation dataset split of 8: 2 was randomly generated, enabling the application of ensemble machine learning model for LSM prediction. The study culminated in the feasibility of dataset replenishment strategy, which was employed to explore uncertainties and identify governing factors in LSM. The results indicate that the bagging-ANN model exhibits superior performance in both accumulation and rock areas, with Areas Under Curve (AUC) of 0.987 and 0.994. Furthermore, the dataset replenishment strategy emerges as instrumental in enhancing the reliability of LSM, as evidenced by an 8.97 % reduction in average value (AVG) and a 11.00 % increase in standard deviation (STD). The governing factors for landslides in accumulation and rock areas are designated as river erosion and height, respectively. Together with the excellent performance, this study is expected to provide a promising reference for LSM in other townships worldwide.

Evaluating and simulating the impact of afforestation policy on land use and ecosystem services trade-offs in Linyi, China

Forest can provide multiple benefits, such as supplying a variety of ecosystem services. However, the planet is currently at risk of deforestation as a result of increased urbanization and growing food demand. Countries around the world have introduced a wide range of policies to mitigate this issue. In China, the Linyi City government has launched the cross-county forest credit market transactions (CFCMT) policy, which showcased significant innovations in compliance credits and transaction entities to enhance motivation for afforestation. This study creates a no-policy counterfactual scenario to analyze the woodland growth and ecosystem service trade-offs between 2013 and 2021. The results demonstrate that the woodland grew faster after this policy, with a growth rate 1.78 times higher than that from 2013 to 2017. The areas of woodland growth with the policy are mainly located on the edges of cropland and woodland. The increased woodland primarily originates from cropland conversion, and compared to the no-policy scenario, these growing woodlands have gentler slopes and lower altitudes. After the policy’s enforcement, there were more increases in carbon storage, soil retention, and habitat quality. And ecosystem services showed a more optimizing trend in the direction of synergy at grid and town scales. We also find that larger spatial scales exhibit synergies and less accurately represent trade-off/synergistic change trends. The ecosystem services bundle consisting of carbon stocks, soil conservation and habitat quality showed a significant increase. This study reveals woodland growth and trade-offs among ecosystem services after the implementation of CFCMT policy, offering valuable insights for future afforestation policy optimization and promotion.

Exploring the Built Environment Factors Influencing Town Image Using Social Media Data and Deep Learning Methods

The representational image of the city has attracted people’s long-term attention. Nevertheless, the mechanism of interaction between the image and the built environment (BE) and image studies at the town scale have not been fully explored. In this study, we collected multi-source data from 26 characteristic towns in Tianjin, China. We explored a deep learning approach to recognize social media data, which led to the development of quantifiable town uniqueness image (UI) variables. We studied the influence of the BE on the town UI and the moderating effects of positive emotions on the relationship between the two. The results showed that positive emotions had significantly positive moderating effects on the water system ratio’s effect on UI, but weakened sidewalk density and tourist attraction density. They also inhibited the negative effects of road connectivity but could strengthen the negative effects of the sky view factor and points of interest (POI) mix. The moderating effects on other variables are relatively mediocre. This study helps to reveal the inner mechanism of BE and town image. It is conducive to accurately coordinating the relationship between planning policies and design strategies, optimizing resource allocation, and promoting sustainable town development.

Theoretical Logic and Implementation Path of Comprehensive Land Consolidation for Promoting Common Prosperity: A Case Study of Ningbo City

Eliminating poverty and achieving social justice are global concerns. China has focused on common prosperity. Comprehensive land consolidation is a potential policy tool that can contribute to common prosperity, but its effectiveness and implementation methods are yet to be verified and discussed. Therefore, we construct an analytical framework to understand how comprehensive land consolidation promotes common prosperity. The pilot area for comprehensive land consolidation in Ningbo City is used as a qualitative case study. The research results indicate that comprehensive land consolidation focuses on development and sharing to promote high-quality socio-economic development, social fairness, and justice. The paths for achieving development included the following: (1) a network governance structure consisting of multiple entities to enhance land governance; (2) various consolidation activities were conducted at the town scale to optimize the functionality and spatial pattern of public spaces; and (3) enabling the flow of urban and rural factors for improved resource allocation efficiency and providing an impetus for industrial development. The paths for achieving sharing included clarifying collective land ownership and promoting land transactions to provide diverse land values and ensure a shared distribution. This research provides new insights applicable to other Chinese cities and numerous developing countries engaged in land consolidation to address social distribution issues.

Evaluation and Analysis of the County-Level Sustainable Development Process in Guangxi, China in 2014–2020

Sustainable development has become a scientific and decision-making consensus in countries and regions around the world. The current research on sustainable development mainly focuses on urban areas with a high level of economic development and intensive land use. Small-scale research, especially for underdeveloped areas, is required to reveal the spatial patterns and differences within administrative units. This study focuses on 1241 towns in Guangxi to assess the sustainable development process and variations at the township scale from 2014 to 2020 by using the entropy method, the coupled coordination degree method, and cluster analysis. The results show that the average sustainable development goal composite index (SDGCI) of towns in Guangxi is around 0.12, and their overall sustainable development level is low. The SDGCI of towns in the central region shows an increasing trend, while that in the northern and southern regions shows a decreasing trend. Then, the SDGs are divided into three systems, namely people, planet, and prosperity. The prosperity system contributes the most to the overall SDGCI, and the low values of the people and planet systems are the reason for the low level of sustainable development in Guangxi. The coupling degree of the SDGCI among the three systems is at a high level, and the level of coupling coordination degree is good, which indicates high consistency and close linkage of the towns in Guangxi when pursuing the SDGs. The results of hierarchical cluster analysis show that towns in Guangxi can be divided into three categories to adapt to different features based on SDGCI values. The assessment of SDG process in towns in Guangxi could guide local governments to refine their development policy, formulate and adjust development strategies in a targeted manner, and promote balanced and sustainable development under townships.

Evaluating the Spatial Evolution of the Eco-Economy Harmony in Anxi County, China, Based on Ecosystem Services Value

The harmonious development of the ecological environment and the economy is extremely important to achieve regional ecological construction and sustainable development. To properly assess the status of the harmonious development of the ecosystem and the economy, this study constructed an improved ecosystem services value (ESV) and eco-economic harmony (EEH) model to analyze the coordination relationships between the ecosystem and the economy in this region, based on Landsat TM/OLI data of Anxi County in 1999, 2009, and 2019. The results were as follows. (1) Significant changes in land- use occurred in Anxi County between 1999 and 2019. While grassland, cultivated land, and water bodies decreased by 22.91%, 36.82%, and 8.18%, respectively, other land-use types expanded including construction land (206.10%), garden land (56.39%), forest land (10.37%), and unutilized land (90.43%). (2) The ESV decreased by CNY 41.02 billion during this period, with the largest contribution from forest land and the most important service function being regulating services, and mountainous townships made a great contribution to the total ESV. (3) The eco-economic system of Anxi County was at an inharmonic level. The evaluation model produced more favorable results, especially at the township scale, which is highly sensitive to economic policy. This can provide scientific evidence for inter-regional ecological compensation and sustainable development while providing reference and inspiration for similar areas around the world to carry out relevant research.

Ecosystem service tradeoff and synergistic relationship in the Yellow River Delta High-Efficiency Eco-Economic Zone.

Exploring the tradeoff and synergy relationship among ecosystem services in the Yellow River Delta High-Efficiency Eco-Economic Zone is of great practical significance for regional ecosystem service function zoning and high-quality development. Using the InVEST model, spatial auto-correlation and trade-off synergism (ESTD) model, we analyzed the spatial and temporal variations of five ecosystem services (habitat quality, carbon storage, soil conservation, water conservation, and water purification), as well as their trade-off and synergistic relationships at the township scale from 2000 to 2020. The results showed that habitat quality, carbon storage, and nitrogen and phosphorus output decreased as a whole from 2000 to 2020, and soil conservation and water purification increased. Habitat quality showed a distribution pattern of high in the north and low in the south, and carbon sto-rage, nitrogen and phosphorus output, soil conservation and water purification showed a pattern of low in the north and high in the south. During the study period, synergistic relationships among the five ecosystem services were predominant in both time cross-section and time period, but there were still differences, with synergistic relationships mainly between carbon storage and other services in time cross-section, and between habitat quality and other ser-vices in time period. Our results can provide theoretical guidance and practical reference for the enhancement of ecosystem services and the zoning of ecosystem functions, as well as basic support for the optimization of spatial patterns of national territory.