Urban Land Expansion Research Articles

Identification of the critical factors in flood vulnerability assessment based on an improved DEMATEL method under uncertain environments

With accelerated urbanization, the expansion of urban construction land and the increase in concrete pavement have led to a continuous decline in the natural permeability of the urban surface. This makes it difficult for rainwater in urban areas to infiltrate quickly into the ground, which may lead to urban flooding disasters in cases of heavy rainfall. In recent years, the frequency of urban flooding disasters has been increasing, posing a great safety threat to communities and residents as well as property damage. Therefore, it is important to build a scientific and reasonable community flooding vulnerability assessment system to improve the community emergency response capacity and reduce the losses caused by flooding disasters. In this paper, 94 indicators for community flooding vulnerability assessment are collected by combining literature research and field surveys. The newly proposed fuzzy language expression method based on pentagonal fuzzy numbers (PFN) and the proportional two-tuple linguistic representation (P2TLR) are used as the first step of indicator evaluation and screening, and PFN-P2TLR with the two-step DEMATEL method are combined as the second step of indicator screening. Finally, 23 representative evaluation indicators belonging to the dependent variable are selected. Following a thorough investigation, it was found that “resident characteristics”, “regional economic strength”, “community precipitation status” and “institutional soundness” are the four most influential factors for community resilience to flooding, and these indicators have a significant impact on other indicators. The research results provide a reliable basis and specific guidance suggestions for community flooding vulnerability assessment, which is crucial for further reducing the occurrence of flooding disasters and mitigating the social and economic losses caused by them.

Study on the Spatial and Temporal Evolution of Regional Green Space Morphology Outside Built-Up Areas based on the Google Earth Engine and Biophysical Component Modeling

The spatial pattern of regional green space is an important dimension to describe and quantitatively express the characteristics of regional green spaces outside the built-up area of a city. With the expansion of urban and rural construction land, regional green space has been continuously encroached upon. This leads to a decline in regional ecological well-being and the loss of biodiversity. Based on the remote sensing data of Shanghai city from 2000 to 2020, we quantitatively studied the spatial morphological change characteristics of regional green space outside the built-up area of Shanghai city. Firstly, with the help of the GEE platform, the optimal decoding accuracy classification method was selected through machine learning (random forest, support vector machine, classification regression tree); then, based on the biophysical component (BCI) and CA binarization, the built-up area ranges for up to five time nodes were obtained; finally, through GIS spatial data analysis and processing technology, the regional green space dynamic data of Shanghai for five time nodes were extracted. Based on the above data, an analysis index system was constructed to quantitatively analyze the spatial morphology characteristics of the regional green space outside the built-up area of Shanghai. The results show that (1) the area of regional green space outside the built-up area of Shanghai had a fluctuating growth pattern of “decreasing and then increasing”. The arable land and water areas in Shanghai decreased, and the woodland area increased steadily, while the wetland and grassland areas showed a trend of first decreasing and then increasing. (2) The regional green patch fragmentation shows a fluctuating development trend of increasing, decreasing, and increasing. (3) The change in the spatial center of gravity of the regional green space in Shanghai had a high degree of consistency with the overall green space change. The center of gravity of the grasslands in the regional green space moved substantially to the northwest, while the center of gravity of the other types remained basically unchanged. This study reveals the spatial morphology characteristics of regional green spaces and provides a research method to study the dynamic changes in regional ecological resources. The results of this study can provide a scientific basis for the identification, protection, and development of regional ecological resources.

M-AFDE-NET: NOVEL DEEP LEARNING-BASED BUILDING CHANGE DETECTION OF FRESHLY BUILT LOCALES FROM SATELLITE IMAGERY IN THE NILE VALLEY, EGYPT

Abstract. Urban land expansion is a defining characteristic of urbanization, necessitating the monitoring of this phenomenon and the detection of changes to promote sustainable land use and contribute to updating geospatial databases. Methods based on detecting changes in high-resolution satellite imagery have shown poor performance due to downsampling during image processing, resulting in the loss of boundary information. Furthermore, these methods struggle with complex backgrounds where the ground resembles building roofs. This paper delves into the investigation and evaluation of Freshly Built Locales (FBLs) using bi-temporal images through recently proposed computer vision networks. To address the limitations of existing approaches, we have introduced modifications to the AFDE-Net model, which include the novel residual pyramid attention fusion (RPAF) module. This enhancement enables more precise identification of intricate details in complex change detection scenarios. Our proposed model, M-AFDE-Net, has been evaluated on a newly captured dataset from the Nile Valley regions of Egypt, with a spatial resolution of 30 cm. Special attention has been given to New Mansoura and New Tiba as focal areas for analysis. The evaluation results reveal that the modified model, M-AFDE-Net, outperforms other state-of-the-art models in detecting FBLs. It achieves an impressive F1-score of approximately 89.2%, demonstrating its superiority and effectiveness.

Study on Spatial and Temporal Characteristics of Construction Land Expansion in Hohhot City Center, 1992-2022

Based on CLCD LULC data, this paper uses the ArcGIS 10.8 platform to analyze spatial data and discusses the expansion rate, expansion intensity, expansion direction, expansion type, and land use structure changes of construction land in Hohhot. The results show that the construction land area of Hohhot increased from 103.02 square kilometers in 1992 to 343.41 square kilometers in 2022, with an average annual expansion rate of 7.75 square kilometers and an expansion intensity index of 7.53. The city's expansion shows a staged character, with 2002 to 2012 as the period of rapid expansion. The direction of expansion is mainly concentrated in the northeast, southeast, east, and southwest directions, which is closely related to the city's economic development, natural conditions, and planning control. In terms of expansion types, infill expansion has dominated from 1992 to 2002, while marginal expansion has dominated from 2002 to 2012 and from 2012 to 2022. The land use structure has changed significantly, with a significant decrease in the area of arable land and grassland, a continuous increase in the area of construction land, and a slight increase in the area of forested land. During the 30 years, 242.51 square kilometers of land of various types have been converted into construction land, with arable land being the most converted, accounting for 71.51% of the total amount of converted land. The study concludes that urban land expansion in Hohhot is characterized by obvious spatial and temporal differences and phases, and strict land management methods need to be implemented to ensure the rationality and sustainability of land use. At the same time, arable land and the ecological environment damaged by urban expansion should be protected and restored through ecological compensation mechanisms.

Urban Land Expansion Simulation Considering the Increasing versus Decreasing Balance Policy: A Case Study in Fenghua, China

Under the political dominance of urbanization, the policy of increasing versus decreasing balance (IVDB) between urban and rural construction land has had a profound influence on urban land expansion in China. The purpose of this study is to reveal the impact of the IVDB policy on the process of urban land expansion. Considering the transition process among different land use types under the IVDB policy, this study proposes two situations of urban land expansion. A future land use simulation (FLUS) model is applied to simulate the expansion process over three steps. A case study of Fenghua District in Ningbo City, China, shows the following: (1) In the first situation of village land directly transformed into urban land, the transformation is concentrated in the northern and western parts of Fenghua District. The expansion trends are particularly pronounced along existing urban land and main traffic lines. (2) In the second situation of village land reclamation for agricultural land and urban land occupation for agricultural land, the spatial differences in village land conversion to arable land or other agricultural land are relatively small, and the degree of concentration of arable land is significantly increased after reclamation. Urban land expansion mainly occurs close to Ningbo City. With the help of transfer quotas “produced” by other areas, expansion land can be balanced within Fenghua District. This research helps to shed light on the urban land use growth process and provides beneficial insights for stock spatial planning in China.

How does urban land use efficiency improve resource and environment carrying capacity?

Considering the constraints on urban land expansion, improving the efficiency of existing urban land becomes a key factor in promoting resource sustainability and environmental protection. This paper examines the impact mechanism and threshold effect of urban land use efficiency (ULUE) on resources and environment carrying capacity (RECC) using panel data covering 282 Chinese cities from 2007 to 2018. The empirical results show that: (1) ULUE enhances RECC in China, and the rationalization and advancement of industrial structure are important transmission mechanisms; (2) The impact of ULUE on RECC is heterogeneous, showing significant differences in different regions, periods, administrative levels, and resource endowments; (3) With industrial rationalization and industrial advancement as threshold variables, ULUE exhibits a “gradient-style” enhancement with significant threshold characteristics in improving RECC. These findings can provide practical guidance for various land policies.

Spatial and temporal inequity of urban land use efficiency in China: A perspective of dynamic expansion

In the face of conflicting land-resource supply and demand, land-use efficiency is critical for sustainable urbanization. In this study, we unified the consistent boundaries of land, population, and economic development, identified urban expansion patterns (infilling, edge expansion and leapfrogging), and precisely estimated urban land-use efficiency (ULUE) in 260 Chinese cities from the perspective of dynamic expansion during 2000–2015. With the consideration of the dynamics of outward expansion and internal development of urban land, the results showed that China's main expansion pattern gradually shifted from edge expansion with lower ULUEs to infilling with higher ULUEs. Over the 15-year period, ULUEs in all expansion areas increased from 0.065–0.18 to 0.093–0.31. Inequity remained significant in terms of expansion patterns, built-up layers, regions and urban sizes. ULUE increased more quickly in the super-large cities of the central and western regions, whereas it increased more slowly in the northeast and even decreased in expansion built-up area formed during 2005–2010 (EBUA (2005–2010)). Importantly, ULUE decreased in most cities with edge expansion. Based on the findings, we concluded that the urbanization of China was progressing toward sustainability but still had room for improvement, and we suggested that policymakers should pay more attention to the complex, systemic nature of urban development.

Projecting spatial interactions between global population and land use changes in the 21st century

Previous research on global urban land expansion has primarily focused on accommodating the growing population without adequately considering the trade-offs between urban land and ecological services. Consequently, it is important to investigate the effect of this expansion on the ecological service system, while also examining the potential trade-offs between population growth and available urban land. Here, we quantify how different global land expansion options contribute to reconciling global population changes and to compliance with the UN Sustainable Development Goal 11 on sustainable cities and human settlements. Using an integrated framework for projecting global land consumption with the trade-off strategy between global land expansion and population under shared socioeconomic pathways (SSPs), we aim to bridge the knowledge gap in this area. The results of our study suggest that implementing a trade-off strategy between global land expansion and population growth can successfully reduce the levels of global land consumption in the future. Under the SSP1 scenario, for instance, our findings indicate that implementing trade-off policies can significantly reduce land consumption while increasing carbon sinks and protecting the global ecological service system. Specifically, converting land to forest or grassland can help decrease land consumption by 8.07% by the end of the 21st century. These insights can be valuable in designing land use policies that incorporate data-based solutions and address the challenges of sustainable urban development while also accommodating population growth.

Integrating a heatscape index and a Patch CA model to predict land surface temperature under multiple scenarios of landscape composition and configuration

Effectively predicting and mitigating urban heat island (UHI) through regulation of urban landscape patterns remains a global challenge. This paper introduces a new framework for predicting land surface temperatures (LST). We introduce a heatscape index (SCSS) to establish a relationship between landscape patterns and LST within spatial grids. Furthermore, the framework employs an urban CA model, equipped with a sophisticated patch generation engine, to forecast urban landscapes under multiple scenarios. LST under these scenarios is then calculated based on the established regression relationship. Application of the framework in Wuhan yields valuable insights: (1) The regression coefficient (R2 = 0.85) between SCSS and LST indicates that changes in SCSS can well explain the spatial heterogeneity in LST, especially in areas with evident UHI effects. (2) The simulated and retrieved LST for 2015 shows high spatial consistency, achieving an R2 value of 0.81, indicating the model's credibility. (3) Scenario simulations demonstrate that rapid and compact urban land expansion would exacerbate the UHI effect, leading to extreme high-temperature areas expanding towards suburban regions and significant temperature increases in urban fringe areas. The proposed framework provides powerful tools for policymakers and urban planners to mitigate the UHI effect and enhance urban sustainability.

Substantial increase in future fluvial flood risk projected in China’s major urban agglomerations

Urban land will face high fluvial flood risk against the background of climate change and urban expansion. The effect of urban spatial expansion, instead of densification of assets within existing urban cells, on flood risk has rarely been reported. Here, we project the future flood risk of seven urban agglomerations in China, home to over 750 million people. The inundated urban land areas in the future are projected to be 4 to 19 times that at present. Without considering the urban spatial expansion, the inundated urban land areas will be underestimated by 10-50%. Urban land is more likely to be inundated than non-urban land, and the newly-developed urban land will be inundated more easily than the historical urban land. The results demonstrate the urgency of integrating climate change mitigation, reasonable urban land expansion, and increased flood protection levels to minimize the flood risk in urban land.

Spatiotemporal Distribution Characteristics and Multi-Factor Analysis of Near-Surface PM2.5 Concentration in Local-Scale Urban Areas

Near-surface PM2.5 concentrations have been greatly exacerbated by urban land expansion and dense urban traffic. This study aims to clarify the effects of multiple factors on near-surface PM2.5 concentrations from three perspectives of background climatic variables, urban morphology variables, and traffic-related emission intensity. First, two case areas covering multiple local blocks were selected to conduct mobile measurements under different climatic conditions. The observed meteorological parameters and PM2.5 concentration were obtained through GIS-based imaging. These interpolation results of air temperature and relative humidity reveal highly spatiotemporal diversity, which is greatly influenced by artificial heat emissions and spatial morphology characteristics in local areas. The PM2.5 concentration on measurement days also varies considerably from the lowest value of 44~56 μg/m3 in October to about 500 μg/m3 in December in Harbin winter and ranges between about 5 μg/m3 and 50 μg/m3 in Guangzhou summer. The correlation analysis reveals that both the climatic conditions and urban morphology characteristics are significantly correlated with local PM2.5 concentration. Especially for Guangzhou summer, the PM2.5 concentration was positively correlated with the street traffic emission source intensity with correlation coefficient reaching about 0.79. Multivariate nonlinear formulas were applied to fit the association between these factors and PM2.5 concentration with higher determined coefficients. And optimization strategies are thus suggested to improve the urban air quality in local-scale areas. This attribution analysis contributes to environmentally friendly urban construction.

High-carbon expansion or low-carbon intensive and mixed land-use? Recent observations from megacities in developing countries: A case study of Shanghai, China

Cities have become significant sources of greenhouse gas emissions. Effective land management may be the solution to carbon neutrality targets for megacities with limited land resources. This paper takes Shanghai as a case study to investigate the regional land use dynamics and its impact on carbon emissions following the implementation of land conservation and intensive use policy. During 2010–2020, the land use pattern in Shanghai changed from the previous urban land expansion to a combination of industrial land reduction and woodland expansion. Meanwhile, the area proportion of land-use mixture grids increased from 90.50% to 92.28% with the spatial pattern of mixed types also changing. Furthermore, the notable land-use mixture does not necessarily lead to carbon emission reduction, but it can reduce carbon emission hotspots in industrial agglomerations by promoting the mixed use of industrial land and other land use types. However, megacities cannot achieve carbon balance through land use management alone. Due to the increasing carbon emission density of hybrid industrial land, the joint implementation of a land conservation and intensive use strategy with industrial and energy structure adjustments may be an effective way forward.

The expansion efficiency of urban land in China's urban agglomerations and its impact on ecosystem services

Analyzing the impact of urban land expansion efficiency (ULEE) on ecosystem services (ESs) is crucial to constructing high-quality territorial spatial patterns within urban agglomerations (UAs). While numerous studies have investigated the coercion and disturbance of urban sprawl on the ecological environment, research examining the impact of urban sprawl from an efficiency perspective remains relatively rare. In this study, ten UAs of different levels of development in China are selected as the research objects, and prefecture-level cities are used as the primary research units. CO2 emissions are included as undesired outputs in the measurement and research framework of expansion efficiency to reflect the vision and requirements of emission reduction and carbon neutrality. At the same time, the Spatial Durbin Model (SDM) is used to reveal the impact of ULEE on ESs in years 2005–2021. The main results are as follows: (1) The ULEE within the entire UAs areas exhibited a fluctuating trend across different periods. Efficiency variations were evident among UAs with different development levels. Spatially, the UAs in the central region showed relatively low ULEE, while the northwest and southeast UAs displayed relatively high ULEE. Besides, the expansion efficiency of core cities in each UA exceeded that of surrounding cities. (2) The ecosystem service value (ESV) within the ten UAs demonstrated a consistent downward trend. In terms of the rate of ESV decline among UAs with varying developmental levels, breeding UAs exhibited the most rapid decline, followed by growing UAs, while mature UAs experienced the slowest decline. (3) Over the study period, the ULEE in UA areas positively contributed to enhancing ESs, with varying effects observed across different time frames. Natural factors directly influenced ES changes, thereby affecting both ULEE and Es dynamics. In contrast, changes in social factors indirectly caused changes in ESs. This study underscores the importance of a comprehensive assessment of ULEE and ESs to provide a scientific reference for formulating high-quality social and economic development and territorial spatial planning.

CLIMATE VARIABILITY IN RELATION TO LAND USE AND LAND COVER (LULC) CHANGES IN KOTA BHARU, KELANTAN, MALAYSIA

The process of rapid urbanization has significantly altered natural landscapes and contributed to climate variability. Due to urbanization, land surface characteristics are changing, resulting in a changing thermal climate making cities warmer than surrounding rural areas. The study utilized remote sensing and Geographic Information System (GIS) technologies to analyze the connection between land use and land cover (LULC) change and climatic variability in Kota Bharu, Kelantan, Malaysia. The outcome showed that the greatest LULC change resulted from converting vegetation and bare land into built-up areas, with 25.46% and 10.17% respectively. This represents the rapid expansion of urban land caused by population growth. LST increment averaged 3.65°C in the last decade due to this massive increase in built-up areas. A linear regression analysis between LST and LULC indices, NDBI and NDVI shows that they are positively correlated. By understanding these two variables, land use planning could be further improved, hence, reducing the city's vulnerability towards climate variability.

A Comparative Analysis of the Interaction between Urban-Rural Construction Land Transition and Population Flow: Dominant and Recessive Perspectives

Population flow caused by rapid urbanization has driven the urban-rural construction land transition. A systematic recognition of their interaction is essential for achieving coordinated and sustainable urban-rural development. We chose Hangzhou, one of the most urbanized cities in China, as the study area to analyze this interaction from the perspectives of dominant morphology and recessive morphology during the period of 2010 to 2020. From the perspective of dominant morphology, a structured analysis method is applied to assess the variation in the internal components. A dynamic land utilization efficiency index is proposed and combined with an original static land utilization efficiency index to comprehensively portray a complete periodicity of urban-rural construction land transition and population flow from the perspective of recessive morphology. Results demonstrate that the path dependence of rural industrialization leads to a seemingly stagnant urban-rural construction land transition in Hangzhou. Meanwhile, the rapid increase in the demographic urbanization rate has been supported by the massive inflow of external migrants. Based on the more stringent dynamic land utilization efficiency index and the more comprehensive combination of static and dynamic indices, the moderate expansion of urban construction land increases the proportion of township-level units of the intensive land utilization pattern while, instead of population loss, the general non-intensive land utilization pattern in rural areas has been driven by the overexpansion of rural residential land.

Simulating the impact of urban expansion on ecosystem services in Chinese urban agglomerations: A multi-scenario perspective

Urban agglomerations (UAs) are the most active areas of urban land expansion. The encroachment of urban land on large-scale ecological land has caused severe ecological problems and threatens the ecological sustainability of UAs. Understanding the characteristics of multi-scenario urban land expansion and its impacts on ecosystem services (ESs) in UAs can provide guidance for formulating ecologically sustainable management and control policies in UAs. However, few studies have simulated the characteristics of multi-scenario urban expansion and determined its impacts on ESs in Chinese UAs. In this study, we used a patch-generating land use simulation (PLUS) model and the benefit transfer method to conduct a multi-scenario simulation of urban land expansion in Chinese UAs in 2030 and measure its impacts on ESs. The simulation indicates that urban land continued to expand and expanded most severely under an urban development scenario. In the future, under an ecological protection scenario, ESs would be maintained at their highest levels. In general, the global Moran's I indices of the ESs and urban expansion were negative at the 0.001 significance level, indicating that ESs and urban expansion in Chinese UAs were strongly spatially concentrated. The impacts of urban expansion on the ESs varied among the UAs. In national and regional UAs, ESs were affected negatively by patch density (PD) and percentage of like adjacencies (PLADJ), whereas the loss of ESs in local UAs was not only affected by PD and PLADJ, but also by the proportion of urban land. These findings provide effective guidance for improving ESs, urban development planning, and high-quality development in Chinese UAs.

Simulating the dynamics of urban land quantity in China from 2020 to 2070 under the Shared Socioeconomic Pathways

Rapid expansion of urban land areas in the past few decades has exerted great pressure on regional environment, and simulating urban land dynamics is of great significance for sustainable urban development. However, the differences in driving forces of urban land among cities were not fully considered in previous simulations. Here, we adopted a data-driven approach combined with Monte Carlo method to simulate future urban land quantity in China at the city scale under the Shared Socioeconomic Pathways (SSPs). The results show that the total urban land area of China will reach 154,105 to 289,932 km2 by 2070 under different scenarios, 1.8 to 3.4 times that of 2020. Compared with the traditional methods at the national or regional scale, the clustering method used to classify urban land expansion types can better fit the urban land change of each city. Meanwhile, the iterative simuation of future urban land quantity can depict the slowing down trend of urban land expansion. This study provides the amount of urban land from 2020 to 2070 at the city scale, confirming a close relationship between urban development and selection of urbanization pathway. Choosing a more sustainable path of social and economic development is conducive to restraining the rapid expansion of urban land in China. It is particularly important to formulate city-specific sustainable development strategies according to the trend of urban land dynamics over time.

Simulation and analysis of ecological early-warning of urban construction land expansion based on digital sensing feature recognition and remote sensing spatial analysis technology

To improve the analysis effect of the simulation and prediction of the expansion effect of urban construction land, this paper combines the digital sensing feature recognition and remote sensing analysis technology for the earth's surface, and uses Artificial-neural-network-based cellular automaton (ANN-CA) Markov model and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to study and analyze the expansion effect and trend of urban construction land, and subdivides the spatial and temporal characteristics of land cover. In addition to that, multi-based sensing data is used to generate urban construction land expansion effect drivers. The multi-source sensing data and InVEST model are used to conduct spatial information analysis and ecological early-warning. The research shows that combining digital sensing feature identification and remote sensing analysis technology, using the analysis model of ANN-CA-Markov model and InVEST model can effectively improve the analysis effect of urban construction land expansion effect prediction, and carry out ecological early-warning of construction land expansion on this basis. Overall territorial spatial planning stage of Xuzhou city, the designated ecological space area accounts for 20% of the whole land area. There is a sharp contradiction between constructive land expansion and ecological security in the whole region, so it is appropriate to conduct precise intervention and efficient management of constructive land expansion according to ecological early-warning.

Study on the Characteristics and Influencing Factors of Land Use Changes in the Metropolitan Fringe Area: The Case of Shenzhen Metropolitan Area in China

With the development of the regional economy, the metropolitan area has gradually shifted from the rapid development stage of concentrating on the central city to the stage of coordinated and integrated regional development. This trend has brought new development opportunities to the metropolitan fringe area; however, due to the differences in resource endowment and the complex relationship between different levels of government, the metropolitan fringe area inevitably has contradictions and imbalances in economic and social development. There has been extensive research on land use and urban governance in the metropolitan area, but less attention has been paid to the metropolitan fringe area, and it is difficult to quantitatively characterize the complex interactions between various forces in this area. This paper summarizes the spatial pattern and spatiotemporal characteristics of construction land use in the fringe area of Shenzhen metropolitan area based on the 30 m resolution land cover dataset from 2000 to 2020, and analyzes the driving factors affecting the changes of construction land use through logistic regression. The results show that the overall land use in the study area is shifting from cropland and forest land to urban and rural construction land. With different stages of development, the rate of land change varies greatly from one period to another. Three factors, population density, lighting index and distance to highway, have a significant correlation with the changes in built-up land across the region, while the boundary effects of administrative boundaries show some variation in the impact of urban land expansion at different economic levels. Finally, we put forward that reducing the negative impact of administrative divisions on the integration of resources in different cities is important for realizing the synergistic development of the Shenzhen metropolitan area.

Exploring the urban–rural gradient effects of construction land expansion processes on land use function trade‐off/synergy in rapidly urbanizing areas

AbstractConstruction land expansion greatly affects the supply and interaction of distinct land use functions, particularly in rapidly urbanizing areas. However, existing research rarely focuses on the urban–rural gradient role of different construction land expansion processes in affecting the interactions between land use functions, which limits the refined high‐quality development of territorial space. Using the main urban area of Hangzhou as an example, this research analyzed the spatiotemporal transmission process of trade‐offs/synergies among distinct functions between urban and rural regions from the living‐production‐ecological function perspective, and probed the differences in the impact of distinct urban and rural construction land expansion processes on them across different urban–rural gradients, thereby proposing the urban–rural spatial development pathways for promoting synergistic territorial spatial patterns. The results showed that the changes in different functions had an obvious urban–rural gradient difference. During 2000–2020, the trade‐off between living function and other functions increased continuously, and regions with a higher trade‐off primarily shifted from urban development areas to urban–rural transition areas. The infilling and edge‐expansion of urban construction land were more favorable to the increased synergy between distinct functions; the infilling and edge‐expansion of rural construction land in urban development and urban–rural transition areas greatly reduced the functional trade‐off level, while its leapfrogging in rural development areas strongly affected the synergy between distinct functions. These findings can help to restrict unreasonable urban and rural construction land expansion processes as well as promote synergistic territorial space patterns in rapidly urbanizing regions.