Sprawl Index Research Articles

Detection of Urban Growth in Taiz City, Yemen, Between 1981 and 2022 by Using Google Earth™ and Geographical Information System Data

Rapid urbanization brought serious socio-economic and environmental problems in many cities around the world, particularly in developing countries like Yemen. Urban "sprawl", a synonym of rapid and unplanned urban growth, is considered an obstacle for sustainable development, which causes serious long- and short-term problems, such as extreme infrastructure expenses, economic inefficiency, environmental destruction, and social instability. This is the case of Taiz City, the third largest city in Yemen, which is facing a huge challenge to manage the spatial extension of its built-up area at the expense of the reduction of natural resources and environment. This study aims to investigate urban growth process in Taiz City, focusing on urban sprawl and agricultural land-use change during 1981–2022. The data used are high resolution geospatial data, which are the topographic map for 1981 and Google Earth (GE) images for 2003, 2012, and 2022. The methodology adopted was manual digitizing using Geographic Information System (GIS) software to extract urban land use features from the images of the different dates. Four land-use maps were produced and used for calculation the urban sprawl and land-use changes. The urban expansion rate and patterns were also identified in three phases: 1981–2003, 2003–2012, and 2012–2022. The results show that the built-up area increased six times from 6.2 km2 in 1981 to 34 km2 in 2022, while the agriculture area decreased by 77% from 18 km2 in 1981 to 4.2 km2 in 2022. The urban sprawl in Taiz covered about 75% of its municipal area and extended to the agricultural and rural areas. The sprawl index (USI) is measured to be 5.4%, indicating a high degree of sprawl in Taiz. There is no open space left for future development, and the water resources are at risk of population and depletion. The study demonstrated that informal and haphazard expansion must be controlled, a development strategy should be prepared, so that sustainable urban growth can be achieved. The results of this study could be used as a decision support tool for urban management activities. The vector layers produced by this study could provide the required input data for the future urban modeling of the city.

Spatiotemporal dynamics of urban sprawl in China from 2000 to 2020

ABSTRACT Accurately and timely quantifying the dynamics of urban sprawl is essential for improving land use efficiency and land use planning. However, existing research mainly focused on the sprawl of a single city or urban agglomerations in China, while national scale studies mainly used short-term remote sensing data to quantify urban sprawl. Therefore, we still lack a long term and most up-to-date understanding of urban sprawl in China, especially in different regions, cities of different sizes. Here, we quantified the spatiotemporal dynamics of urban sprawl using urban sprawl index (USI) based on the latest population census, and analyzed its driving force in China during 2000 ~ 2020 using the optimal parameters-based geographical detector. The results showed that in the past two decades, Chinese cities were still experiencing urban sprawl, with an average USI of 3.04, indicating that the average annual growth rate of urban lands was 3.04% higher than that of the urban population. Overall, the sprawl showed a slowdown, with the USI dropping from 3.55 in 2000 ~ 2010 to 2.53 in 2010 ~ 2020. Among regions, urban sprawl was more severe in the western region, where the USI was 5.33 during 2000 ~ 2020 and 89.3% of the cities exceeded the national average sprawl speed. Recently, the driving force of transportation on urban sprawl substantially increased. In the future, the Territorial Spatial Planning should pay attention to confining excessive sprawl of small- and medium-sized cities in the western region of China.

Does urban sprawl lead to carbon emission growth? ——Empirical evidence based on the perspective of local land transfer in China

The rapid expansion of urban areas has caused a series of impacts on the ecological environment. Exploring the effects of urban sprawl on carbon emissions and its mechanisms is crucial for realizing sustainable development patterns and low-carbon city planning. This study integrates used nighttime light data and population grid data to construct an Urban Sprawl Index. It employs a spatial Durbin model to analyze the spatial impact of urban sprawl on carbon emissions, examining the mechanisms from the perspective of local land transfers. The research reveals the following findings: (1) Urban sprawl significantly contributes to a positive spatial spillover effect on carbon emissions, leading to increased emission levels in surrounding cities. (2) The overall local impact of urban sprawl on urban areas is not significant. It suppresses carbon emissions in municipal districts but increases them in counties, with these effects counterbalancing each other. (3) Mechanism analysis indicates that different types of land transfers have varied effects on carbon emissions in districts and counties, and the regulation of the floor area ratio regulation strengthens the impact of land transfers. (4) Heterogeneity analysis shows that the size of urban populations significantly reduces the local effects of sprawl on carbon emissions, while environmental regulations strength attenuate the impact of urban sprawl on carbon emissions in municipal districts. The findings of this study provide practical references and policy implications for formulating reasonable urban development and land use plans, facilitating the achievement of peak carbon and carbon neutrality goals.

Landscape Analysis and Ecological Risk Assessment during 1995–2020 Based on Land Utilization/Land Coverage (LULC) and Random Forest: A Case Study of the Fushun Open-Pit Coal Area in Liaoning, China

China’s Fushun open-pit mine is the largest century-old coal mine in Asia. Large-scale mining and the use of coal has caused dramatic changes in the regional urban landscape pattern, seriously affecting the ecological function and ecosystem stability of its surrounding landscape. Evaluating the ecological risks of the landscape in the urban areas of open-pit mines contributes to the risk management of regional ecosystems and the sustainable development of society. This study selected six-phase Landsat ETM/OLI remote sensing images from 1995 to 2020 and combined them with the random forest model to carry out an LULC classification of the open-pit mine and its surrounding areas and, on this basis, discusses the evolution of its landscape pattern and evaluates the ecological risks. It fills the gap in the research on the evolution of regional landscape patterns and ecological risks in the study area and improves the automatic classification efficiency of LULC for use in open-pit mines. The results show that the classification accuracy of LULC regarding open-pit mines based on image pixels and the random forest model can reach 30 m, and the rate of accuracy can reach 92–97%. From 1995 to 2020, the coverage area of forest land and building land in the study area has increased and is mainly composed of grassland and undeveloped land. The use of land was transferred to the mining area, the water body area maintained a relative dynamic balance, and the overall vegetation coverage of the mining area was greatly improved; the forest land began to expand from the surrounding area to the mining area in 2010, and the construction land began to move from the areas surrounding the mining area to the surrounding valleys in 2015. The landforms have extended radially, and the landscape sprawl index has increased, indicating the optimization of the ecological environment; the high- and medium-risk areas decreased by 75.51 km2, the low-risk areas expanded by 461.48 km2, and the overall ecological risk index decreased. From this, it is possible to conclude that the landscape restoration project adopted in the study area has achieved great results, and the improvement of the ecological environment also directly affects the increase of construction land. These research results can provide scientific guidance for the rational utilization and sustainable development of land resources in urban areas of open-pit mines.

The effect of city size on the disability rate of the older adults: empirical evidence from CHARLS data.

Exploring the value orientation of city development from the perspective of people's well-being is key to clarifying the current debate on city size strategies. Based on the survey data of the China Health and Retirement Longitudinal Study in two phases, and by using the unbalanced panel-ordered logit model, stepwise analysis method, and KHB method, among others, we discuss the impact of city size on the disability rate of older adults. The study finds that city size significantly and positively affects the activities of daily living (ADL) of older adults, with odd ratios of 1.3286 (95% CI = [1.082243, 1.631089]), and exhibits significant group heterogeneity in terms of age, registered residence, income, and education level. City size has indeed played an mediation role through the health improvement effect, disease mitigation effect, emotional effect, and employment structure optimization effect, with a cumulative contribution rate of the mediation effect of 35.17%. In addition, the urban sprawl index has a significant moderation role. Robust urban sprawl is conducive to promoting the improvement of the regional health environment, the improvement of the medical security policy, the optimization of the family support policy, and the employment structure, thus helping to reduce the disability rate of older adults.

ANALYSING URBAN SPRAWL OF THE MUMBAI METROPOLITAN REGION USING REMOTE SENSING AND SOCIOECONOMIC DATA

Abstract. Urban growth in developing countries like India is happening more than twice as fast as the population increase. Such rapid urban growth has resulted in urban sprawl characterized by low-density scattered development. Urban planners require a timely updated dataset and suitable tools to monitor the urban sprawl and ensure sustainable development. The present study uses Landsat data from 1999, 2009 and 2019 and socioeconomic data to study the urban sprawl characteristic of the Mumbai Metropolitan Region (MMR) over two decades. The analyses show that MMR's built-up areas have expanded from 400 sq. km in 1999 to 761 sq. km in 2019, implying a 90% growth in the past two decades. While most municipal corporations have more than 60% of land covered by built-up areas, municipal councils are less saturated, with <30% built-up covers. With saturated land spaces within municipal corporations, higher growth rates are observed in the municipal councils. Also, the urban growth rates in these municipal councils outpace the population growth rate. The urban sprawl indices computed also suggest a continuous compact development within the municipal corporations while a continued sprawling within these fast-developing municipal councils. Mira Bhayandar is the most compact, while Bhiwandi Special Notified Area is the most sprawled urban area in MMR. The analyses show a clear indication of urban sprawl characteristics of the MMR. Many of these municipal councils are in the initial stages of development and lack appropriate governance to tackle rapid urbanization. Suitable policy measures that result in balanced urban growth can help ensure sustainable development.

The Effects of Urban Sprawl on Electricity Consumption: Empirical Evidence from 283 Prefecture-Level Cities in China

Under the urban development trend of sprawl, improving energy use efficiency is a proper way to promote green and low-carbon construction in cities. This paper uses panel data from 283 prefecture-level and above cities in China from 2008 to 2019 to measure the urban sprawl index, and analyze the spatial-temporal evolution law of urban sprawl and electricity consumption. The relationship between urban sprawl and electricity consumption is empirically examined, and the differential effect of urban sprawl on electricity consumption is analyzed. Finally, the impact of urban sprawl on electricity consumption based on a spatial perspective is explored in depth by establishing a spatial error model. We found the following: (1) The levels of urban sprawl and urban electricity consumption are on the rise. The spatial distribution of urban sprawl is more dispersed, and cities with high electricity consumption levels are mostly concentrated in the eastern coastal areas. (2) Urban sprawl exacerbates electricity consumption, and this conclusion is still robust after a series of robustness tests were conducted and endogeneity issues were taken into account. In terms of the influence mechanism, urban sprawl mainly affects electricity consumption by changing the allocation of land resources, increasing the dependence on private transportation, and inhibiting green technology innovation. (3) The incremental effect of urban sprawl on electricity consumption is more pronounced in cities with high sprawl levels, weak environmental regulations, and low green innovation levels, as well as in west cities. (4) Urban sprawl and electricity consumption both have a significant positive spatial correlation. Electricity consumption of cities is not only related to their own regions but also influenced by the adjacent regions, and the spatial correlation is mainly reflected in the random error term. This paper deepens the understanding of the basic laws of urban sprawl affecting urban low-carbon development, which also has implications for new urbanization strategies and green development.

The Impact of Urban Sprawl on Carbon Emissions from the Perspective of Nighttime Light Remote Sensing: A Case Study in Eastern China

This paper collects the nighttime light data and six control variables of 77 cities in the eastern China region from 2000 to 2020 and analyzes the spatio-temporal changes of urban sprawl and carbon emissions in the eastern China region. Using the baseline regression model, the correlation and influencing factors between urban sprawl and carbon emissions are explored. The results show that although the impact of urban sprawl on carbon emissions in the eastern China region is positive, it is the result of a trade-off of various factors. Different factors have different impacts on carbon emissions, and urban expansion of different city sizes also has different impacts on carbon emissions in the eastern China region. This paper uses nighttime light data to measure the urban sprawl index more finely, directly explores its impact on carbon emissions from the perspective of urban sprawl and conducts an in-depth analysis of multiple external factors and different city types, providing references for decision-makers to construct sustainable low-carbon city development models and low-carbon city planning systems from different dimensions.

The Spatiotemporal Pattern and Driving Mechanism of Urban Sprawl in China’s Counties

Cities in China do not constitute a few global metropolises, but are characterized by heterogeneity. Studying counties can give us a comprehensive picture of urban sprawl in China. This study measured the sprawl index of 1880 counties in China from 2005 to 2020 for the first time and then revealed the evolution of their spatiotemporal characteristics and driving mechanisms. The results revealed the following. (1) China’s counties had a noticeable sprawling trend from 2005 to 2020, and their evolutionary process was characterized by spatiotemporal heterogeneity. (2) From 2005 to 2020, the counties’ sprawl gradually evolved into a spatial distribution pattern of high in the east and low in the west. The spatial distribution of sprawl in county and municipal districts had the characteristics of an interlocking distribution. (3) High–high cluster areas of CSI are mainly distributed in plains, and hilly, basin, and plateau areas tend to be low–low cluster areas. High–low outliers were distributed in a “point–line” pattern along the railroad lines and a cluster pattern near railroad intersections and central cities. Low–high outliers had the trend of encircling the high–high cluster areas. (4) The coefficient of the natural drivers was higher but tended to decrease, while the coefficient of economic and spatial drivers was lower but gradually increased. This study is the first to refine the study of urban sprawl to the county scale, which provides a reference for decision making to optimize the spatial structure of counties and thus promote high-quality development.

The impact of urban sprawl on green total factor productivity: A spatial econometric analysis in China

The rapid expansion of Chinese cities has led to serious urban productivity and eco-environment changes, and has therefore attracted considerable international academic attention. The main objective of this study is to investigate the theoretical mechanisms and practical effects of urban sprawl on green total factor productivity (GTFP), in order to provide a reference for optimizing the spatial layout of cities and promoting high-quality economic development. Realistic urban land area and population characteristics are extracted using DMSP/OLS and NPP/VIIRS nighttime lighting data, and LandScan global population dynamics statistics to measure the urban sprawl index. GTFP is measured using a super-SBM model that considers undesirable output. Based on the panel data of Chinese cities from 2006 to 2020, a spatial Durbin model was constructed to carry out the empirical analysis. The results show that, overall, urban sprawl in China is detrimental to its own GTFP, while contributing to the GTFP of neighboring cities. The impacts of urban sprawl vary markedly across cities of different sizes and across regions.

Unveiling the Regional Differences and Convergence of Urban Sprawl in China, 2006–2019

There is an obvious imbalanced regional development among eastern, central, and western China. This is also a fundamental problem that policy makers and planners need to address. Specific to urban development, we wondered whether there were regional differences in urban sprawl and whether this trend was under control. By using the urban sprawl index (USI), this paper investigated the spatiotemporal pattern of urban sprawl from 2006 to 2019, and its regional difference and convergence among eastern, central, and western China. It finds that the cities with high, medium, and low sprawl in the east and west regions are distributed with a clear geographical pattern, while the distribution in the central region has no intuitive geographical features. Also, the proportion of cities with high sprawl in the eastern region is more than that in the other regions, with low sprawl in central China and medium sprawl in the western region. Moreover, urban sprawl in all three regions showed a downward trend, but this process was fluctuating and had obvious phase characteristics. It can be concluded that there is a convergence trend in urban sprawl in China over the research period, and the club convergence effect exists in the eastern, central, and western regions.

Quantifying the Impact of Urban Sprawl on Green Total Factor Productivity in China: Based on Satellite Observation Data and Spatial Econometric Models

Worsening environmental effects caused by the rapid large-scale urban expansion in most Chinese cities is a worrying trend. In response, China is advocating an economic transition from rapid (raw growth) to a high-quality development model that incorporates negative environmental consequences. Green total factor productivity (GTFP) is regarded as one of the important approaches for measuring high-quality development. Hence, the aim of this research is to quantify the impact of urban sprawl on GTFP using remote sensing data and spatial econometric models. The primary findings of this study are as follows. (1) The urban sprawl index presents a decreasing trend from 2005 to 2016, indicating that urbanization has slowed; (2) The GTFP scores of Chinese cities are not randomly distributed and thus present significant spatial spillovers; and (3) The results of spatial lag models reveal that spatial spillover of GTFP is significant and positive. In other words, increases in GTFP in neighboring cities promotes GTFP improvements in nearby cities. We also find that the impact of urban sprawl on GTFP is significant and negative, indicating that rapid urban expansion is a contributor to decreased GTFP growth in China. Moreover, urban sprawl has a negative effect on technical change and efficiency change. The main findings can provide policy makers in Chinese cities with scientific foundations to design and implement effective measures to improve GTFP.

From an agent-based laboratory to the real world: Effects of “neighborhood” size on urban sprawl

Agent-based models (ABMs) have been established as a valuable research tool in the study of complex human-environment systems. However, it is still challenging to produce generalizable and practical results with ABMs for theory development. We use the case of the effects of “neighborhood” size on urban sprawl to illustrate the practice of generating and testing general conclusions from ABMs. In agent-based urban land-change models, homebuyer agents assess land utilities with a bundle of attributes including the quality of focal or zonal neighborhoods. The size of such neighborhoods, or more precisely the spatial assessment units (SAUs), has significant impacts on simulated urban patterns, yet this sensitivity of modeled impacts has not been validated with empirical evidence. Using an ABM that features markets and competitive bidding, we explored how the neighborhood or SAU size affects urban development patterns under various scenarios of homebuyer preferences, which produced a consistent finding that bigger SAUs tended to generate more sprawled patterns. To bring this finding to the real world, we evaluated relationships in data between sprawl indices in US metropolitan areas and the average sizes of their school districts—one type of real-world SAU in neighborhood delineation and a strong input to homebuyers' assessment of housing quality. While the finding has practical policy implications for urban planning and public education, this case exemplifies a path for simple ABMs to support empirically grounded theory development.

The relationship between the built environment and respiratory health: Evidence from a longitudinal study in Indonesia

Multiple studies have discussed the relationship between the built environment and non-infectious diseases, but research involving infectious diseases and the built environment is scarce. How the built environment is associated with infectious diseases varies across areas, and previous literature produces mixed results. This study investigated the relationship between the built environment and infectious diseases in Indonesia, which has different settings compared to developed countries. We combined the longitudinal panel data, Indonesian Family Life Survey (IFLS), and land cover data to examine the relationship between the built environment and the likelihood of contracting respiratory infectious diseases. We focused on the sprawl index to measure the built environment. The study confirmed that a sprawling neighbourhood is linked to lower respiratory infection symptoms by employing a fixed effect method. The association is more evident in urban areas and for females. The results also suggested that the linkage works through housing quality, such as housing crowdedness and ventilation, and neighbourhood conditions like neighbourhood transportation modes and air pollution levels. Thus, our results underlined the need to consider the health consequences of the densification policy and determine the direction of landscape planning and policy.

Simulation on the Evolution Trend of the Urban Sprawl Spatial Pattern in the Upper Reaches of the Yangtze River, China.

Urban sprawl has become the main pattern of spatial expansion in many large cities in China, and its ecological and environmental effects profoundly impact Chinese urban development. In this paper, nighttime light data and statistical yearbook data are adopted as basic data sources to simulate the evolution trend of the urban sprawl in the upper Yangtze River (UYR), China. First, the urban sprawl index (USI) is employed to assess the level of urban sprawl and to determine the characteristics of urban sprawl under different scales. Second, the spatial autocorrelation model is applied to reveal the spatial pattern change characteristics of urban sprawl from 1992 to 2015. Third, a scenario analysis model of urban sprawl is constructed to simulate the evolution trend of the urban sprawl under different scenarios. Finally, based on the Geodetector, the influence of factors and factor interactions influencing urban sprawl in different time periods is analyzed. The results yield the following main conclusions: (1) The urban sprawl in the UYR first intensifies and then stabilizes over time. The number of cities with high USI in Sichuan province, medium cities, and Chengdu-Chongqing urban agglomeration increases over time, indicating that urban sprawl is intensifying in these areas. (2) The urban sprawl hot spots experience a pattern transformation process of point-like expansion-point-ring expansion-point-axis expansion-axis radiation. (3) Under the scenarios with different scales, the urban land sprawl in large cities is the highest, accounting for more than 47% of the UYR. Urban land sprawl extent in the Chengdu-Chongqing urban agglomeration is the highest, accounting for more than 51% of the UYR. The cities exhibiting the highest sprawl are Chongqing, Lijiang, and Kunming, accounting for 25.84%, 7.37%, and 5.11%, respectively, of the UYR. (4) In the different time scenario simulations, the urban land in large cities exhibits the highest sprawl, accounting for approximately 48.16% of the UYR. The urban land in the Chengdu-Chongqing urban agglomeration demonstrates the highest sprawl, accounting for 50.92% of the UYR. (5) From 1996 to 2002, the driver with the highest influence on urban sprawl was secondary industry share of GDP, with a q-statistic of 0.616. From 2009 to 2015, the driver with the highest influence on urban sprawl was green space per capita with a q-statistic of 0.396.

Spatio-temporal analysis of landscape pattern in water network area of Southern China-- A case study of Shuifumiao Reservoir basin in Hunan Province

Landscape pattern research is the premise of maintaining the stability of ecosystem structure, and is of great significance in guiding the orderly and rational planning of territorial space. In order to deal with the risk of landscape fragmentation of ecological environment in southern hilly region, taking Shuifumiao Reservoir basin of Hunan province as an example, Fragstats landscape pattern analysis software was used to analyze the landscape fragmentation. The patch area, patch number, density index, aggregation index, edge density, patch number, diversity index, evenness index, patch density, aggregation index, and sprawl index of each landscape type were obtained from 2002 to 2018, and the landscape pattern in this region was characterized by fragmentation. Finally, three rationalization landscape pattern optimization strategies were proposed to maintain the stability of regional landscape pattern and alleviate the negative impact of landscape fragmentation.

Suburban sprawl measurement and landscape analysis of cropland and ecological land: A case study of Jiangsu Province, China

AbstractSuburban sprawl occurs when suburban construction exceeds the need for urban–rural development. This phenomenon has garnered considerable attention and criticism due to the outcomes of land resource wastage, environmental pollution, loss of green space, and farmland degradation. However, due to the complexity of suburbs, suburban boundaries remain unclear, which increases the difficulty and uncertainty in the assessment of suburban sprawl. To fill the research gap, this study conducted an empirical study of Jiangsu Province to identify the suburban boundaries in 1998 and 2018 using a logistic‐geographically weighted regression model. By constructing a suburban sprawl index, this study estimates the suburban sprawl at a city scale. This study obtained the following findings: first, from 2000 to 2018, the proportion of suburban areas in Jiangsu increased from 14.36% to 23.29%. Second, the ratio of suburban expansion areas to suburban sprawl areas revealed the efficiency of suburban land use. As results, Nantong had the highest ratio value of 4.49, and Nanjing had the smallest ratio value of 0.58. Finally, this study demonstrated the effects of suburban sprawl on cropland and ecological landscape fragmentation. The present study contributes to a new perspective of identifying suburbs and provides suggestions for cropland and ecological land protection.

Does industrial land sprawl matter in land productivity? A case study of industrial parks of South Korea

Despite an enormous amount of research on the urban sprawl of residential and commercial land uses, little attention has been paid to the negative effects of the sprawl of industrial land development. Furthermore, there is increasing interest in industrial land productivity or efficiency of land use, which is emphasized in terms of preventing sprawl, but so far, there is no clear evidence about the “sprawl–land productivity” relationship.This study aims to understand whether and how industrial park sprawl is associated with land productivity, paying a special attention to a locational factor represented by the “sprawl index.” For methodology, we applied annual sprawl index for 697 industrial parks in South Korea from 2011 to 2020 using a modified gravity model, and conducted a panel regression model to estimate main factors affecting the land productivity of industrial parks. We also conducted specific panel regression models to examine how the influencing factors of land productivity vary by types of industrial parks.The results of the panel regression models indicate that industrial land developments with sprawled locations are negatively associated with land productivity, regardless of the types of industrial park. We also find that the age of industrial park, the designated area, industrial compositions, land sales rate, large metro cities, and the Seoul metropolitan area are positively associated with land productivity, while the number of firms in an industrial park and the distance to transportation services are negatively associated. The study provides a strong basis for improving land use policies to promote land productivity by preventing future sprawl of industrial lands and by facilitating sustainable and regenerative use of the existing industrial parks.

Spatiotemporal Pattern and Driving Factors of Urban Sprawl in China

Urban sprawl is a complex phenomenon related to abnormal urbanization, and it has become a key issue of global concern. This study aimed to measure urban sprawl in China and explore its spatiotemporal patterns and driving factors. Based on 343 Chinese cities at the prefecture level and above, remote sensing-derived data from 2000 to 2017 were used to calculate the urban sprawl index (USI). The evolutionary trend and spatiotemporal pattern of urban sprawl in China were then analyzed using trend analysis and exploratory spatiotemporal data analysis, and Geodetector was applied to investigate the factors driving the changes. The results show the following. ① Moderate or high urban sprawl development occurred in China from 2000 to 2017. In terms of spatial distribution, the USI was high in northwest China and low in southeast China. ② The local spatial stability of the USI gradually decreased from southeast to northwest and northeast. USI had strong spatial dependence. No significant spatiotemporal transitions in urban sprawl were observed, and the spatial pattern was stable with strong spatial cohesion. ③ The gross regional product (GRP) of the tertiary industry, the total GRP, and investment in real estate development have been the most important factors affecting sprawl in cities at the prefecture level and above in China.

Analysis on the Evolution of Rural Settlement Pattern and Its Influencing Factors in China from 1995 to 2015

Since the early 1990s, China has experienced rapid industrialization and urbanization. As cities have expanded rapidly, the spatial patterns of rural settlements also changed significantly. This study uses land use data from satellite imagery interpretation, socioeconomic statistics, and field survey data, together with techniques including landscape pattern analysis, kernel density estimation, and spatial measurement models, to analyze the evolving spatial patterns of rural settlements influencing factors in China from 1995 to 2015. The results indicate the following: First, China’s rural settlements experienced significant changes in the period 1995–2015, as 88.92% of Prefectural-level administrative district units saw an increase in rural settlement area, with total settlement size increasing by 1.35 million hectares, and settlement area sprawl index values can be summarized as “high in the west and low in the east”. Second, in the two-decade study period, the population agglomeration capacity of rural settlements in China continuously weakened, and the shape and structure of rural settlement became more complex and irregular. The scale and scope of the disappearance of rural settlement areas in the northeast and southeast regions was relatively drastic, and the kernel density value of settlements dropped significantly. Third, the increase in rural settlement land area is concentrated in low-altitude and low-slope areas, with a significant tendency to be near water and roads. Fourth, social and economic factors, such as per capita net income of rural residents, the proportion of the population employed in agriculture, the size and structure of the permanent rural population, local fiscal revenue, and urbanization level, are the main factors that cause changes of rural settlement patterns. The results of this study can serve as a reference for promoting regional rural sustainable development policies and advancing rural spatial governance and comprehensive revitalization.