Search Results (58)

The excessive occupation of ecological space (ES) due to city expansion and construction can reduce a variety of natural values and socioeconomic benefits, which would also bring challenges associated with ecological rights and justice between urban areas (with economic impetus) and rural areas (with rich ecological endowments). A more sustainable development mode is required to shift population–industry–land (PIL) allocation from urban-led commensalism (ULC) to PIL interaction by urban–rural mutualism (URM). Thus, an urban–rural integration six-step symbiotic framework (UISS) was built to reflect how the change in urban–rural integration symbiotic mode (the ULC to URM transformation process) can ameliorate socioeconomic inequity in ecological space (IES). Moreover, the two-way fixed-effects model and heterogeneity analysis are used to discuss how the improvement of urban–rural integration symbiotic development level (URI) ameliorates the IES under socioeconomic development to reduce the unfairness, differences between regions, and mismatch of gravity centers from the perspective of spatiotemporal and dynamic changes under various symbiotic environments. The comprehensive multi-perspective analysis of IES based on the symbiotic framework (MEU) was applied to reflect the effect of dynamic PIL interaction changes from ULC mode to URM mode on IES in Yunnan Province, China. The results can be obtained as follows: (1) The URI including symbiotic units of PIL shows a steady rise in growth, with a maximum growth rate of 22.89%, which indicates that the URI has changed from the urban-led commensalism development mode to the urban–rural mutualism development mode. (2) The IES in temporal unfairness has been steadily alleviated, but the spatial differences remain obvious due to the unique symbiotic environment. The dynamic changes in the distance of the gravity centers between ES and PO-IN reflect an increasing mismatch in some regions (e.g., Kunming), while decreasing in others (e.g., Qujing). (3) URI generates a significant symbiotic effect on IES to reduce unfairness, differences, and mismatch, especially through the integration of industrial and population symbiotic units. The heterogeneity analysis shows that a good symbiotic environment, including business environment, industrial structure, transportation conditions, and government size, is conducive to ameliorating IES through the environmental adaptability of symbiotic units. All the results can provide a scientific reference for regional sustainable planning and management under mutualistic population–industry–land interaction between urban and rural areas. Full article

As a precious non-renewable resource, the rational utilization of land resources is crucial for global sustainable development, with urban land development scenario prediction and analysis serving as key methodologies to achieve this goal. Although previous studies have extensively explored urban land expansion simulation and scenario forecasting, further investigation is still required to simultaneously address spatial functional zoning differentiation and urban expansion mode diversity while simulating development trends under various expansion modes. In this study, we integrated major functional zones and ecological redlines to delineate urban spatial functional units and define development coefficients for construction land within each unit. Based on the spatial heterogeneity of expansion modes, the scopes of infill, sprawl, and leapfrog expansion modes were determined. Combining functional zoning and expansion mode zoning, we employed cellular automata model principles to design land conversion rules and simulate the evolution of land use under different expansion modes. Using Jiangyin City, China, as a case study, the model achieved a high simulation accuracy (kappa coefficient of 0.959), significantly outperforming comparative models. By predicting land-use patterns under different expansion scenarios and aligning with Jiangyin’s territorial planning goals, we recommend implementing infill–sprawl–leapfrog and infill–leapfrog–sprawl expansion modes. The results demonstrate that the model effectively supports the refined simulation of urban land expansion, providing a scientific basis for optimizing land resource allocation and balancing ecological protection with urban development. Future research could integrate multiple types of territorial control elements, refine land-use categories, and optimize prediction scenarios to enhance the model’s practicality and applicability. Full article

Urban growth, a pivotal characteristic of economic development, brings many environmental and ecological challenges. Modeling urban growth is essential for understanding its spatial dynamics and projecting future trends, providing insights for effective urban planning and sustainable development. This study aims to assess the spatiotemporal patterns of urban growth and morphological evolution in mainland Shanghai from 2016 to 2060 using the SLEUTH model under multiple growth scenarios based on the Shanghai Urban Master Plan (2017–2035). A comprehensive set of urban growth metrics and quadrant analysis were employed to quantify the magnitude, rate, intensity, and direction of urban growth, as well as morphological evolution, over time. We found that (1) significant urban growth was observed across most scenarios, with the exception of stringent land protection. The most substantial growth occurred prior to 2045 with an obvious north–south disparity, where southern regions demonstrated more pronounced increases in urban land area and urbanization rates. (2) The spatiotemporal patterns of the rate and intensity of urban growth exhibited similar characteristics. The spatial pattern followed a “concave shape” pattern and displayed anisotropic behavior, with the high values for these indicators primarily observed before 2025. (3) The urban form followed a diffusion–coalescence process, with patch areas dominated by the infilling mode and patch numbers dominated by the edge-expansion mode. This resulted in significant alternating urban growth models in the infilling, edge-expansion, and leapfrog modes over time, influenced by varying protection intensities. These findings provide valuable insights for forward-looking urban planning, land use optimization, and the support of sustainable urban development. Full article

Currently, with the acceleration of urbanization, traditional transportation modes are increasingly causing congestion, pollution, and resource waste, drawing widespread attention to Transit-Oriented Development (TOD). TOD is an urban development concept that advocates the implementation of high-density, mixed-use land utilization around transit stations to encourage the use of public transportation, reduce reliance on private vehicles, and achieve more sustainable urban growth. The ‘node–place’ model is a classic analytical framework in TOD typology, forming the foundation for assessing TOD effectiveness. However, this model requires expansion due to its limited adaptability. This study aims to bridge this gap by proposing an innovative, network-based ‘node–place–convenience (NPC)’ model to enhance insights on the overall assessment of metro networks. Using a combination of CRITIC weighting and K-means++ clustering, this study evaluates TOD in cities with metros in the middle reaches of the Yangtze River. By assessing node, place, and convenience values of metro stations, this study compares how different urban structures, population distributions, and metro network configurations impact travel behavior, economic vitality, and regional sustainability. The results show that TOD degree in Wuhan decreases from urban to suburban areas, presenting ‘center to sub-center’ pattern in Changsha, and presenting ‘ring-radial’ distribution across the city center in Nanchang. The clustering results divide TOD benefits into six groups, with Changsha performing the best, followed by Wuhan, while Nanchang still has room for improvement. The average TOD benefits for Wuhan, Changsha, and Nanchang are 0.28, 0.35, and 0.28. Full article

Land use imbalances are a critical driving factor contributing to regional disparities in carbon storage (CS). As a significant component of China’s Yangtze River Economic Belt, Hunan Province has undergone substantial shifts in land use types, resulting in an uneven distribution of ecosystem CS and sequestration capacity. Therefore, within the framework of the “dual carbon” strategy, examining the effects of land use changes driven by regional resource imbalances on CS holds practical importance for advancing regional sustainable development. This study focuses on Hunan Province, utilizing the PLUS-InVEST model to assess the spatiotemporal evolution of CS under land use changes from 1990 to 2020. Additionally, multiple scenario-based development modes were employed to predict county-level CS. The results indicate the following: (1) From 1990 to 2020, Hunan Province experienced continuous urban expansion, with forest land and cultivated land, which are core ecological land types, being converted into construction land. (2) Over these 30 years, the province’s total CS increased by 2.47 × 10⁸ t, with significant spatial differentiation. High-value zones were concentrated in bands along the province’s borders, while lower values were observed in the central and northern regions. The highest CS values were recorded in forested areas at the province’s periphery, whereas the lowest values were observed in the northern water bodies. (3) The scenario-based predictions revealed notable differences, with the ecological protection scenario demonstrating a substantial carbon sink effect. By prioritizing forest and cultivated land, CS could be maximized. This research provides valuable insights for enhancing CS and optimizing land use structures in regions facing resource imbalances. Full article

Accurately assessing and predicting the impacts of land use changes on ecosystem carbon stocks in the Yellow River Basin (YRB) and exploring the optimization of land use structure to increase ecosystem carbon stocks are of great practical significance for China to achieve the goal of “double carbon”. In this study, we used multi-year remote sensing data, meteorological data and statistical data to measure the ecosystem carbon stock in the YRB from 2000 to 2020 based on the InVEST model, and then simulated and measured the ecosystem carbon stock under four different land use scenarios coupled with the FLUS model in 2030. The results show that, from 2000 to 2020, urban expansion in the YRB continued, but woodland and grassland grew more slowly. Carbon stock showed an increasing trend during the first 20 years, with an overall increase of 7.2 megatons, or 0.23%. Simulating the four land use scenarios in 2030, carbon stock will decrease the most under the cropland protection scenario, with a decrease of 17.7 megatons compared with 2020. However, carbon stock increases the most under the ecological protection scenario, with a maximum increase of 9.1 megatons. Furthermore, distinct trends in carbon storage were observed across different regions, with significant increases in the upstream under the natural development scenario, in the midstream under the ecological protection scenario and in the downstream under the cropland protection scenario. We suggest that the upstream should maintain the existing development mode, with ecological protection prioritized in the middle reaches and farmland protection prioritized in the lower reaches. This study provides a scientific basis for the carbon balance, land use structure adjustment and land management decision-making in the YRB. Full article

This study aims to analyze bike-sharing information and related urban factors to promote bike-sharing utilization in Houston, Texas. The research was initiated with a descriptive analysis, where the hourly and daily variations in bike demand are investigated, thereby revealing the time-related patterns of bike tours. The models included data on socio-demographics, public transportation availability, land use patterns, tree canopy coverage, bike routes, and job density within 0.25-mile and 0.5-mile buffer zones around each bike-sharing station. Stepwise regression was utilized to examine the effects of urban factors on bike-sharing ridership, and the explanatory power of the model was enhanced by selecting meaningful variables. The analysis found that tree canopy coverage was a significant factor in influencing bike-sharing ridership. Expansion of tree coverage can help make biking a sustainable mode of transportation. These findings have the potential to guide the development of practical policies that aim to promote sustainable urban mobility through bike-sharing programs. Full article

High-density urban development is promoted by both global and local policies in response to socio-economic and environmental challenges since it increases mobility of different land uses, decreases the need for traveling, encourages the use of more energy-efficient buildings and modes of transportation, and permits the sharing of scarce urban amenities. It is therefore argued that increased density and mixed-use development are expected to deliver positive outcomes in terms of contributing to three pillars (social, economic, and environmental domains) of sustainability in the subject themes. Territorial quality of life (TQL)—initially proposed by the ESPON Programme—is a composite indicator of the socio-economic and environmental well-being and life satisfaction of individuals living in an area. Understanding the role of urban density in TQL can provide an important input for urban planning debates addressing whether compact development can be promoted by referring to potential efficiencies in high-density, mixed land use and sustainable transport provisions. Alternatively, low-density suburban development is preferable due to its benefits of high per capita land use consumption (larger houses) for individual households given lower land prices. There is little empirical evidence on how TQL is shaped by high-density versus low-density urban forms. This paper investigates this topic through providing an approach to spatially map and examine the relationship between TQL, residential expansion, and densification processes in the so-called NUTS2 (nomenclature of terrestrial units for statistics) regions of European Union (EU) member countries. The relative importance of each TQL indicator was determined through the entropy weight method, where these indicators were aggregated through using the subject weights to obtain the overall TQL indicator. The spatial dynamics of TQL were examined and its relationship with residential expansion and densification processes was analysed to uncover whether the former or the latter process is positively associated with the TQL indicator within our study area. From our regression models, the residential expansion index is negatively related to the TQL indicator, implying that high levels of residential expansion can result in a reduction in overall quality of life in the regions if they are not supported by associated infrastructure and facility investments. Full article

Against the backdrop of rapid urbanization, with the expansion of administrative boundaries, some former villages have been transformed from administrative to urban in the sense that they have become special “village-to-city areas”; in this context, the housing pattern, which was previously dominated by self-built houses, is facing many challenges. In particular, the frequent occurrence of safety accidents in self-built houses in the village conversion areas in recent years constitutes an important component of urban spatial vulnerability. However, the ensuing “one-size-fits-all” ban on self-built housing has also raised concerns among scholars. In order to better guide the planning and construction of self-built houses, official safety inspections, planning guidance, and institutional constraints are essential. However, the safety inspection of self-built houses across China is difficult. On the one hand, it is challenging to obtain data on individual buildings (e.g., age, use, building structure ratio, foundation, structural condition, illegal demolition and alteration, and illegal use), and the methods of obtaining such data rely mainly on the basic checking of the safety grids under the responsibility of grassroots safety officers. However, the current organizational system of safety officers is not perfect, and the relevant evaluation training also has limitations. On the other hand, due to the city’s finances, development stage, and other reasons, the agricultural-to-residential areas in the cities of poverty-stricken counties are not likely to be renewed as rapidly as the cities of developed regions but instead may face long-term renewal timelines. Therefore, for the agricultural resettlement areas in the cities of poverty-stricken counties, it is necessary to screen the current problems, systematically study the mechanism and strategy of their renewal based on the management framework of the whole process, and carry out the organic renewal of self-built houses, so as to gradually realize a safe and resilient development mode. This paper establishes a framework for the renewal of self-built houses oriented to security resilience based on the theory of fortress land under the urban form theory of Conzen. Taking Lianhua County as a case study, we analyze the problems and issues related to self-built housing areas through an investigation of the current situation. Then, in response to the existing problems, based on the comprehensive investigation of the safety of self-built houses, we clarify the planning objectives and value orientation and suggest (i) the adoption of hierarchical and classified planning and construction control for the self-built housing areas of villages converted to residences in accordance with the local conditions; (ii) the enhancement of government supervision in the use of self-built houses and the establishment of laws and regulations; and (iii) renewal planning in an orderly manner to enhance the safety resilience of the self-built housing areas. Based on the renewal study of self-built houses in Lianhua County, a systematic exploration of the planning, construction, and governance strategies of self-built houses in China is carried out, which can provide a reference for the decision making of relevant departments. Full article

The 14th Five-Year Plan for China proposes to promote the urbanization process from a county perspective, presenting an unprecedented opportunity to develop county urbanization. However, in the context of relatively limited resources, insufficient funds, and comparatively lower land values in Chinese counties, how to promote county urbanization remains the primary challenge, which has not been studied yet. This study first analyzes the necessity of promoting county urbanization from four dimensions: national development strategy, industrial policy development, local government status, and enterprise development demands using literature research and survey interviews. Based on field research conducted in 32 counties in China, the strengths, weaknesses, opportunities, and threats (SWOT) analysis is carried out on the county urbanization process in this study. By analyzing the developmental status and challenges of major urban areas, expansion areas of counties, and their surrounding countryside, this paper proposes a “three-level gradient integration” concept for the spatial integration of county urbanization. Furthermore, the mechanism of multi-agent linkage to promote county urbanization was explored based on the theory of urban governance and the characteristics of county urbanization. Subsequently, relying on the analysis of policies, such as land acquisition and integrated land improvement, and adopting modes, such as “Investor + Engineering Procurement Construction + Operation” (investor + EPC + O) and renovate–operate–transfer (ROT), we propose a pathway for promoting county urbanization through the linkage of government, enterprises, and residents. This study provides insight into promoting the county urbanization process. Additionally, each country faces the common issue of how to use limited resources to promote regional development, and this article can provide valuable insights and inspiration for addressing this shared issue by the principle of adapting to local conditions and adhering to the concept of efficient market and proactive government. Full article

Mixed land use (MLU) plays a crucial role in fostering a sustainable urban development, vibrant communities, and efficient land utilization, providing a viable solution for smart growth, inclusive public transit, and urban sustainability. This study employs deep neural network (DNN) models: multilayer perceptron (MLP), and long short-term memory (LSTM), to analyze the effect of the transportation infrastructure-based accessibility on the prevalence of MLU patterns, based on the following data: infrastructure-based accessibility measures represented by the logsum (or transport supply), MLU patterns at the parcel level, and floor space prices by space type, for the years 2012 and 2015. Furthermore, the proposed methods are applied to the Jiang’an District of the city of Wuhan, China, at the parcel level as the case study. The study results reveal that MLU is predominantly accessible in areas close to the city center, characterized by a high density, and is relatively scarce on the city outskirts. Notably, parcels exhibiting mixed residential–commercial and residential land-use patterns underwent significant changes between 2012 and 2015, particularly in regions with robust accessibility via non-motorized modes and public transit, specifically in the central and southern parts of Jiang’an District. This transition is evident under scenario 3 (walk, bike, bus, subway) and scenario 6 (walk, bus, car) considered in this study. Furthermore, the study observed a substantial expansion in mixed commercial–residential and commercial districts, significantly near the high-transit accessibility area of subway line 1, as demonstrated in scenario 7 (bike, subway, taxi). The results from the MLP models show a mean relative error (MRE) of 4.7–14.08% for the MLU, and the LSTM models show an MRE of 3.74–10.38% for the MLU. More importantly, both the training and forecasting errors of the above models are lower, in most cases, than those reported in the literature. Moreover, these results indicate that the transportation supply or the infrastructure-based accessibility (represented by logsum) significantly influences MLU patterns. Full article

Floods are natural disasters that cause damage, loss of life, and economic problems throughout the world. Part of these losses can be minimized with the help of different methodologies and tools used to prepare simulations, analyses, and data monitoring to predict such phenomena in time. The metropolitan area of Cluj-Napoca, Romania, is the study area of this paper and it is located in Floresti, the largest rural settlement in Romania. In this area, changes in urbanization, land use, and the expansion of urban areas in a chaotic mode represent a problem. This study focuses on an area prone to flooding due to its proximity to the Somes River. Previous events of this type have caused economic losses that must be considered. This approach combines photogrammetric methods for obtaining data from the field with topographical methods for establishing control points and GIS methods for data processing, modeling, and simulation to obtain the necessary data for flood prevention and intervention. Full article

Land use intensity (LUI) reflects the utilization status of land use. However, traditional LUI assessments have been conducted for land space governance with a primary focus on surface land. Thus far, the explicit variation and spatiotemporal characteristics of land use of underground space (LUUS), particularly the quantization of LUUS-related intensity, are not well understood. Using the case of Wuhan in China, this study takes the main urban area of Wuhan as the research area, based on the time series data of the underground space information survey of analysis units from 2002 to 2018. This reflected the distribution pattern and evolution characteristics of underground space in terms of the intensity, the concentration and spatial hot-spots by using the spatiotemporal analysis framework. The results show that: (1) The LUUS exhibits spatial characteristics of global dispersion, and local aggregation increased and expanded along the northwest–southeast direction; (2) The global spatial dependency of LUUS is strong and the degree decreases with the expansion of the scope; (3) The LUUS is mainly developed in a relatively concentrated mode, and the concentration degree decreases with time; (4) The main development area of the LUUS is gradually expanding from within the inner ring line outside the second ring road in different periods, and the spatial difference is more obvious and increasing. Our study renews the indicators of quantitative LUI evaluation based on underground spatial data. The findings refreshed the knowledge base concerning the spatiotemporal heterogeneity in terms of underground space intensity and provided new insights into spatial governance. Full article

An urban agglomeration is the engine of regional and national economic growth, but also causes many ecological and environmental issues that emerge from massive land changes. In this study, the spatiotemporal evolution of an urban agglomeration was quantified and its impacts on the urban and regional landscape patterns were evaluated. It showed that the urbanized land area of the Pearl River Delta Urban Agglomeration (PRDUA) in China nearly quadrupled, having linearly increased from 1819.8 km² to 7092.2 km² between 1985 and 2015. The average annual growth rate presented a bimodal wave-like pattern through time, indicating that the PRDUA has witnessed two rounds of the urbanization process. The growth modes (e.g., leapfrog, edge-expansion, infilling) were detected and they exhibited co-existing but alternating dominating patterns during urbanization, demonstrating that the spatiotemporal evolution of the urban development of the PRDUA follows the “spiral diffusion-coalescence” hypothesis. The morphology of the PRDUA presented an alternating dispersal-compact pattern over time. The city-level and regional-level landscape patterns changed synchronously with the spatiotemporal evolution of the PRDUA over time. The urbanization of the PRDUA increased both the complexity and aggregation of the landscape, but also resulted in an increasing fragmentation and decreasing connectivity of the natural landscape in the Pearl River Delta region. These findings are helpful for better understanding how urban agglomerations evolve and in providing insights for regional urban planning and sustainable land management. Full article

Quantifying the change in land use and land cover (LULC) is critical for revealing the impact of human activities on the environment of the Earth’s surface. Although some studies were conducted on the change in LULC in rapidly urbanizing areas, conventional methods could not provide a systematic understanding of the changes and their underlying causes. This study adopted an enhanced Intensity Analysis and landscape matrices to deeply explore the change information and expansion modes of LULC in the Chang-Zhu-Tan Metropolitan Region (CZTMR). This exploration was based on remote sensing images from the past 40 years and GIS tools. The results show that the overall change in the LULC accelerated during the period 1980–2020, with its intensity expanding by 16 times. The Built gain and the Crop loss were steadily active. The Built gain was derived mainly from Crop and Forest, and its mode was dominated by edge expansion. It was detected that the Built gain steadily targeted Crop but avoided Forest despite Built gaining a large area from Forest. The reason for this is because Forest initially had the largest area. The measurement results contribute to the formulation of urban plans and land policies for sustainable development in the CZTMR. Our study explained the evolution of Intensity Analysis and its analytical thought, which could be employed in other regions for the detection of land change to help decision makers develop more targeted and sustainable land management strategies. Full article