Search Results (174)

To promote the sustainable use of land resources and improve air pollution control, this study investigates the spatiotemporal dynamics of industrial land development and the heterogeneity of PM_2.5 concentrations across regions. Based on national land transaction data and PM_2.5 raster datasets, the analysis employs Moran’s I, a hot and cold spot analysis, and multivariate linear regression to examine how the transaction frequency, transaction area, and total transaction price of industrial land influence PM_2.5 concentrations in 286 cities from 2010 to 2021. The study focuses on quantifying the impact of industrial land development on PM_2.5 concentrations. The main findings are as follows: (1) the frequency of industrial land transactions varies significantly across regions, with clear intra-regional differences. The transaction area and total transaction price decrease in the following order: “East-West-Central-North-East” and “East-Central-West-North-East”, respectively. (2) The spatial clustering of PM_2.5 concentrations has intensified, with hot spots concentrated in Eastern and Central cities. Cold spots are distributed in bands along the Southern coast and scattered patterns in Heilongjiang Province. (3) The influence of industrial land development on PM_2.5 concentrations has generally weakened nationwide, with the strongest effects observed in the Eastern region. Among the development indicators, the impact of the transaction area is increasing, while those of the transaction frequency and total price are declining, showing clear regional disparities. Therefore, integrating sustainable development principles into the adjustment of the industrial land market is essential for effective air pollution prevention. Full article

Under China’s dual land ownership system, the use rights of urban land (state-owned) and rural land (collective-owned) are not equal. Understanding the roles of ownership type and government decision-making behaviors in the formation of land prices is crucial for further reform to promote “equal rights and equal prices” for urban and rural land. This paper analyzed the impact of ownership type on construction land prices using micro-level land transaction data from Wujin District, Changzhou City, from 2015 to 2021 and investigated the role of government decision-making behaviors such as spatial planning and supply plan in this relationship. The results show that collective ownership has a negative impact on land prices, and the development of collective-owned construction land has a positive impact on the prices of adjacent land. In addition, the boundary of downtown areas determined by spatial planning enhances the negative impact of collective ownership on land prices, thus widening the price gap between state and collective-owned land within the downtown areas. Furthermore, the proportion of collective-owned construction land in the annual land supply determined by the land supply plan strengthens the negative impact of collective ownership on land prices, meaning that an increase in the supply of collective-owned construction land leads to further downward pressure on land prices. This study can provide insights for policy making aiming to achieve “equal rights and equal prices” for land with different ownership type in China and in other countries with a dual land ownership system. Full article

Positional accuracy in cadastral data is fundamental for secure land tenure and efficient land administration. However, many land administration systems (LASs) experience difficulties to meet accuracy standards, particularly when data come from various sources or historical maps, leading to disruptions in land transactions. This study investigates the use of unsupervised clustering algorithms to identify and characterize systematic spatial error patterns in cadastral maps. We compare Fuzzy c-means (FCM), Density-Based Spatial Clustering of Applications with Noise (DBSCAN), and Gaussian Mixture Models (GMMs) in clustering error vectors using two different case studies from Greece, each with different error origins. The analysis revealed distinctly different error structures: a systematic rotational pattern surrounding a central random-error zone in the first, versus localized gross errors alongside regions of different discrepancies in the second. Algorithm performance was context-dependent: GMMs excelled, providing the most interpretable partitioning of multiple error levels, including gross errors; DBSCAN succeeded at isolating the dominant systematic error from noise. However, FCM struggled to capture the complex spatial nature of errors in both cases. Through the automated identification of problematic regions with different error characteristics, the proposed approach provides actionable insights for targeted, cost-effective cadastral renewal. This aligns with fit-for-purpose land administration principles, supporting progressive improvements towards more reliable cadastral data and offering a novel methodology applicable to other LASs facing similar challenges. Full article

Information consumption has been reshaping the modes of human living and production, and driving the transformation of production and trade activities traditionally dependent on land resources, thus influencing urban land green use efficiency (ULGUE). Based on the panel data of 281 prefecture-level cities in China from 2011 to 2023, this study employs the national Information Consumption Pilot Policy (ICPP) as a quasi-natural experiment and utilizes a double machine learning model to assess the ICPP’s impacts on ULGUE. According to the results of the causal mediating effect analysis, the ICPP has improved ULGUE through three mediating mechanisms: expanding the scale of digital transactions, nurturing future industrial developments, and promoting green consumption behaviors. Moreover, in light of the results of the heterogeneity analysis, the ICPP’s impacts on ULGUE vary significantly. Such variation can primarily be attributed to differences in urban resource endowments, disparities in transportation infrastructure development, and variations in geographical location. Specifically, the ICPP has produced more prominent impacts on enhancing land green use efficiency in resource-based cities, cities with high-speed rail access, and coastal cities. Therefore, the government should proactively establish an urban information consumption environment, enhance the role of digital transactions, strategize future industrial developments, encourage green consumption behaviors, and differentiate local policies to effectively promote the continuous improvement of ULGUE. Full article

Land serves as a crucial repository of resource elements, and enhancing the green use efficiency of urban land (GUEUL) is essential for attaining sustainable development. Based on 296 cities in China from 2006 to 2022, this study explored the relationship between land system innovation and GUEUL by integrating multi-source data, ArcGIS analysis, the EBM-DEA model, and the DID model, and elucidating the temporal trend and spatial utilization characteristics of GUEUL in China. Based on the natural experimental scenario of the pilot reform of China’s urban construction land use approval system, this study finds through in-depth analysis of the double-difference model that the vertical transfer of land approval authority has fundamentally optimized the development pattern of GUEUL, and that this positive impact is mainly reflected in two dimensions: on the one hand, it reduces the systematic transaction costs, and on the other hand, it enhances the density of industrial spatial agglomeration. Second, the lower the initial level of infrastructure and the lower the degree of dependence on land finance, the more significant the decentralization of land approval power in the promotion of GUEUL. Currently, China is undergoing a swift phase of urbanization and industrialization, and this study provides policy support for improving the comprehensive efficiency of green land use and promoting high-quality and sustainable development of the region. Full article

While the literature has investigated the associations between urban environments and COVID-19 infection, most studies primarily focused on urban density factors and early outbreaks, often reporting mixed results. We examined how diverse urban factors impact COVID-19 cases across 229 administrative districts in South Korea during Pre-Omicron and Post-Omicron periods. Real-time big data (Wi-Fi, GPS, and credit card transactions) were integrated to capture dynamic mobility and economic activities. Using negative binomial regression and random forest modeling, we analyzed urban factors within the D-variable framework: density (e.g., housing density), diversity (e.g., land-use mix), design (e.g., street connectivity), and destination accessibility (e.g., cultural and community facilities). The results revealed the consistent significance of density and destination-related factors across analytic approaches and transmission phases, but specific factors of significance varied over time. Residential and population densities were more related in the early phase, while employment levels and cultural and community facilities became more relevant in the later phase. Traffic volume and local consumption appeared important, though their significance is not consistent across the models. Our findings highlight the need for adaptive urban planning strategies and public health policies that consider both static and dynamic urban factors to minimize disease risks while sustaining urban vitality and health in the evolving pandemic. Full article

Spatial justice, as a fundamental value in social systems, plays a key role in achieving social justice and improving human well-being. Drawing on theories of spatial justice, property rights, and new institutional economics, this study explores the comprehensive impact of land development rights (LDR) transfer on urban–rural spatial economic, resources, social, and ecological equity from the perspective of urban–rural spatial justice. Using the Chongqing land quota trading pilot as the core case, we apply synthetic control methods to analyze the causal effects of this policy. The results show that LDR transfer promotes urban–rural spatial resources equity in the short term, particularly through the marketization of land transactions. Over the long term, it significantly enhances urban–rural spatial economic and social equity, evidenced by the narrowing of the income gap, the growth of the primary industry, and improved connectivity between urban and rural areas. However, the improvement in ecological equity through LDR transfer lacks sustainability, suggesting the need for stronger ecological protection measures in future policies. By establishing a comprehensive framework for urban–rural spatial justice and using comparative spatial indicators to measure equity, this study advances our understanding of how LDR transfer can promote urban–rural spatial justice and provides valuable insights for future policy refinement and institutional reforms. Full article

Urban renewal is a critical approach to address issues such as the scarcity of urban spatial resources and infrastructure aging in the later stages of urbanization. Urban village renewal is one of the typical practices of urban renewal. Based on China’s unique dual urban–rural land system and urbanization process, this study localizes the rent gap theory. It applies the modified rent gap theory to conduct a case study on Wangjiapeng Village in Xi’an using the process-tracing method. It explores the internal mechanisms of urban village renewal and the key factors influencing the progress of renewal projects. The findings reveal that the size of the rent gap directly determines the attractiveness and timing of urban village renewal. However, issues such as interest conflicts, administrative redundancy, and government supervision during the renewal process significantly increase transaction costs, raising the rent gap threshold and thereby affecting the progress and outcomes of the renewal. This paper proposes a rent gap theory that is more suited to China’s context and further expands its applicability through case study research. The practical experience of Wangjiapeng Village provides important policy implications for other major cities in China and cities currently in the late stages of urbanization. Full article

This study, as a contribution to the research on urban land grabbing (grabs) as a global phenomenon, seeks to evaluate the populist belief that developers swallow up urban land originally zoned for community purposes under Government, Institution and Community (GIC) zoning, thus depriving communities of space for their own benefit. The authors applied a systematic analysis of non-aggregate planning and development statistics to better interpret the features of the land market as regulated by zoning. Their research focuses on the salient features of redevelopment projects that enjoy successful planning applications and onsite development in GIC zones. They compared the planning and development statistics, obtained from the Planning Department’s website, of 425 approved GIC projects with those of the 261 Comprehensive Development Area (CDA) zone projects. Subject to the limitations of the data collected, the results qualify a negative view of land oligarchs (powerful land developers) who sought land under unitary ownership obtained in the past at nominal land premiums for quick windfalls. Particularly, GIC redevelopments were found to have proceeded much faster than CDA developments and, hence, were a natural attraction to developers, which were diverse, not exclusively private, and produced a few urban innovations during the redevelopment process. Full article

Given the increasing environmental pressures, it is essential that agriculture achieves the goal of sustainable and low-carbon development. In 2010, China, as the top carbon emitter, introduced a policy on agricultural land lease (ALL), which has been met with considerable approval from farmers and has resulted in a notable surge in the rate of ALL within the country. Nevertheless, the question of how the ALL policy affects agricultural carbon emissions (ACEs) remains unanswered. What are the transmission mechanisms? To answer these questions, this paper presents an equilibrium model that accounts for the heterogeneous production efficiency among farmers. It offers a theoretical analysis of the impact of ALL policy on agricultural carbon emission reduction (ACER) and presents an empirical test of this impact using a difference-in-differences (DID) model. Our research shows that the ALL policy gives impetus to ACER. This conclusion persists even after conducting the robustness and endogeneity tests. The mechanism posits that the policy achieves ACER through reducing the proportion of rural agricultural employees. Heterogeneity analysis indicates that the policy effect is significant in both the northern and southern regions of China. Nonetheless, the effect is only observable in economically developed areas, regions with high chemical fertilizer application rates, and areas with restricted agricultural progress. This study elucidates the connection between land transfer and agricultural carbon emissions, offering empirical evidence to support the advancement of green and low-carbon agricultural development. Full article

Investigating the experience and improvement measures for China’s distinctive land supply participation in macro-control processes holds significance for full utilization of land policy. However, the spatial heterogeneity and its theoretical and comprehensive analysis of drivers are still poorly revealed. This paper uses spatial analysis methods and micro-scale big data on land transactions to depict the spatiotemporal heterogeneity of land supply, and analyses its driving mechanisms via an endogenous–exogenous factor framework and regression models. Land supply experienced fluctuating “growth–decline–growth” trends in 2001–2021, spatially showed a large cluster in the east, a small cluster in the center and scattering in the west, with the gravity center relocating southwest, and formed a multi-core, hierarchical, circular structure of high density in core cities, density in peripheral cities and sparseness in districts. Endogenously, total land resources and road accessibility facilitated land supply, while topographic relief and urban proximity showed inhibitory effects; land supply positively correlated with land finance dependence, officials’ appraisal pressure, local government competition and officials’ corruption but negatively related with fiscal tax revenues and fiscal transparency; construction land indicators directly determined land supply, while the intensity of use control restricted the conversion of arable land and weakened land supply. Exogenously, urbanization, industrialization, capital investment, technological innovation and marketization level promoted land supply, while the substitution of human capital reduced the demand for land; economic fluctuations showed non-significant relationships with land supply. Differentiated impacts of multiple factors on land supply pattern are emphasized and should be integrated into formulating land policy and optimizing land allocation. Full article

Successfully advancing the redevelopment of urban villages can unlock land resources for high-quality urban development. This study attempts to explain the heterogeneous outcomes of urban village redevelopment projects in China. A comparative case study method is adopted to analyze the transaction costs and the processes applied under distinct institutional arrangements. The analysis of four cases demonstrates how institutional arrangements affect transaction costs by creating a power structure that encompasses the different participants, who represent the different interests of constituent groups in exchanges of land and housing. This study demonstrates that institutional arrangements are not immutable. In addition to transaction costs, changes in the external institutional environment can alter institutional arrangements. Changes in relative prices and ideologies can also induce institutional changes. Subtle factors, such as issues indirectly linked to the redevelopment, can increase the transaction costs of achieving a consensus if policymakers ignore them in the initial policymaking stage. The findings contribute to a nuanced understanding of the heterogeneous outcomes of urban village redevelopment in China and will encourage local governments to take effective measures to ensure smooth urban village redevelopment. Full article

Land and real estate have long been regarded as stable investments, with property prices steadily rising, underscoring the need for accurate predictive models to capture the varying rates of price growth across different locations. This study leverages a decade-long dataset of 83,527 apartment transactions in Vienna, Austria, to train machine learning models using XGBoost. Unlike most prior research, the extended time span of the dataset enables predictions for multiple future years, providing a more robust long-term prediction. The primary objective is to examine how spatial factors can enhance real estate price predictions. In addition to transaction data, socio-demographic and geographic variables were collected to characterize the neighborhoods surrounding each apartment. Ten models, each varying in the number of input years, were trained to predict the price per square meter. The model performance was assessed using the mean absolute percentage error (MAPE), offering insights into their predictive accuracy for both short-term and long-term predictions. This study underscores the importance of distinguishing between newly built and existing apartments in real estate price modeling. By splitting the dataset prior to training, predictive models focusing solely on newly built properties achieved an average reduction of about 6% in MAPE. The best-performing models achieved an average MAPE of 15% for one-year-ahead predictions and maintained a MAPE below 20% for predictions up to three years ahead, demonstrating the effectiveness of leveraging spatial features to enhance real estate price prediction accuracy. Full article

The land price reflects the supply and demand relationship in the land market and plays an important role in regulating land use. Improving land auction rules is of great significance for avoiding abnormal fluctuations in the land market and promoting the sustainable use of land resources. To regulate the abnormal fluctuations in the state-owned land use rights’ auction prices, Chinese local governments have implemented a “sealed one-time bidding, average price wins” rule. However, limited theoretical and empirical research that assesses its policy impact exists. This study examines the policy motivations behind this rule, constructing three game models; namely, static complete information, static incomplete information, and multiperiod repeated games. By deducing bidding strategies and equilibrium results, hypotheses are formulated. A baseline difference-in-differences (DID) and a dynamic policy effect model are designed, and the Python crawler is used to obtain 1182 microland auction samples in Suzhou. This study evaluates the impact of the one-time bidding rule on the starting prices, transaction prices, and premium rates. The empirical results underwent multiple robustness tests, eliminating potential endogeneity issues and biases. The results show that while the policy is effective in restraining the premium rate, indicating the bidding intensity in single-land auctions, it proves challenging to curb the long-term rise in land prices through continuous bidding auctions. Moreover, the policy may stimulate local governments to increase auction starting prices. Full article

The US rejoined the Paris Agreement in 2021 with a targeted 50–52% reduction in net GHG emissions in 2030 relative to 2005. Within the US’s nationally determined contributions, several land-based mitigation options were submitted, targeting the removal of 0.4–1.3 GtCO₂ yr⁻¹ in 2030 compared to the net flux in 2010. Acknowledging disagreement has existed on both technological and economic feasibility levels of soil C sequestration adoption and practices, this review explores and evaluates the research findings and needs for six concepts: (1) permanence; (2) additionality; (3) leakage; (4) uncertainty; (5) transaction costs; and (6) heat-trapping ability of different gases. These concepts are crucial for the effective implementation of soil C sequestration projects since they help establish robust and integrated methodologies for measurement, verification, and issuance of carbon credits. In turn, they help ensure that environmental, social, and economic benefits are accurately assessed and credibly reported, enhancing the integrity of carbon markets and contributing to global climate mitigation efforts. This review also evaluates the existing and potential market opportunities for agricultural production with C sequestration and “climate- smart” farming practices. Current barriers to, research needs for, and policy considerations regarding soil C sequestration strategies are also stated. Full article