Search Results (147)

Green total factor productivity (GTFP) is an important indicator for assessing urban green development under resource and environmental constraints. Using panel data from 110 prefecture-level cities in the Yangtze River Economic Belt from 2007 to 2023, this study examines changes in urban green total factor productivity. A super-efficiency slack-based measure model that includes undesirable outputs is adopted to measure GTFP, while the Malmquist–Luenberger index is used to decompose its dynamic changes. Spatial variation is then analyzed through trend surface analysis, center-of-gravity migration analysis, spatial pattern analysis, and the geographical detector model. The results indicate that GTFP in the Yangtze River Economic Belt improved on the whole, but its growth did not follow a smooth upward path. Among the decomposed effects, technological progress (TC) was the main source of improvement. Clear spatial differences were also observed. Cities in the middle and lower reaches generally had higher GTFP levels than those in the upper reaches, although this gap became less marked over time. The center of gravity of GTFP stayed mainly in the middle reaches and shifted gradually toward the northeast. The driving factors behind spatial differentiation were not constant. In the early stage, energy intensity and economic development level had stronger effects, whereas technological innovation, human capital, and industrial structure upgrading became more influential in the later stage. These findings provide empirical support for differentiated green development policies and coordinated regional governance in the Yangtze River Economic Belt. Full article

This study examines whether higher education development (HED) in China remains geographically locked in a core–periphery structure over 2002–2021 despite long-standing policies promoting balanced development. Using a composite assessment of HED and multiple spatial-inequality diagnostics, we identify strong persistence in the national spatial hierarchy and limited restructuring over time. Results indicate: (1) a stable top tier concentrated in a small set of leading cities, with the top-ranked cities exhibiting a stability index above 0.90, alongside a persistent lagging group; (2) an education-quality “center of gravity” anchored along the North China–East China axis, with a reduced migration distance from 76.58 km to 16.63 km, indicating only modest cross-regional movement; (3) pronounced clustering in major eastern coastal urban agglomerations, contrasted with a broader and weaker distribution in the west; and (4) regionally differentiated constraints—HED in eastern China is jointly driven by economic scale, market demand, and innovation investment, while the central region exhibits no stable dominant driver, the western region remains primarily constrained by economic scale and consumption conditions, and the northeastern region is increasingly shaped by demographic structure and consumption dynamics. These findings indicate that the spatial differentiation of HED is jointly shaped by economic, demographic, industrial, and innovation-related factors. For sustainability-oriented governance, the findings suggest that narrowing gaps requires moving beyond scale expansion toward targeted capability building, cross-regional collaboration, and institutional reforms that improve peripheral regions’ capacity to convert inputs into sustained quality and outcomes. Data granularity remains a limitation; future research should integrate micro-level data and comparative evidence. Full article

Spatial differentiation of urban natural basement conditions leads to significant differences in urbanization development patterns and land evolution patterns in different regions. Taking Fuzhou, a typical coastal basin city located in the Minjiang River Estuary, as the study area, this paper analyzes the spatiotemporal evolution characteristics of land use/cover change (LUCC) and quantifies its driving mechanism from 1990 to 2020, by using the land use transition matrix (LUTM), the center-of-gravity model (CGM), the standard deviation ellipse (SDE), and the optimal parameters-based geographical detector (OPGD). The results show that (1) the land use structure has undergone drastic restructuring, the built-up land has increased significantly, the grassland has decreased significantly, and the cropland and forest land have shown phased evolution characteristics: a light increase from 1990 to 2000 and a continuous decline from 2000 to 2020. Water exhibited a fluctuating pattern: shrinking from 1990 to 2000, expanding from 2000 to 2010, and shrinking again from 2010 to 2020. (2) Constrained by the terrain of the Minjiang Estuary Basin, the gravity centers of cropland and grassland shifted northwestward, forest land moved southeastward, water shifted northeastward, and built-up land expanded northward. (3) Driving factors exhibited stagewise differences: socioeconomic factors played a dominant role from 1990 to 2000, with population density ($q$ = 0.4029) and nighttime light ($q$ = 0.3639) being significantly higher than other factors. From 2000 to 2010, the terrain constraint effect continued to intensify, with GDP ($q$ = 0.4470), nighttime light ($q$ = 0.3658) and DEM ($q$ = 0.3638) as the dominant factors. From 2010 to 2020, urban land pattern evolution was jointly driven by multiple factors. This study clarifies the land use evolution mechanism of coastal basin cities during urbanization, providing a scientific reference for the sustainable development of similar coastal basin cities. Full article

Using a sample of 297 prefecture-level cities in China from 2010 to 2022 and drawing on green patent transfer data, this study constructs a directed weighted network and applies social network analysis, a modified gravity model, and quadratic assignment procedure (QAP) regression to examine the spatial structural evolution, node topology characteristics, and driving factors of China’s green technology transfer (GTT) network. The results show that: (1) From 2010 to 2022, the number of nodes grew from 249 to 292, network coverage increased from 83.8% to 98.3%, and the number of edges expanded by a factor of 14.47. Network density and average degree also rose markedly. The spatial structure evolved from an initially sparse and fragmented configuration into a polycentric complex network centered on the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and the Chengdu–Chongqing economic circle. (2) In terms of node topology, the intermediary and control capacities of cities exhibit dynamic changes, with central and western cities gaining growing influence within the network. (3) Cohesive subgroup analysis identifies four functional blocks, revealing a multi-level technology spillover path of “core—secondary—regional—peripheral.” (4) QAP regression further identifies the digital economy, geographic location, high-speed rail mileage, industrial structure, and government environmental concern as key drivers of network formation and evolution. This study offers a new perspective on understanding cross-regional green technology transfer and provides theoretical grounding and policy references for promoting regional collaborative innovation and green low-carbon development. Full article

Under the dual-carbon goals and energy transition backdrop, the photovoltaic cell has become a crucial pillar for optimizing China’s energy structure and promoting green development. From the perspective of patent intelligence, this study systematically investigates the spatiotemporal evolution paths, coupling characteristics, and driving mechanisms of China’s photovoltaic cell industry and innovation chains, using nationwide photovoltaic cell enterprise and patent data from 2005 to 2024 and integrating spatial gravity center modeling, location quotient analysis, and spatial Durbin models. The findings reveal the following: (1) the spatiotemporal evolution of the dual chains exhibits distinct phases, with a notable developmental leap after 2015. The industry chain shows a pattern of “westward shift and eastern optimization,” while the innovation chain evolves from eastern dominance toward a nationally coordinated, multipolar network. (2) At the macro level, the dual chains demonstrate a coupling trend characterized by “coordinated gravity center migration and spatial distance convergence,” yet significant spatial heterogeneity and mismatch persist at the city scale. (3) Industrial agglomeration has an inverted U-shaped effect on innovation, with regional heterogeneity in its impact, driven synergistically by multidimensional factors such as economic foundation, the innovation environment, and openness. Based on these insights, this study proposes recommendations for optimizing the spatial layout of these dual chains, strengthening multifactor synergy, and implementing regionally differentiated policies, aiming to provide decision-making references for achieving sustainable and high-quality development in the photovoltaic cell. Full article

Mapping directed spillover pathways in urban housing prices is essential for monitoring the contagion of housing prices across cities. However, existing studies typically rely on either spatial gravity models or time-series models in isolation to analyze intercity connections, thus failing to simultaneously capture the spatiotemporal integration characteristics of housing price contagion. To address this, we embed a finite-length sequence correlation analysis (Correlation-Dependent Balanced Estimation of Diffusion Transfer Entropy, $CBEDTE$) into the gravity model, yielding the $CBEDTE$-GM integrated model. Using housing price data from 296 Chinese cities, we construct a spatiotemporal correlation matrix and employ the directed minimum spanning tree algorithm to extract core directed spillover pathways. Results reveal that China’s urban housing price spillover network exhibits a hierarchical architecture with pronounced ripple effects, where eastern coastal cities and the national core city serve as dominant radiation hubs. The East China sub-network occupies a distinctive net spillover position. We identify heterogeneous structural evolution patterns across regional sub-networks: (1) North China evolved from a dispersed multi-centered configuration to a Beijing-dominated single-core structure; (2) East China developed a robust multi-centered architecture anchored by Shanghai; and (3) South China transitioned from a Guangzhou-centered single-core pattern to a tri-polar configuration co-driven by Guangzhou, Shenzhen, and Nanning. Full article

Under the macro background of the rural revitalization strategy and urban-rural integrated development, rural settlements are undergoing a profound transformation from physical morphology to functional connotation. However, existing studies mainly focus on the expansion of single land elements, lacking long-term quantitative monitoring of the coupling relationship between rural development and policy texts. Taking Fuzhou City as a case study, this research selects long-term Global Human Settlement Layer (GHSL) and Night-Time Light (NTL) data from 1990 to 2025, combined with policy text quantification methods. Based on rural development units, the Coupling Coordination Degree Model (CCDM), Macro-Micro Matching Index (MMI), and gravity center migration analysis are employed to systematically reveal the spatiotemporal evolution characteristics and driving mechanisms of rural settlement morphology under policy institutional changes. The research results indicate that: (1) Fuzhou’s rural settlements exhibit relatively stable gravity centers of construction land, while the gravity center of economic vitality has significantly shifted toward the southeastern coastal area under policy guidance; (2) The coupling coordination degree of rural human–land relationships has generally increased, but with significant spatial heterogeneity, forming a pattern of high-quality coordination in coastal areas and low-efficiency lag in mountainous regions; (3) The shift in policy orientation from scale expansion to functional enhancement has driven economic factors to concentrate in key policy areas ahead of physical spatial expansion. The analytical framework combining remote sensing monitoring and policy quantification constructed in this study reveals the precedence of factor flow and the lag of physical space driven by policies, providing a scientific basis for the differentiated governance of rural areas in coastal mountainous cities. Full article

Resource-based cities in the Yellow River Basin are important pillars of national energy security and regional coordinated development, and their green transformation is closely related to the overall strategy of ecological protection and high-quality development in the basin. This study takes 34 resource-based cities within the basin as the research objects and employs a combination of methods, including the Super Slacks-Based Measure (SBM) model, the Malmquist–Luenberger index, the standard deviational ellipse, the Dagum Gini coefficient, and the geographical detector, to systematically analyze the spatio-temporal evolution characteristics and driving mechanisms of green development efficiency from 2012 to 2022. The results indicate that: (1) green development efficiency shows an overall upward trend, forming a pattern of leading performance in the lower reaches, lagging development in the middle reaches, and accelerated catching-up in the upper reaches, with efficiency improvements jointly driven by technical efficiency enhancement and technological progress; (2) the gravity center of efficiency shifts southwestward overall, and interregional disparities constitute the main source of overall differences; (3) economic development level, science and technology investment, fiscal expenditure, and energy intensity are the key driving factors, with significantly strengthened interactions among multiple factors. From the dual perspectives of basin location and the urban life cycle, this study constructs a multidimensional analytical framework that provides a reference for categorized regulation and coordinated regional governance of resource-based cities. Full article

This study examines a panel of 268 Chinese cities during 2013–2023, employing patent applications in Low-carbon technologies (LCTs) as a proxy indicator for the level of LCTs. The spatiotemporal patterns of LCTs are characterized through integrated Standard Deviation Ellipses and Spatial Autocorrelation Techniques, while their driving mechanisms are investigated using Geographic Detectors. The key findings identified in this study are: (1) The advancement of LCTs exhibits a swift increasing trajectory; (2) The eastern region and provincial capital cities have relatively high levels of LCT, while western cities have lower levels. The overall trajectory of the gravity center moves southwest, and typical global and local spatial autocorrelation characteristics are observed in the cities; (3) Infrastructure construction and government R&D funding significantly drive LCTs, while environmental regulations show limited predictive power. Full article

New-type urbanization (NTU) is a key driver of high-quality development and progress toward the Sustainable Development Goals (SDGs) in China. While existing studies acknowledge the multidimensional nature of this process, they often measure it as a single composite aggregate. This approach masks the system’s local sensitivity to internal structural changes and obscures the spatially stratified heterogeneity of dominant drivers. To address this gap, this study constructs construct a comprehensive evaluation index system using panel data for 280 prefecture-level and above cities in China from 2001 to 2023. This study integrates the entropy-weighted TOPSIS method, a modified coupling coordination degree model (MCCD), geographically and temporally weighted regression (GTWR), and the optimal parameters geographical detector (OPGD). Using this framework, this study investigates the spatio-temporal characteristics of the coordinated high-quality development (CHQD) in NTU, systematically dissecting the spatial heterogeneity of local sensitivities and dominant drivers. The results indicate that the following: (1) CHQD exhibits a continuous upward trajectory characterized by significant regional convergence, with the center of gravity gradually shifting southwest. Structurally, green and social dimensions demonstrate the most rapid growth, progressively superseding spatial expansion as primary growth poles. (2) The structural decomposition reveals clear spatially stratified heterogeneity in local sensitivity. The coastal East faces “diminishing marginal utility” of traditional factor inputs, whereas the Central and Western regions continue to reap “structural dividends” from factor accumulation. (3) The dominant drivers shaping spatial heterogeneity have undergone a sequential evolution from an early “resource-space orientation” to a later “innovation-service orientation.” For instance, in the eastern region, the proportion of construction land (L2) had a single-factor explanatory power (q-statistic) of 0.791. However, its interactions with science and technology expenditure (E3) and other factors yielded q-statistics exceeding 0.820, indicating a marked synergistic effect. These findings support region-specific policy recommendations to promote CHQD and inform sustainable urbanization pathways in China. Full article

The complex topography and harsh natural environment of the Loess Plateau in Longzhong have been suffering from an undefined living circle structure, which has hindered rural planning and development. A rural community living circle is a spatial unit centered on meeting the needs of villagers, within which various service facilities are rationally allocated within a specific spatial scope. To refine its spatial patterns, the concept of living circles was introduced to address travel challenges. The extent of these living circles is affected by the accessibility of public service facilities and barriers to travel. Using land use data, DEM, population density, and road networks, this study employed the MCR model, gravity model, and ArcGIS spatial analysis to examine the patterns of rural community living circles. The focus was on analyzing the living circle structure of rural communities on the Loess Plateau in Longzhong, considering both natural and artificial environmental constraints. The results show: (1) Rural community living circles present multi-scale spatial features. The basic living circle covers a 15 min slow-travel area. The central living circle corresponds to village-level needs, accessible within 35 min by both slow and motorized travel. The town living circle covers a 10 km radius, reachable within 60 min by a mix of transport modes. The county living circle, dominated by motorized travel, represents the top tier of public service configuration. (2) Quantitatively, the delineation identified 2753 basic, 444 central, 19 township, and 1 county-level living circles in the Anding District of Dingxi City. The Northern, Eastern, and Southwest Zones suffer from fragmented mountainous landscapes, limiting mobility and accessibility. The Central Zone, however, benefits from a combination of mountainous terrain and river valley plains, offering superior service accessibility. (3) The analysis results based on the MCR model and gravity model aligned more closely with reality, reflecting the scale patterns of rural community living circles. The results of this study can provide theoretical guidance for rural planning, construction, and management in the hilly and gully areas of the Loess Plateau. Full article

Drastic cropland expansion and its internal structural changes have had an obvious impact on agricultural landscapes and ecosystem services. However, a prolonged investigation of this effect is still lacking in China’s grain-producing bases, such as Sanjiang Plain. To address this issue, half a century of study on the ‘land trajectory migration–landscape evolution–ecological effect,’ covering the period 1970–2020, was elucidated using the synergistic methodology of spatial analysis technology, the reclamation rate algorithm, the landscape indicator, and the newly established ecosystem service improvement model. Satellite observation results indicate that the cropland area exhibited a substantial expansion trend from 23,672.69 km² to 42,856.17 km² from 1970 to 2020, representing a net change of +19,183.48 km² and a huge growth rate of 81.04%, which led to an obvious improvement in the level of agricultural cultivation. Concurrently, the internal structure of the cropland underwent dramatic restructuring, with rice fields increasing from 6.46% to 53.54%, while upland fields decreased from 93.54% to 46.46%. In different regions, spatially heterogeneous improvements of 2.64–52.47% in agricultural cultivation levels across all cities were observed. From 1970 to 2020, the tracked cropland center of gravity trajectories exhibited a distinct biphasic pattern, initially shifting westward and then followed by a southward transition, accumulating a displacement of 19.39 km². As for the evolved agricultural landscapes, their integrity has improved (SHDI = −0.08%), accompanied by increased connectivity (CON = +8.82%) and patch edge integrity (LSI = −15.71%) but also by reduced fragmentation (PD = −48.14%). Another important discovery was that the evaluated ecosystem services continuously decreased from 2337.84 × 10⁸ CNY in 1970 to 1654.01 × 10⁸ CNY in 2020, a net loss of −683.84 × 10⁸ CNY and a huge loss rate of 33.65%, accompanied by a center–periphery gradient pattern whereby degradation propagated from the low-value central croplands to the high-value surrounding natural covers. These discoveries will play a significant role in guiding farmland structure reformation, landscape optimization, and ecosystem service improvement. Full article

As a core sector of the Belt and Road Initiative (BRI) and dual-circulation pattern, Xinjiang’s cultural tourism industry—its ninth-largest industrial cluster—plays a key role in enhancing industrial competitiveness and regional coordinated development. To fill the research gap of insufficient analysis on China’s western frontier regions in existing tourism cluster studies, this research focuses on 14 prefecture-level cities in Xinjiang (2009–2023) and innovatively adopts a spatiotemporal synergy and dual-dimensional correlation framework, addressing the limitations of previous single-dimensional research. Tourism Location Quotient (TLQ) quantified specialized agglomeration, Local Moran’s I identified spatial correlation patterns, gravity models analyzed horizontal inter-cluster interactions, and Gray Relational Model (GRM) measured vertical driving relationships between cluster development and related dimensions. This approach facilitates an in-depth analysis of the spatiotemporal evolution trajectory of Xinjiang’s tourism clusters and their horizontal-vertical linkage mechanisms. Findings show: (1) Xinjiang’s tourism clusters present a spatial pattern of “Northern Xinjiang as the core, Eastern Xinjiang with differentiated development, and Southern Xinjiang as lagging.” With narrowing regional gaps, their evolution transitions from a “fixed gradient” to “co-evolution.” (2) Agglomeration effects are significant: Urumqi propels Northern Xinjiang to form a “high-high agglomeration zone,” while Southern Xinjiang remains a “low-low agglomeration zone” led by Kashgar. (3) Horizontal linkages evolve from a Urumqi-centered single-core structure to a multi-axis cluster network, and vertical linkages are mainly driven by destination attractiveness and economic support capacity. This study clarifies the spatiotemporal evolution logic and associated driving mechanisms of tourism clusters in arid, multi-ethnic frontier regions, providing a scientific basis for optimizing regional tourism layouts and promoting high-quality development. Full article

Maize, one of the world’s three major food crops, plays a vital role in global food security. Analyzing the spatiotemporal patterns of maize cultivation in Hunan Province and their influencing factors contributes to enhancing planting quality and efficiency, optimizing production patterns, and supporting provincial food security initiatives. Utilizing maize cultivation data from Hunan Province (2001–2023), this study employed the standard deviation ellipse, center of gravity shift model, and principal component analysis to examine production patterns and their drivers. Key findings include the following: (1) The maize planting area exhibited an overall increasing trend from 2001 to 2023, with a spatial convergence from the northwest towards the east. Cultivation hot spots were identified in Shaoyang, Loudi, and Changde. Maize cultivation was predominantly concentrated in areas with gentle slopes (0–3°) and gradually shifted eastward towards similar terrain. (2) The provincial maize production center of gravity followed a “Z”-shaped trajectory, moving eastward and southward with Loudi City as its core. While the spatial distribution pattern shifted from “northwest–southeast” to “west–east”, the core concentration area maintained its “northwest–southeast” orientation. Concurrently, the fragmentation of cultivated land within the maize planting landscape increased. (3) Maize planting hot spots expanded from the northwest towards the central and eastern regions, extending southward. Cold spot areas shifted from the central region towards the northeast. By the study’s end, the central region had emerged as the core maize planting area. (4) Agricultural production conditions and policy factors were identified as the main drivers of spatiotemporal changes in maize acreage within Hunan Province. Full article

Harmonizing economic growth and carbon emissions is key to reaching the “dual carbon” targets. This research centers on the seven key urban agglomerations within the Yellow River Basin (YRB) and establishes an integrated research framework of decoupling effect quantification–spatial association recognition–driving factor analysis. By combining the Tapio decoupling model, a modified gravity model, social network analysis (SNA), and the Logarithmic Mean Divisia Index (LMDI) method, the study systematically evaluates the decoupling states, spatial association structure, and driving mechanisms between regional carbon emissions and economic growth from 2001 to 2020. The results show that: (1) All seven urban agglomerations exhibit a simultaneous upward trend in both carbon emissions and GDP, but significant regional disparities exist, with some agglomerations demonstrating a green growth pattern where economic growth outpaces carbon emissions. (2) Weak decoupling is the predominant type among urban agglomerations and their constituent cities in the YRB. Notably, some regions have regressed to growing connection or growing negative decoupling during 2016–2020. (3) The spatial network of carbon emission decoupling effects exhibits a core-periphery structure characterized by stronger eastern regions and weaker western regions, with the Shandong Peninsula and Guanzhong Plain urban agglomerations serving as core nodes for regional linkage. (4) Per capita GDP and technological level play a dominant role in promoting decoupling, while energy intensity and the population carrying intensity of the real economy are the primary inhibiting factors; the impact of industrial structure shows an unstable direction. Grounded in these findings, this study formulates differentiated carbon reduction pathways tailored to regional heterogeneity, providing theoretical insights and actionable guidance to facilitate the low-carbon transition and coordinated governance of urban agglomerations. Full article