Search Results (580)

Accommodation establishments constitute a core component of tourism infrastructure, and their location choices directly affect water resource utilization, land pressure, and the spatial equilibrium of tourism development—issues that are particularly acute in vast arid regions. Yet the spatial organization of accommodation supply across extensive drylands characterized by fragmented oasis distribution, and the reasons why standard and non-standard accommodation follow divergent location logics, remain poorly understood. This study addresses three questions: (1) How are nine accommodation categories, differentiated by type and quality, distributed across Xinjiang? (2) Do directional spatial associations exist among categories that are consistent with hierarchical, path-dependent development? (3) Which factors drive these patterns, and do their effects exhibit the nonlinearity and threshold behavior predicted by location theory? Drawing on 12,073 accommodation establishments from the Ctrip platform, we construct a staged analytical framework in which each technique answers a specific question: the nearest-neighbor index and standard deviational ellipse characterize global patterns; kernel density estimation and OPTICS clustering identify local agglomerations; directional local co-location quotients measure asymmetric spatial associations; and XGBoost–SHAP isolates nonlinear drivers and threshold effects. Results reveal a highly concentrated “single-core, multi-center” structure anchored by Urumqi, Yining, and Kashgar, with rapid expansion toward the Ili Valley, Kashgar, and Altay since 2019. Standard accommodation tracks urban centrality and transport nodes, while non-standard accommodation tracks tourism resource endowments, consistent with location-theoretic expectations. Directional co-location analysis reveals hierarchical spatial associations among categories, and driving factors exhibit pronounced nonlinear threshold effects. From a sustainability perspective, the identified thresholds—elevation (1360 m), water-body proximity, and distance to rural tourism demonstration sites (3 km)—constitute quantifiable, spatially explicit sustainability indicators that can be incorporated into planning tools to monitor and steer accommodation development away from ecologically sensitive zones. Global Moran’s I diagnostics of model residuals (reduction of 83–99.7%) suggest that these findings are unlikely to be artifacts of spatial autocorrelation; this diagnostic, however, complements rather than replaces spatially blocked validation. The study contributes category-differentiated, spatially directed evidence for policies balancing tourism expansion against water security and ecosystem integrity, serving sustainable tourism development in arid-region destinations. Full article

The pervasive rise in digital platforms has fundamentally recalibrated the relationship between urban communities and their cultural landscapes, reconfiguring not only the sensory experience of these environments but also their interpretive frames and the everyday contestations that surround them. Using coffee spaces in Beijing as an empirical lens, this study integrates 630 validated POI locations, 287,632 online reviews from Dianping, GIS spatial analysis, LDA topic modelling, semiotic coding, and a fine-tuned RoBERTa (Robustly Optimized BERT Pretraining Approach) text classifier to examine the convergence between platform-mediated public perceptions and urban spatial differentiation. Our spatial interrogation identifies a statistically significant centre–periphery divide within this platform-curated corpus—a pattern that describes the geography of platform-mediated visibility rather than the total physical distribution of coffee outlets in Beijing, characterised by pronounced high-density agglomerations nesting within historic urban cores, central business districts, nascent knowledge hubs, and gentrifying lifestyle enclaves. Three landscape prototypes are derived from the data—business corridors, cultural experimental fields, and social-media spectacles. Each type exhibits discernibly different patterns of spatial density, adjacent land-use configurations, perceived experiential qualities, and underlying symbolic discourses. While positive sentiments dominate platform discourse, localised anxieties emerge regarding visual homogenization, intense queuing, premium pricing, and loss of place authenticity. The 630 venues analysed here represent a platform-visibility stratum—establishments sufficiently reviewed to feature on digital intermediaries—and the spatial patterns we map describe the geography of this visibility rather than the total physical distribution of coffee outlets. Full article

Urban agglomerations are increasingly exposed to shocks that extend across administrative boundaries through infrastructure systems, industrial chains, population mobility, and shared ecological spaces. Existing urban resilience research has predominantly assessed city-level capacity, while comparatively less attention has been paid to the relational structures associated with differences in resilience capacity and geographic proximity. This study examines the model-implied spatial correlation network of urban resilience across 41 cities in the Yangtze River Delta from 2013 to 2022. A multidimensional resilience index covering economic, infrastructure, social, and ecological dimensions was constructed using the entropy weight method and directed intercity interaction potentials were estimated using a modified gravity model and analyzed through social network analysis. The results show that overall resilience improved during the study period, although substantial cross-city disparities persisted. Under the baseline row-specific mean threshold, network density remained broadly stable, fluctuating between 0.2476 and 0.2506 and decreasing slightly from 0.2506 in 2013 to 0.2482 in 2022. The model-implied network remained fully reachable but relatively sparse, with persistent positional differentiation. Nanjing and Hangzhou consistently occupied leading total-degree positions, while Hefei, Nanjing, Hangzhou, Huangshan, and Chuzhou repeatedly exhibited relatively high betweenness. The block-model structure was also comparatively stable, with only three cities changing block membership between 2013 and 2022. Robustness analyses further showed that broad positional differentiation was more stable than exact density levels, outward-oriented rankings, and brokerage positions. Overall, improvements in city-level resilience did not translate into substantial densification or reorganization of the regional network, highlighting the need to distinguish internal resilience capacity from model-implied network position when designing differentiated regional coordination strategies. Full article

With urban rail transit networks gradually entering a mature stage of development, whether newly added lines and stations can still improve local labour market outcomes remains an important question in transport planning and urban regeneration research. This paper examines light rail transit expansion in three mature UK cities: Manchester, Sheffield, and Nottingham. Using MSOA-level panel data from 2013 to 2024, this study applies a Difference-in-Differences (DID) approach to evaluate the impact of light rail transit expansion on local labour market vulnerability. MSOAs intersecting with the 500-m buffer zones of newly opened light rail stations are defined as the treatment group, while MSOAs not directly affected by light rail expansion are used as the control group. The Claimant Count is used as a proxy for welfare dependency and labour-market vulnerability. The results show that light rail transit expansion significantly reduces the Claimant Count in treated areas, with an estimated decline of approximately 7.52–7.56%. This finding remains robust after adding demographic, socio-economic, and built environment controls, applying MSOA-level clustered standard errors, implementing PSM-DID, and conducting placebo tests. Mechanism analysis further shows that light rail expansion is associated with changes in the functional structure of station areas, including increases in overall POI density and service-oriented facilities, while manufacturing and production-related facilities decline. These findings suggest that light rail expansion may reduce local unemployment-related welfare dependency by improving employment accessibility, alleviating spatial mismatch, and promoting service-sector agglomeration. This study provides new empirical evidence on the socio-economic effects of light rail expansion in mature UK cities. Full article

Urban–rural governance and planning systems, as viewed through the lens of online public attention, are reshaping approaches to achieving coordinated development of cultural heritage conservation and urban space. Taking Nanchang as a case study, this paper investigates the application mechanism of online public attention in the evaluation of heritage corridor nodes and the formulation of optimization strategies. Employing multi-source data collection, we extracted textual content from online travelogues. We quantified the online attention level of each cultural heritage unit and analyzed its spatial distribution using kernel density estimation and standard deviational ellipse methods. We then applied a minimum resistance model, incorporating geographic data on land use and transportation networks, to identify potential heritage corridor routes. Based on attention classification, we propose a three-tier optimization strategy: core-leading, marginal-activating, and gradient-linking. Specifically, high-attention heritage units are positioned as central nodes that reinforce corridor connectivity; low-attention nodes are targeted for activation through corridor links to overcome spatial isolation; and attention gradients serve as the basis for hierarchical integration across the network. Our results reveal a pronounced spatial pattern of “core agglomeration and peripheral dispersion” in Nanchang’s heritage corridors. High-attention resources are heavily concentrated in the historic urban core, anchoring the main corridor axes, whereas low-attention resources are scattered across peripheral counties, exhibiting a clear urban–rural attention gradient. Importantly, attention levels show a positive correlation with corridor hierarchy. These findings provide a novel perspective for heritage corridor spatial planning and offer practical insights for sustainable cultural heritage governance and culture–tourism integration in an era of pervasive internet and urban expansion. Full article

Urban employment restructuring generates job–housing mismatches whose planning consequences depend on spatial scale and temporal trajectory, yet existing data sources rarely combine fine spatial resolution with long temporal coverage. This study applies multiscale geographically weighted regression (MGWR) to reconstruct annual employment surfaces at 1 km² resolution for Tianjin, China, from 2010 to 2023, using a single anchor year of mobile signaling data. Spatial relationships estimated from 2020 records were transferred across time using annual updates of Points of Interest (POI) density, nighttime light intensity, and population density, with aggregate consistency enforced against official employment totals. Validation confirmed the spatial ordering of employment concentration in the calibration year (Spearman ρ = 0.509, RMSE = 2856 jobs/km²), temporal stability in an independent year (ρ = 0.522, RMSE = 2640 jobs/km² for 2023), and consistency with district statistics (R² = 0.718). Directional robustness to anchor-year selection was further supported by reverse-transfer validation (ρ = 0.652) and by a 2023-anchored reconstruction that replicated the principal directional findings. Three findings emerged that remain invisible at conventional administrative resolution: employment decentralization was spatially bounded at the intermediate ring by an economic activity intensity gradient; the dual-core structure remained morphologically stable while the two poles diverged functionally due to structurally different employment bases; and employment agglomeration change preceded spatial job–housing co-location adjustment by approximately three years. This exploratory lag is consistent with a theoretical assumption of sequential adjustment—a city-specific exploratory signal whose planning implications warrant further investigation in other restructuring cities. Full article

With the continuous improvement of tourism infrastructure and the rapid development of digital platforms, tourism development is increasingly shaped by both traditional and digital factors. As one of China’s major urban agglomerations, the Urban Agglomeration in the Middle Reaches of the Yangtze River provides an important case for examining regional tourism development in the digital era. This study investigates 31 prefecture-level cities and develops a comprehensive evaluation framework covering tourism development foundation, platform visibility, and tourism market performance. The entropy weight-TOPSIS method, coupling coordination model, GIS spatial analysis, and optimal-parameter geographical detectors are employed to examine spatial patterns and driving mechanisms. The results show that Wuhan, Changsha, and Nanchang constitute three major tourism growth poles. Tourism development foundation exhibits a clear core–periphery pattern, while the overall coupling coordination degree remains moderate to low, with some cities characterized by high coupling but low coordination. Platform visibility is identified as a key factor contributing to spatial disparities and demonstrates a significant nonlinear enhancement effect when interacting with transportation factors. These findings highlight the importance of digital platforms in regional tourism development and provide implications for promoting coordinated tourism development within urban agglomerations. Full article

Global environmental change has shifted disaster risk from being predominantly natural hazard-dominated to increasingly socially driven. While the Social Vulnerability Index (SoVI) is widely used to quantify these dynamics, its construction remains hindered by uncertainty in weighting algorithms and spatial aggregation schemes. This study assesses SoVI in Taiwan across three harmonized study years (2015, 2020, and 2025) by bridging data innovation, spatial representation, and methodological synthesis. To offer fine-scale spatial representation, we integrate gridded nighttime light, urban built-up volume, and population density to shift vulnerability assessments from conventional administrative borders to functional, data-driven Human Agglomeration Zones (HAZs). Furthermore, we examined algorithmic uncertainty by comparing the variance-driven Principal Component Analysis (PCA) against the Entropy Weight Method (EWM). We found that integrating gridded socioeconomic data can effectively identify small contiguous HAZ patches that were commonly omitted by administrative divisions. The results also reveal a twofold pattern of vulnerability. PCA produced comparatively stable rankings and repeatedly identified south-central counties as high-vulnerability areas, whereas EWM generated more concentrated weights and a stronger reordering of vulnerability patterns in 2025 as the weight assigned to population density increased sharply. Ultimately, by proposing a synthesized multi-method framework, a comprehensive SoVI was established to mitigate algorithmic bias, providing policymakers with a multidimensional tool that aligns long-term structural investments with short-term dynamic monitoring. Full article

Spatiotemporal differentiation and coupled driving mechanisms of urban ecological resilience in transboundary composite economic belts remain an understudied niche within human–land coupling system research. Taking 29 prefecture-level and county-level units of the Huaihe River Eco-Economic Belt from 2014 to 2023 as research samples, this study constructs an ecological resilience evaluation framework tailored to the pollution disturbance characteristics of the Huaihe River Basin under a three-dimensional theoretical framework encompassing resistance, adaptability, and recoverability. The entropy weight method is adopted to calculate comprehensive ecological resilience values, while the geographically and temporally weighted regression (GTWR) model is applied to identify spatiotemporal heterogeneous correlations among multiple influencing factors. This paper further characterizes the spatiotemporal evolutionary patterns of urban ecological resilience across the study area and unpacks the coupled associative effects of natural, economic, and social driving factors. The empirical results reveal three key findings: (1) Temporally, the overall comprehensive ecological resilience of the study region rose from 0.318 to 0.416, with a total growth rate of 30.91%. Its evolutionary trajectory follows three successive phases: rapid growth, steady improvement, and slow saturation. Adaptability, which is predominantly boosted by anthropogenic environmental governance, constitutes the primary contributor to resilience growth. The range of urban resilience values narrowed by 9.97%, indicating continuous advancement in balanced regional development. (2) Spatially, ecological resilience presents a prominent core-periphery pattern, with high-resilience zones concentrated in mountainous southwestern areas and low-resilience zones distributed across northeastern plains. All low-resilience county-level units were eliminated by 2023. (3) In terms of driving associations, topographic relief and environmental governance investment maintain persistent positive correlations with ecological resilience, while per capita GDP acts as the core economic supportive factor. The proportion of secondary industry and population density exhibit significant negative correlations with resilience. The normalized difference vegetation index (NDVI) shifts from a negative correlation to a weak positive correlation alongside progressive ecological restoration, whereas river network variables exert negligible long-term associative impacts. Collectively, the spatiotemporally heterogeneous coupling of natural endowments, industrial-economic conditions, and social governance factors shapes the evolutionary patterns of regional ecological resilience. This study fills the research gap regarding long-timescale resilience driving mechanisms for transprovincial composite river basins covering five provinces. It identifies novel human–land coupling mechanisms, including the temporal reversal of vegetation’s ecological benefits and the dual stress imposed by industrial agglomeration and dense human settlements in plain regions. The quantitative outputs of this research can provide data-based references for differentiated coordinated ecological governance across the Huaihe Ecological Economic Belt. Full article

Against the backdrop of stock-space urban renewal, green-space governance in megacity cores increasingly requires a shift from expansion-oriented supply to the optimisation of existing spatial resources. This study examines the spatial equity of green-space provision in the central districts of seven Chinese megacities using high-resolution remote-sensing data from 2015, 2020, and 2025. We combined semantic segmentation, nested-buffer measurement, the Gini coefficient, Extreme Gradient Boosting (XGBoost), and Shapley Additive Explanations (SHAP) to evaluate the relationships between urban morphology and green-space provision. We first derived a pixel-level cumulative green-space provision index from nested-buffer measurements and calculated city-year Gini coefficients to quantify distributional inequality. XGBoost models were then used to predict the cumulative green-space provision index from urban morphology, and SHAP was applied to interpret the resulting nonlinear, model-derived associations. The results show that changes in the green-space provision index and its distributional inequality were not synchronous across cities. Beijing showed the largest increase in inequality, whereas Chengdu showed the strongest improvement; Tianjin recorded the fastest increase in the green-space provision index, while Beijing experienced a marked decline. Urban form showed nonlinear associations with the unit-level green-space provision index, helping to explain the spatial differentiation underlying the city-year Gini coefficients. Building density was the primary contributor in most city-year models, whereas compactness showed threshold-like associations, with positive effects at lower levels and inhibitory effects at higher levels. Statistical testing and clustering further indicated substantial heterogeneity among cities, which were categorised into three spatial patterns: centripetal agglomeration, peripheral expansion, and clustering/ring-shaped fluctuation. These findings provide morphology-based evidence for differentiated green-space governance in high-density megacity cores, though they should not be interpreted as a complete socioeconomic assessment of green-space equity. Full article

To advance environmental sustainability, China proposed the Beautiful China Goals (BCGs) as its localized strategy, with urban agglomerations serving as the key implementation scale. To address the limitations of difficulty in identifying key tasks and insufficient regional applicability, this study develops a multi-goal evaluation system comprising 21 goals and 52 indicators rooted in the policy framework. Methodologically, a three-tiered assessment framework—goal, city, and region—is constructed for urban agglomerations, integrating spatial-temporal analysis, city-level two-dimensional diagnostics, and regional synergy quantification. The framework is applied to the Yangtze River Delta Urban Agglomeration (YRDUA), a national-level pilot area for the BCGs, over the period 2015–2023. Results indicate that: (1) progress toward the BCGs in the YRDUA increased by 5.7%, but full achievement by 2035 remains unlikely. Significant structural imbalances exist among the 21 goals, with infrastructure-related goals scoring higher than those related to institutional development, innovation, and carbon neutrality. Spatially, BCGs’ performance follows a “high southeast, low northwest” pattern, although distribution varied by goal, and regional equity has improved. (2) Fewer than half of the 41 cities had achieved “double high” states in both development magnitude and evenness by 2023, with cities following four distinct development pathways that reflect differing priorities and strategies for goal attainment. (3) Intercity cooperation in advancing the BCGs remains limited. Synergistic effects are relatively stronger for green production goals but weaker for ecological, technological, and institutional goals, with Ningbo, Suzhou, and Shaoxing emerging as key contributors to regional synergy. This framework offers a replicable tool for regional environmental planning and provides evidence for BCGs implementation strategies in China and beyond. Full article

Identifying the spatio-temporal evolutionary patterns and driving mechanisms of rural tourism network attention is essential for predicting the development trends of the rural tourism industry and delivering refined industrial governance. Taking 356 prefecture-level cities in China from 2015 to 2024 as basic research units, this paper constructs a comprehensive evaluation system for rural tourism network attention based on multi-source data. Furthermore, its spatio-temporal evolution characteristics and internal influencing factors are systematically investigated by means of spatial autocorrelation analysis and geographically weighted regression. The results indicate that the overall level of rural tourism network attention in China shows an obvious fluctuating growth trend, which can be divided into three successive stages, namely steady growth (from 0.8530 in 2015 to 1.2028 in 2019), explosive growth (from 1.9563 in 2020 to 3.7471 in 2021) and high-level fluctuation (maintained in the high range of 2.4–3.4). In addition, with the continuous iteration of internet communication media, the guiding influence of traditional search platforms has gradually weakened, while emerging social media and short-video platforms have become the core carriers of online tourism traffic. Correspondingly, media innovation persistently reshapes the spatial distribution pattern of rural tourism network attention. In terms of spatial characteristics, rural tourism network attention has undergone a significant transformation from geographical gradient polarization to overall regional equilibrium. Specifically, from 2015 to 2024, the overall Moran’s I index remained positive, with values ranging from 0.0116 to 0.1358, indicating an overall trend of gradual decline. High-attention areas are predominantly concentrated in economically developed urban agglomerations, whereas remote and economically underdeveloped regions exhibit contiguous low-value aggregation characteristics, which reveals a remarkable trend of balanced development nationwide. In view of driving mechanisms, highway network density, tourism income, rural tourism resource and enrollment of university students are identified as the core driving factors dominating the spatio-temporal evolution of rural tourism network attention. Moreover, the intensity of the influence of each factor presents distinct spatial heterogeneity. This study further reveals that the spatial heterogeneity of rural tourism network attention calculated using multi-source fused data shows a remarkable convergent characteristic, which can reflect the actual distribution of the rural tourism market more objectively and accurately. Meanwhile, rural tourism network attention is typically characterized by scale-dependent with the spatial distribution at the macro-scale being more balanced than that at the meso- and micro-scales. Full article

As global urban development shifts towards stock upgrading and cultural tourism consumption, historic and cultural districts have become crucial spatial carriers for reshaping local identity and driving urban regeneration. Although the literature explores cultural value, current research remains limited to macro-scale assessments, leaving a gap in micro-scale, quantitative identification of spatial narrative capacity. To address this, the concept of ontological narrative is introduced, and a three-dimensional framework integrating physical space, functional formats, and historical events is constructed. Using event space as the unit of measurement, a mixed-methods approach combining spatial syntax, kernel density estimation, and the Analytic Hierarchy Process is applied to Chaozong Street in Changsha. The findings indicate that narrative intensity exhibits a spatial pattern of main-axis agglomeration and deep-alley attenuation. High-value nodes concentrate along primary streets with high accessibility. Conversely, narrative efficacy declines in branch alleys and functionally deficient zones. Furthermore, a four-quadrant diagnosis reveals widespread structural decoupling, such as high historical value paired with low vitality. This shows that historical assets require functional activation to become effective narratives. This research provides a precise analytical tool, grounded in node diagnosis, to counter homogenized urban renewal by fostering differentiated cultural expression. Full article

Achieving coordinated development between higher education and regional economies is central to sustainable urban growth. This study examines the spatiotemporal coupling coordination between higher education and economic development across 90 cities within seven major coastal urban agglomerations in China over the period 2008–2021. An evaluation index system was constructed across seven dimensions, and three analytical methods were integrated: the entropy weight method for composite index calculation, the coupling coordination degree model for assessing synergistic development, and the panel vector autoregression (PVAR) model for dynamic interaction analysis. A fixed-effects regression model was further applied to identify key driving factors. The results indicate that: (1) higher education levels showed a steady upward trend across all agglomerations, while widening absolute disparities persisted among cities; (2) although a bidirectional Granger-causal relationship exists between higher education and economic development, the interaction is asymmetric along two distinct dimensions: higher education exerts a more statistically robust predictive influence on the economy, while unforecast economic shocks transmit more strongly to higher education than the reverse; this asymmetry manifests in specific urban agglomerations—most notably the Pearl River Delta—as a structural mismatch between economic strength and higher education development; (3) economic development level, government fiscal support, urbanization, and higher education scale are significantly associated with the coupling coordination between the two systems. These findings highlight the structural misalignment between higher education supply and regional economic demand and underscore the need for differentiated, spatially targeted policy interventions to promote sustainable regional development. Policy recommendations are proposed for optimizing higher-education resource allocation, reforming talent cultivation, and strengthening intra-agglomeration coordination mechanisms. Full article

Against the backdrop of optimizing national energy mix and advancing industrial low-carbon transformation to achieve sustainable socioeconomic development, this study adopts prefecture-level panel data covering 2005–2020 to reveal the spatiotemporal evolution law of carbon emissions generated by urban energy consumption. We systematically characterize emission disparities from three dimensions: total carbon output, per capita carbon emissions, and carbon emission intensity, and further adopt regression analysis to quantitatively identify core socioeconomic and industrial drivers behind energy-related carbon flows. The results indicate that China’s total urban energy carbon emissions kept rising over the research window with decelerating growth momentum. Driven by cross-regional industrial transfer and uneven energy resource endowments, high-emission zones gradually spread from eastern coastal agglomerations to northern and western inland territories, forming a stable spatial layout of high emissions in the east and north, and low emissions in the west and south. Per capita carbon emissions present striking regional differentiation: northwest resource-abundant provinces become concentrated high-value clusters, while populous southeast regions maintain relatively low levels, with inter-regional per capita emission gaps continuously widening. Nationwide carbon emission intensity maintained a persistent downward trend; high-intensity zones shrank markedly while low-carbon areas expanded continuously, and inter-regional efficiency gradients gradually converged, reflecting tangible achievements in nationwide energy conservation and low-carbon industrial transition. Overall, the gravity center of energy carbon emissions shifted northwestward, with Inner Mongolia, Xinjiang, and Ningxia evolving into major high-emission hotspots relying on fossil energy exploitation and heavy industrial layout. Statistical regression associations suggest that urban construction land expansion, economic expansion, foreign capital agglomeration, and industrial energy carbon outputs are positively correlated with urban carbon emissions; by contrast, commercial housing scale and domestic enterprise development present significant negative correlational links with emission levels. The differentiated spatiotemporal carbon landscape arises from the joint interplay of regional resource endowment, coal-dominated energy structure, industrial layout restructuring, and tiered low-carbon policy implementation, demonstrating China’s overall shift from high-carbon extensive industrial growth toward energy-efficient, low-carbon intensive sustainable development. This research delivers empirical evidence for formulating zoned carbon abatement schemes, optimizing regional energy allocation and industrial layouts, and advancing long-term low-carbon sustainable development to fulfill China’s carbon peaking and carbon neutrality targets. Full article