Search Results (58)

As a catalyst for sustainable urbanization, urban vibrancy drives human interactions, economic agglomeration, and resilient development through its spatial manifestation of diverse activities. While previous studies have emphasized the connection between built environment features—especially street network centrality—and urban vibrancy, the broader mechanisms through which the full spectrum of street configuration dimensions shape vibrancy patterns remain insufficiently examined. To address this gap, this study applies a GeoXAI approach that synergizes random forest modeling and GeoShapley interpretation to reveal the influence of street configuration on urban vibrancy. Leveraging multi-source geospatial data from Xiamen Island, China, we operationalize urban vibrancy through a composite index derived from three-dimensional proxies: life service review density, social media check-in intensity, and mobile device user concentration. Street configuration is quantified through a tripartite measurement system encompassing network centrality, detour ratio, and shape index. Our findings indicate that (1) street network centrality and shape index, as well as their interactions with location, emerge as the dominant influencing factors; (2) The relationships between street configuration and urban vibrancy are predominantly nonlinear, exhibiting clear threshold effects; (3) The impact of street configuration is spatially heterogeneous, as evidenced by geographically varying coefficients. The findings can enlighten urban planning and design by providing a basis for the development of nuanced criteria and context-sensitive interventions to foster vibrant urban environments. Full article

The world is characterised by the growing volumes and flow of goods, which, amid benefits to economic development, result in negative externalities affecting the sustainability of cities. Although numerous studies have analysed the locational patterns of logistics facilities in cities, further research is required to examine their real estate patterns and trends. The aim of the paper is, therefore, to analyse the value of land accommodating logistics facilities in the City of Cape Town municipality, South Africa. Given the lack of dedicated geo-spatial data, logistics firms were searched on Google Maps, utilising a combination of aerial photography and street view imagery. Three main attributes of land parcels hosting logistics facilities were thereafter captured from the municipal cadastral information: property extent, street address, and property number. The latter two were used to extract the 2018 and 2022 property market values from the valuation rolls on the municipal website, followed by statistical, spatial, and geographically weighted regression (GWR) analyses. Zones near the central business district and seaport, as well as areas with prime road-based accessibility, had high market values, while those near the railway stations did not stand out. However, GWR yielded weak relationships between market values and the locational variables analysed, arguably showing a disconnect between spatial planning and logistics planning. Towards augmenting sustainable logistics, it is recommended that relevant stakeholders strategically integrate logistics into spatial planning, and particularly revitalise freight rail to attract investment to logistics hubs with direct railway access. Full article

As ecologically sensitive interfaces shaped by the interplay of land and sea, coastal zones demand close attention. Uncovering the spatiotemporal evolution of ecosystem service value (ESV) and the intricate interrelations among ecosystem service (ES) functions is imperative for the informed governance of human–land interactions and for fostering sustainable regional development. This study analyzes the spatiotemporal evolution of ESV based on the modified equivalent factor table, combining the Geo-information Tupu, Markov transfer model, and standard deviation ellipse. Additionally, we introduce an ecosystem service tradeoff degree (ESTD) to assess the tradeoffs and synergies among various ESs, and we utilize GeoDetector to elucidate the driving forces behind the spatial disparities in ESV. Our findings reveal that (1) Although the land use composite index in the Liaoning coastal economic belt (LCEB) increased, the pace of land use transformation demonstrated a trend toward stabilization over the study duration. (2) Between 2000 to2020, ESV initially declined but subsequently experienced an upward rebound, resulting in a net gain of approximately 48 billion yuan. Spatial analysis indicated continuous enlargement of the standard deviation ellipse, with its centroid consistently located within Yingkou City and a gradual directional shift toward the southwest. (3) The dominant relationship among ESs showed synergy, with notable tradeoffs between hydrological regulation and other services. (4) Topography and climate factors were the primary drivers of spatial heterogeneity of ESV in the LCEB. The research provides spatial decision support for optimizing the ecological security pattern of the coastal zone. Full article

Pine caterpillar (Dendrolimus) infestations threaten pine forests, causing severe ecological and economic impacts. Identifying the driving factors behind these infestations is essential for effective forest management. This study uses the APCIRD framework combined with an improved random forest model to analyze spatiotemporal changes in infestation risk and the driving effects of habitat factors in Northeast China. From 2019 to 2024, we applied SHapley Additive exPlanations (SHAP), frequency analysis, fitting functions, and GeoDetector to quantify the impact of key drivers, such as snow cover and soil, on infestation risk. The findings include (1) the APCIRD framework with the MLP-random forest model (MRF) accurately assesses infestation risks. MRF is composed of MLP and random forest. Between 2019 and 2024, areas with high infestation risk declined, shifting from higher to lower levels, with Eastern Heilongjiang and Southwest Liaoning remaining as key concern areas; (2) snow cover and soil factors are critical to infestation risk, with eight key habitat factors significantly affecting the risk. Their relationships with infestation risk follow complex, non-monotonic quartic and cubic patterns; (3) factors triggering high infestation risks are mostly at low to moderate levels. High-risk areas tend to have low to moderate elevation (<800 m), moderate to high solar radiation and temperature, gentle slopes (<30°), low to moderate evaporation, shallow snow depth (<0.02), moderate snow temperature (266.73–275), low to moderate soil moisture (0.2–0.3), moderate to high soil temperature (276.73–286.92), low to moderate rainfall, moderate wind speed, low leaf area index, high vegetation type, low vegetation cover, low population density, and low surface runoff. Interactions between factors provide a stronger explanation of infestation risk than individual factors. The APCIRD framework, combined with MRF, offers valuable insights for understanding the drivers of pine caterpillar infestations. Full article

The digital economy, as a major economic form after the agricultural and industrial economies, has become a new driving force in the development of the national economy, and it may provide opportunities for rural economic development through new businesses such as the platform economy and live e-commerce. However, there may also be a risk of a digital divide, and the mechanism of its impact on shared prosperity needs to be scientifically verified. Based on the panel data of 2243 counties in China from 2011 to 2021, the article empirically examines how the digital economy promotes common prosperity among regions and the spatial spillover effects of the digital economy. The findings suggest that, first, the geographic distance matrix reveals a positive spatial relationship between the digital economy and shared prosperity, and the phenomenon of geo-graphic agglomeration is observed, which manifests itself as a high-high-low aggregation. Second, the digital economy has had an impact that transcends space, enabling counties to both “expand the cake” and “share the cake” more equitably. Third, the coordinated, inclusive, and structurally optimizing effects of the digital economy help counties achieve common prosperity by upgrading the level of public services and promoting the upgrading of industrial structure. Ultimately, the digital economy promotes the common prosperity and long-term development of county economies through innovation-driven and optimized resource allocation. Full article

With the development of new agricultural business entities in China, a complex competitive evolutionary dynamic has emerged among diversified agricultural business entities (abbreviated as ABEs), including farmers (traditional ABEs), cooperatives, agricultural enterprises, and family farms (new ABEs). Based on the Lotka–Volterra model, the dominance index, the Shannon–Wiener index of ecological theories, and the geo-detector, this study examines the spatiotemporal evolution and driving factors of ABEs’ structural changes across 286 Chinese cities from 2012 to 2021. Key findings include: (1) Farmers maintain absolute numerical dominance, but their relative advantage has declined. (2) The Shannon–Wiener index of diversified ABEs has increased significantly, indicating that differences between ABEs decreased, which means a trend toward structural homogenization. High Shannon–Wiener index values were observed in the Northeast Plain, Xinjiang, Hebei, Gansu, and Shanxi, while low values were concentrated in Yunnan, Guizhou, and the Guangdong-Guangxi region. Both areas experienced a shrinking trend. (3) Agricultural production factors such as multiple cropping indexes and theindustrial structure strongly explained the structural changes to ABEs, while the explanatory power of socio-economic factors can be enhanced after the interaction with agricultural production factors. (4) The relationship between farmers and new ABEs has shifted from a symbiotic relationship favoring farmers to a symbiotic relationship favoring new ABEs, with a significant spatial heterogenous layout among 286 cities. This study proposes a three-stage differentiation framework for ABEs: a simple structure dominated by traditional farmers, a competitive evolutionary dynamic among diversified ABEs, and a modernized structure led by new agricultural business entities. Based on these stages, this paper provides targeted recommendations for building a high-quality ABE system and advancing agricultural modernization. Full article

Large wildfires have increased in the Mediterranean region due to socio-economic and land-use changes. The most immediate and concerning consequence of the wildfires is the loss of vegetation. However, there are few studies on the relationship between wildfire and vegetation recovery, especially on the complex relationship between species composition, burn severity and geo-environmental context. This study focuses on the analysis of post-fire vegetation regrowth (RV) in Mediterranean forests. Therefore, two objectives were set: (i) to analyse the influence of pre-fire conditions, burn severity and topographic variables on growth rates for each stage of recovery and (ii) to identify the drivers of post-fire vegetation recovery. The results show that NDVI increases rapidly in the first two years after the wildfire and more slowly in the following years. Except for the first year, RV shows a positive relationship with burn severity. In the first year, the importance of topographical features, especially curvature and flow accumulation, stands out. In the fourth year, when NDVI values are highest, RV is mainly explained by the presence of pre-fire vegetation, followed by burn severity and altitude. These results can be an important step towards more effective local management strategies leading to a resilient and sustainable territory. Full article

International market openness has long been regarded as critical for economic development, and recent evidence highlights the distinct roles of financial and trade openness, particularly in emerging and developing economies. This study examines the impact of financial and trade openness on economic growth in ten emerging and developing countries from 1970 to 2023. It employs a dynamic panel generalized method of moments (GMM) model, which is selected for its ability to address potential endogeneity and dynamic relationships within panel data. The analysis finds that both financial and trade openness positively influence economic growth and that stable macroeconomic conditions and political stability enhance these growth-promoting effects. In the context of growing geo-economic tensions, trade fairness, and national security concerns, the study underscores the need for policies that balance global integration with national interests. These findings suggest the importance of designing policies that promote greater integration into global financial and trading systems while ensuring sound macroeconomic fundamentals and supportive institutions. The study recommends that policymakers pursue strategic liberalization and strengthen governance structures to achieve sustained and inclusive growth. Full article

Terrestrial ecosystems are vital carbon sinks that can effectively restrain the rise in CO₂ in the atmosphere. How ecosystem carbon storage (CS) in semi-arid watershed areas with slow urbanization is affected by comprehensive factors of the environment and land use, along with its temporal and spatial changes has still not been fully explored. Notably, there is a paucity of research on the temporal and spatial changes and development trends of CS in the rapid deformation belt of slopes from the eastern margin of the Qinghai–Tibet Plateau to the Loess Plateau. Taking Bailong River Basin (BRB) as an example, this study combined GeoSOS-FLUS, the InVEST model, and localized “social–economic–nature” scenario to simulate the long-term dynamic evolution of CS. The aim was to study how topographic factors and land use change, and their interactions impact carbon sinks and gradient effects in steep-slope areas, and then find out the relationship between carbon sinks and topographic factors to explore strategies to improve regional carbon sink capacity. The results showed that the following: (1) CS in BRB increased year by year, with a total increase of 558 tons (3.19%), and showed significant spatial heterogeneity, mainly due to the conversion of woodland and arable land; (2) except for land use type, the relationship between CS and topographic gradient is inverted U-shaped, showing a complex spatial response; and (3) it is estimated that by 2050, under the arable land protection and natural development scenarios, CS will decrease by 0.07% and 0.005%, respectively, encroachment on undeveloped mountain areas, while the ecological protection scenario gives priority to protecting the carbon sinks of woodland and grassland, and CS will increase by 0.37%. This study supports the implementation of targeted ecological protection measures through topographic gradient zoning, provides a reference for policy makers in similar topographic regions to effectively manage the spatial heterogeneity of CS, and helps further strengthen global and regional climate change mitigation efforts. Full article

The study evaluates the interest of business-educated Gen Z in pursuing careers in various industries and their potential to accelerate Green Innovation (GI). It specifically focuses on Gen Z in Europe, who are business-educated and pursuing their career in different industry sectors, and aiming to address climate change and sustainable practices. By adopting Green Entrepreneurial Orientation (GEO) and building Absorptive Capacity (AC), companies can significantly contribute to improving Environmental Orientation (EO) by appealing to Gen Z—their future employees and customers. The study aims to survey 280 business-educated Gen Z people in Europe. The findings of the study show that the relationship between absorptive capacity and environmental orientation is not always significant, and the impact can be negligible, specifically when the firms have a low commitment to environmental strategies and have a limited strategic emphasis on sustainable practices. The study aims to encourage innovation and sustainable growth among firms, opening the door to a more sustainable future and attracting goodwill from environmentally oriented Generation Z. The publication/article presents the results of the project financed from the subsidy granted to the Krakow University of Economics. Full article

The geographical environment and economic conditions that influence the spatial distribution of minority villages vary significantly, particularly in mountainous regions where they face different levels of disaster risks. Environmental suitability assessment can help us gain a deeper understanding of the differences and degrees of differences among different villages and provide a basis for resource allocation and planning. This study focuses on 499 national level and 68 provincial level minority villages in Fujian province and evaluates the environmental suitability of their spatial distribution using analysis tools such as ArcMap and GeoDetector. The research findings indicated: (1) The ratio between the influence strengths of natural geographical, socioeconomic, and disaster constraint indicators on the environmental suitability of minority villages in mountainous areas is 5:10:7, with the highest influence being the regional gross domestic product (RGDP) in the socioeconomic indicator (0.509) and the lowest influence being flood sensitivity (0.011). (2) Areas with high suitability values are in the southeast coastal and central regions. From east to west, the suitability values gradually decrease. The suitable areas cover 87.2% of the total region, including 91.9% of the minority villages. (3) The geographical correlation coefficient between the spatial distribution of minority villages and environmental suitability is 86.87, indicating a high degree of spatial interaction and fit between the two. This validates the rationality of the multi-factor evaluation model for assessing the environmental suitability of ethnic village spatial distribution in mountainous areas. (4) There is an inverse “U” relationship between environmental suitability and the distribution of national and provincial level minority villages. With the increase in the suitability index, the number of national level minority villages tends to increase, while the number of provincial level minority villages tends to decrease. The research findings have significant implications for promoting the sustainable development of minority villages in Fujian province and provide reference for the regional development and protection of minority villages in other mountainous areas. Full article

As a vital part of the geo-environment and water cycle, ecosystem health and human development are dependent on water resources. Water supply and demand are influenced significantly by land use and cover change (LUCC) which shapes the surface ecosystems by altering their structure and function. Under future climate change scenarios, LUCC may greatly impact regional water balance, yet the impact is still not well understood. Therefore, examining the spatial relationship between LUCC and water yield services is crucial for optimizing land resources and informing sustainable development policies. In this study, we focused on the Hanjiang River Basin and used the patch-generating land use simulation (PLUS) model, coupled with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, to assess water yield services under three Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. For the first time, we considered the impact of future changes in socio-economic and water use indicators on water demand using correction factors and ARIMA projections. The relationship between water supply and demand was explored using this approach, and LUCC’s effects on this balance are also discussed. Results indicate that: (1) The patterns of LUCC are similar for the three scenarios from 2030 to 2050, with varying levels of decrease for cropland and significant growth of built-up areas, with increases of 6.77% to 19.65% (SSP119), 7.66% to 22.65% (SSP245), and 15.88% to 46.69% (SSP585), respectively, in the three scenarios relative to 2020; (2) The future supply and demand trends for the three scenarios of produced water services are similar, and the overall supply and demand risks are all on a downward trend. Water demand continues to decline, and by 2050, the water demand of the 3 scenarios will decrease by $96.275\times {10}^8\mathrm{t}$, $81.210\times {10}^8\mathrm{t}$, and $84.13\times {10}^8\mathrm{t}$ relative to 2020, respectively; while supply decreases from 2030 to 2040 and rises from 2040 to 2050; (3) Both water supply and demand distributions exhibit spatial correlation, and the distribution of hotspots is similar. The water supply and demand are well-matched, with an overall supply-demand ratio greater than 1.5; (4) LUCC can either increase or decrease water yield. Built-up land provides more water supply compared to other land types, while forest land has the lowest average water supply. Limiting land use type conversions can enhance the water supply. Full article

Human actions have led to consistent and profound alterations in land use, which in turn have had a notable effect on the services provided by ecosystems. In this research, the Google Earth Engine (GEE) was initially employed to perform a supervised classification of Landsat satellite images from 2000 to 2020, which allowed us to obtain land-use data for Putian City, China. Next, the geo-informatic Tupu model and the revised valuation model were used to explore the spatial attributes and ecological effects of land-use changes (LUCs). Subsequently, EEH (eco-economic harmony), ESTD (ecosystem services tradeoffs and synergies degree index), and ESDA (exploratory spatial data analysis) methods were employed to further analyze the coordination level, trade-offs, synergies, and spatial patterns of ecological-economic system development. The findings revealed that: (1) The land-use composition in Putian City was predominantly cultivated land and forest land, with other types of land intermixed. Concurrently, there was an ongoing trend of expansion in urban areas. (2) ESV in Putian City exhibited an upward trend, increasing from 15.4 billion CNY to 23.1 billion CNY from 2000 to 2020. (3) ESV exhibited an imbalance in spatial distribution, with high-high agglomeration areas concentrated in the central part of Putian City and the coastal region of Hanjiang District, while low-low agglomeration areas were prevalent in Xianyou County in the southwest, Xiuyu District along the coast, and Licheng District in the urban center. (4) Synergistic relationships among ESs predominated, though the trade-off relationship showed a tendency to expand. (5) The ecological environment and economic progress in Putian City collectively faced a region of potential risk. The findings of this study are intended to serve as a guide for improving the distribution of land resources and for developing strategies that ensure the sustainable development of the region’s socio-economic framework. Full article

While the benefits of land-use mix have been widely analyzed with regard to transportation, public health, and economic development, relatively little attention has been paid to empirically investigating the impact of land-use mix on technological innovation at the intra-urban level. Drawing upon a database of geo-coded patents that are used to reflect the capacity of technological innovation, this paper takes Shanghai as a case study and analyzes how the intra-urban distribution of technological innovation has been associated with land-use mix at the 1 km × 1 km grid cell level. Empirical results, which are robust when the grids are divided at the 2 km × 2 km level, show that the degree of land-use mix is positively associated with the number of patents for a given grid, suggesting that grids with a higher level of land-use mix are likely to have more patents, ceteris paribus. Moreover, the results demonstrate an inverted U-curve relationship between land-use mix and technological innovation, indicating that a too much higher level of land-use mix could lead to a smaller number of patents for a certain grid. In addition, the empirical results suggest the existence of spatial dependence in the effect of land-use mix on technological innovation. Full article

Clarifying the spatio-temporal patterns of ecosystem services trade-off/synergy relationships (ESTSs) and their attribution in the Yellow River Basin is crucial to constructing ecological civilization in China. This study first analyzed the spatio-temporal change of ecosystem services (ESs) including the water yield, soil conservation, carbon sequestration, and habitat quality in the Yellow River Basin during 2000–2020 based on the InVEST and RUSLE models. Then, the spatial autocorrelation methods were used to quantify the spatio-temporal differentiation of ESTSs, and the Geo-detector method was employed to identify the contributions of driving factors associated with the natural, social-economic, and regional policy aspects of the ESTSs. Finally, the random forest and analysis of variance methods were used to validate the reasonability of major driving factors obtained by the Geo-detector. The main findings include: (1) In 2000–2020, water yield, soil conservation, and habitat quality increased, and carbon sequestration decreased. The ESs had a spatial pattern of high in the east and low in the west. (2) Overall, there were synergistic relationships between the four Ess. In the spatial distribution of ESTSs, the expansion of the synergy zone and trade-off zone occupied the majority. The synergy zones tended to be concentrated in the northwest and southeast of the study area. In contrast, the trade-off zones were more scattered than the synergy zone, mainly focused on the east-central and southwestern parts of the Yellow River Basin. (3) Geo-detector and random forest both showed that natural factors had a strong explanatory power on ESTSs, in which NDVI is a key driver. Both the results of Geo-detector and the analysis of variance showed that the interactions between natural factors exerted the most significant influence on ESTSs, followed by the interaction between natural factors and socio-economic factors. Full article