Search Results (324)

Research on commuting patterns has mainly focused on urban and metropolitan areas, and such studies are not typically applied to rural and small-town regions, where workers often face longer commutes due to limited job opportunities and inadequate public transportation. By using the Census Transportation Planning Package (CTPP) data, this research fills that gap by analyzing commuting behavior by ethnic group and industry in south-central Minnesota, which is a predominantly rural area of 13 counties in the United States. The results show that both white and minority groups in District 7 experienced an increase in excess commuting from 2006 to 2016, with the minority group in Nobles County showing a significantly higher rise. Analysis by industry reveals that excess commuting in the leisure and hospitality sector (including arts, entertainment, and food services) in Nobles County increased five-fold during this time, indicating a severe spatial mismatch between jobs and affordable housing. In contrast, manufacturing experienced a decline of 50%, possibly indicating better commuting efficiency or a loss of manufacturing jobs. These findings can help city and transportation planners conduct an in-depth analysis of rural-to-urban commuting patterns and develop potential solutions to improve rural transportation infrastructure and accessibility, such as promoting telecommuting and hybrid work options, expanding shuttle routes, and adding more on-demand transit services in rural areas. Full article

Consumer-accessible and user-friendly smart products such as unmanned aerial vehicles (UAVs), or drones, have become widely used, adaptable, and acceptable devices to observe, assess, measure, and explore urban and natural environments. A drone’s relatively low cost and flexibility in the level of expertise required to operate it has enabled users from novice to industry professionals to adapt a malleable technology to various disciplines. This review examines the academic literature and maps how drones are currently being used in 93 rural and regional city councils in New South Wales, Australia. Through a systematic review of the academic literature and scrutiny of current drone use in these councils using publicly available information found on council websites, findings reveal potential uses of drone technology for local governments who want to engage with smart technology devices. We looked at how drones were being used in the management of the council’s environment; health and safety initiatives; infrastructure; planning; social and community programmes; and waste and recycling. These findings suggest that drone technology is increasingly being utilised in rural and regional areas. While the focus is on rural and regional New South Wales, a review of the academic literature and local council websites provides a snapshot of drone use examples that holds global relevance for local councils in urban and remote areas seeking to incorporate drone technology into their daily practice of city, town, or region governance. Full article

Urban air pollution remains a significant environmental and public health issue, especially in European coastal cities such as Klaipėda. However, there is still a lack of local-scale knowledge on how land use structure influences pollutant distribution, highlighting the need to address this gap. This study addresses this by examining the spatial distribution of nitrogen dioxide (NO₂) concentrations in Klaipėda’s seaport city and several inland and coastal resort towns in Lithuania. The research specifically asks how different land cover types and demographic factors affect NO₂ variability and population exposure risk. Data were collected using passive sampling methods and analyzed within a GIS environment. The results revealed clear air quality differences between industrial/port zones and greener resort areas, confirmed by statistically significant associations between land cover types and pollutant levels. Based on these findings, a Land Use Pollution Pressure index (LUPP) and its population-weighted variant (PLUPP) were developed to capture demographic sensitivity. These indices provide a practical decision-support tool for sustainable urban planning, enabling the assessment of pollution risks and the forecasting of air quality changes under different land use scenarios, while contributing to local climate adaptation and urban environmental governance. Full article

Small towns in mountainous regions face significant challenges in formulating effective landscape zoning strategies due to pronounced landscape fragmentation, which is driven by both the dominance of large-scale forest resources and the lack of coordination between administrative planning departments. To tackle this problem, this study focused on Yuqian, a quintessential small mountainous town in Hangzhou, Zhejiang Province. The town’s layout was divided into a grid network measuring 70 m × 70 m. A two-step cluster process was employed using ArcGIS and SPSS software to analyze five landscape variables: altitude, slope, land use, heritage density, and visual visibility. Further, eCognition software’s semi-automated segmentation technique, complemented by manual adjustments, helped delineate landscape character types and areas. The overlay analysis integrated these areas with administrative village units, identifying four landscape character types across 35 character areas, which were recategorized into four planning and management zones: urban comprehensive service areas, agricultural and cultural tourism development areas, industrial development growth areas, and mountain forest ecological conservation areas. This result optimizes the current zoning types. These zones closely match governmental sustainable development zoning requirements. Based on these findings, we propose integrated landscape management and conservation strategies, including the cautious expansion of urban areas, leveraging agricultural and cultural tourism, ensuring industrial activities do not impact the natural and village environment adversely, and prioritizing ecological conservation in sensitive areas. This approach integrates spatial and administrative dimensions to enhance landscape connectivity and resource sustainability, providing key guidance for small town development in mountainous regions with unique environmental and cultural contexts. Full article

Since the early 21st century, urban shrinkage has become a significant global phenomenon. Dongguan, in Guangdong Province, China, is known as a “world factory”. It experienced notable urban shrinkage following the 2008 financial crisis. However, the city demonstrated remarkable recovery and ongoing development in subsequent years. On that basis, this study focuses on the following three points: (1) identifying the spatiotemporal factors contributing to the growth and shrinkage of manufacturing cities, taking Dongguan as an example; (2) explaining the influencing factors of the growth and shrinkage of Dongguan City during three critical periods, 2008–2014 (post-crisis), 2015–2019 (as machinery replaced human work), and 2020–2023 (the COVID-19 pandemic and recovery); and (3) selecting representative towns and streets for on-site observation and investigation, analyzing the measures they have taken to cope with growth and shrinkage during different periods. The key findings include the following: (1) The spatial dynamics of growth and shrinkage in Dongguan show significant temporal patterns, with traditional manufacturing areas shrinking from 2008 to 2014, central urban areas recovering from 2015 to 2019, and renewed shrinkage from 2020 to 2023. However, some regions maintained stability through strategic innovations. (2) Various factors, particularly industrial upgrading and technological innovation, drove the urban dynamics, enhancing economic resilience. (3) The case study of Houjie Town revealed successful adaptive mechanisms supported by policy while facing challenges like labor mismatches and inadequate R&D investment. This research offers insights for improving urban resilience and promoting sustainable development in Dongguan. Full article

The equitable allocation of clean energy access across towns–rural divides is a critical benchmark of modernization in developing economies. This is because it is intricately linked to the realization of strategic goals such as shared prosperity, ecological civilization advancement, and national energy security reinforcement. This research examines the impact of China’s digital village (DV) construction in reducing the urban–rural disparity in household clean energy access, evaluates the effect on towns–rural clean energy consumption inequality (CEI), explores the mediating mechanisms, and considers regional heterogeneity. It is an innovative approach to test the influence of digital village construction on clean energy consumption inequality between urban and rural areas, beyond which conventional research is limited to infrastructure investment and policy considerations. We can reach the following three results: (1) With the continuous improvement of digital village construction, CEI between towns and rural areas shows an “inverted U-shaped” change. (2) From the perspective of the intermediary mechanism, agricultural technological progress (ATP) and industrial structure upgrading (IND) can facilitate digital village construction and reduce the disparity in clean energy consumption between towns and rural regions. (3) From the perspective of heterogeneity analysis, digital village construction in areas with low urbanization levels, high terrain undulation, and non-clean energy demonstration provinces can significantly alleviate CEI. It is on this basis that the present paper proposes a policy recommendation for the Chinese government to effectively reduce the gap between towns and rural clean energy consumption in the process of digital village construction. Full article

The sharp decline in the population along the northeastern border poses a significant threat to the security of the region, the prosperity of border areas, and the stability of the social economy in our country. Effective management of human and land resources is crucial for the high-quality development of border areas. Taking Changbai County on the northeastern border as an example, based on multi-source data such as land use, the natural environment, climate conditions, transportation location, and social economy from 2000 to 2020, the land use transfer matrix, spatial kernel density, and PLUS model were used to analyze the spatio-temporal evolution characteristics of land use and explore simulation scenarios and optimization strategies under different planning concepts. This study reveals the following: (1) During the study period, the construction land continued to increase, but the growth rate slowed down, mainly transferred from cultivated land and forest land, and the spatial structure evolved from a single center to a double center, with the core always concentrated along the border. (2) The distance to the port (transportation location), night light (social economy), slope (natural environment), and average annual temperature (climate conditions) are the main driving factors for the change in construction land, and the PLUS model can effectively simulate the land use trend under population contraction. (3) In the reduction scenario, the construction land decreased by 1.67 km², the scale of Changbai Town slightly reduced, and the contraction around Malugou Town and Badagou Town was more significant. The study shows that the reduction scenario is more conducive to the population aggregation and industrial carrying capacity improvement of shrinking county towns, which is in line with the high-quality development needs of border areas in our country. Full article

This study investigates the complex dynamics of new-type urbanization in resource-based county-level cities, using Wuan City in Hebei Province, China, as a representative case. As China pursues a high-quality development agenda, cities historically dependent on resource extraction face profound challenges in achieving sustainable and inclusive urban growth. This research employs a multi-method approach—including Theil index analysis, industrial shift-share analysis, a Cobb–Douglas production function model, and a composite urbanization index—to quantitatively diagnose the constraints on Wuan’s development and assess its transformation efforts. Our empirical results reveal a multifaceted situation: while the urban–rural income gap has narrowed, rural income streams remain fragile. The shift-share analysis indicates that although Wuan’s traditional industries have regained competitiveness, the city’s economic structure is still burdened by a persistent negative structural component, hindering diversification. Furthermore, the economy exhibits characteristics of a labor-intensive growth model with inefficient capital deployment. These underlying issues are reflected in a comprehensive urbanization index that, after a period of rapid growth, has recently stagnated, signaling the exhaustion of the city’s traditional development mode. In response, Wuan attempts an “industrial transformation-driven new-type urbanization” path. This study details the three core strategies being implemented: (1) incremental population urbanization through development at the urban fringe and in industrial zones; (2) in situ urbanization of the existing rural population; and (3) the cultivation of specialized “characteristic small towns” to create new, diversified economic nodes. The findings from Wuan offer critical, actionable lessons for other resource-dependent regions. The case demonstrates that successful urban transformation requires not only industrial upgrading but also integrated, spatially aware planning and robust institutional support. We conclude that while Wuan’s model provides a valuable reference, its strategies must be adapted to local contexts, emphasizing the universal importance of institutional innovation, human capital investment, and a people-centered approach to achieving resilient and high-quality urbanization. Full article

In response to the global goal of carbon neutrality, the tourism industry faces mounting pressure to reduce emissions. Characteristic towns that rely on traditional, high-emission models urgently require low-carbon tourism transformation strategies to meet environmental targets while preserving cultural heritage and economic vitality. This study investigates the low-carbon transition pathways of tourism in characteristic towns, using the three-dimensional impact mechanism of tourists, residents, and enterprises as a conceptual entry point. Drawing on empirical research conducted in Zhouzhuang and Tongli—two ancient towns in Suzhou—the study identifies key drivers and barriers to the development of low-carbon tourism. Results indicate that the overall low-carbon transformation score for Suzhou’s characteristic towns is 63.3, suggesting a moderate level of progress. Specifically, Zhouzhuang scored 66.9, while Tongli lagged behind at 57.6, highlighting notable disparities in transition efforts. The study applies multi-agent game theory and system dynamics to analyze the interactive mechanisms among tourists, residents, and enterprises in the low-carbon transition. Our findings reveal that tourists’ low-carbon consumption behaviors, residents’ environmental awareness, and enterprises’ green investments significantly influence the transition process. Further analysis using a chain mediation model shows that policy support positively affects low-carbon outcomes by promoting enterprise investment and influencing resident behavior. The study’s innovation lies in its development of an integrated analytical framework that captures the dynamic interplay among multiple stakeholders, offering a comprehensive perspective on low-carbon tourism transformation in characteristic towns. This study contributes to the sustainable tourism literature and provides valuable insights for policymakers and practitioners working toward carbon neutrality in tourism destinations. Full article

Ensuring the healthy movement of urban and rural factors is a key aspect in promoting urban–rural integration. Defining the mechanisms of factor movement and constructing an urban–rural integration planning model are important for the practice of urban–rural integration work. This study considers the movement of urban and rural factors as its entry point and explores the resource endowments and movement paths of urban and rural factors based on the city–town–village spatial system. The urban–rural integration planning model was constructed using spatial and policy dimensions, and six integration design strategies for ecological, population, industrial, land, transportation, and public service factors were defined. Next, considering the Xiuzhou District of Jiaxing City as a case study, this study combines the current characteristics and integration directions of urban and rural factors to propose integration design goals and measures for six key factors. The movement paths of urban and rural factors were delineated, and the specific tasks of each administrative entity in urban–rural integration development were identified at each level to achieve the breakdown and transmission of the overall urban–rural integration strategy. The study integrated current status assessment, integration design, path construction, and goal breakdown, exploring the formulation of urban–rural integration strategies and work pathways. The aim was to address the current gap between urban–rural integration theory and practice, thus providing a reference and inspiration for related research. Full article

The gridded spatial distribution data of Gross Domestic Product (GDP) has a wide range of application values in many fields, such as regional economic analysis, urban planning, sustainable utilization of resources, and disaster risk assessment. However, currently the publicly accessible GDP grid datasets face limitations in terms of temporal coverage, spatial extent, and accuracy. Therefore, based on the remote sensing data of land use and nighttime light, this study developed two methods: the factor averaging method (FAM) and grid averaging method (GAM), and used Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) algorithms to jointly construct the spatial model of GDP, so as to produce China’s 1 km gridded GDP in 2020. The experimental results show the following: (1) The GAM yields higher R² values than the FAM in modeling the three industries, and therefore, it is adopted as the basis for GDP spatialization modeling. (2) XGBoost achieves higher R² values than RF in modeling primary and secondary industries, but lower R² values in modeling tertiary industry. Consequently, both methods are combined to construct the overall GDP spatialization model. (3) The accuracy of the GDP spatialization results is evaluated based on town-level GDP statistics, with an R² value of 0.78, indicating its reliable predictive capability. (4) Compared with publicly available GDP datasets, our dataset exhibits consistent spatial distribution patterns and aggregation trends. Furthermore, our GDP dataset provides a more detailed depiction of variations within county-level administrative units. Therefore, the method proposed in this study offers a valuable option for generating a gridded GDP dataset, visually displaying the uneven economic development across various regions in China. It helps to uncover economic disparities among regions and provides data support for formulating differentiated support policies, so as to promote balanced regional development among regions. Furthermore, it contributes to promoting sustained, inclusive, and sustainable economic growth (SDG 8) and reducing inequalities within and among countries (SDG 10), thereby providing strong support for urban planning and sustainable development. Full article

This study explores the spatiotemporal distribution and formation mechanisms of urban heat islands (UHIs) in Nanjing during summer, utilizing temperature data from 82 automatic weather stations (AWSs) distributed across five concentric zones. The results demonstrate the substantial impact of urbanization on UHI patterns, with industrial and densely populated areas exhibiting higher UHI intensity (UHII), while regions with natural landscapes such as mountains and water bodies display lower temperatures. The analysis reveals that the most pronounced night-time UHI effect occurs in the highly urbanized central zones, whereas the weakest effect is observed during midday. Transitional UHI phases are identified around sunrise and sunset, with increased long-wave radiation post-sunset amplifying the UHI effect. Additionally, this study underscores the directional characteristics of UHI distribution in Nanjing. Notably, Hexi New Town has emerged as a new high-temperature hotspot due to rapid urbanization, while Jiangning New Town and Xianlin Sub-City maintain lower temperatures owing to their proximity to agricultural and forested areas. By selecting representative AWSs from different zones, this study introduces a novel and practical method for calculating UHII. Although the approach has limitations in precision, it provides an accessible tool for UHI analysis and can be adapted for use in other cities. This research offers valuable insights into the influence of urban development on local climate and presents a practical framework for future UHI studies and urban planning strategies aimed at mitigating UHI effects. Full article

Sequencing batch reactor Grundfos technology (SBR-GT) system efficiently treats municipal and selected industrial wastewater, designed for small and medium-scale facilities. It offers advanced solutions for biodegradable wastewater, including municipal and food industry effluents. Important features include stable sedimentation under fluctuating influent conditions, no need for sludge recirculation, and full process automation. The system uses a static decanter and constant chamber filling for optimal oxygenation efficiency and reduced costs. The system uses a static decanter and constant chamber filling for optimal oxygenation efficiency and reduced costs. It is ideal for small settlements with variable inflow, such as towns, allowing flexible operation and cost-effective maintenance. Implementations showed stable parameters for COD (chemical oxygen demand), BOD5 (biochemical oxygen demand), total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP) and up to 99% pollutant reduction, demonstrating high effectiveness in regular and stormwater conditions. Using multivariate multiple linear regression, significant relationships were identified. A multiple regression analysis revealed a strong relationship between water quality parameters. Total suspended solids, Total nitrogen, and Total phosphorus collectively and significantly influenced both chemical oxygen demand and biochemical oxygen demand (p < 0.01 for all). The models explained a high proportion of variance, with R² values of 0.99 for COD and 0.93 for BOD5 (p < 0.001 for both). Specifically, TSS had a strong positive effect on COD (p < 0.001), while TN and TP also significantly affected COD (p < 0.01). Although the overall BOD5 model was highly significant, the individual effects of TSS, TN, and TP on BOD5 were not statistically significant in this model. This method demonstrated high effectiveness in both regular and stormwater conditions, enhancing overall treatment performance. Full article

Mangrove ecosystems effectively sequester heavy metals, making their sediment distribution and ecological risk assessment vital for coastal protection. This study focuses on the mangrove forests on both sides of the Donghai Island embankment in Huguang Town, Zhanjiang Bay, analyzing the content, spatial distribution, and potential ecological risks of heavy metals (Cu, Zn, Cd, Pb, Cr, As, Hg) in surface and vertical sediment profiles through systematic sampling. The results show higher, more uniform heavy metal concentrations inside the bay, with Cd, Cr, and As showing significant accumulation, while outside, levels are lower but with Pb and As at sites like DW-Z-1 and DW-Z-4 nearing Class I Marine Sediment Quality Guideline limits. Vertically, concentrations inside the bay increase with depth due to long-term pollution, geoaccumulation and potential ecological risk indices, Cd emerges as the primary pollutant, posing a high risk (Er Class 3) inside the bay (RI Class 2) and a low to moderate risk outside. Pollution sources inside stem from industrial, urban, and aquaculture inputs, while tidal dynamics and mangroves pose purification mitigate risks outside. This study underscores Cd control needs and supports the ecological conservation of Zhanjiang Bay. Full article

In light of the current global challenges, such as climate change, the overexploitation of natural resources, and increasing food demand, drought-tolerant forage crops present substantial potential for development in dryland regions. However, there is a notable gap in research that integrates yield improvement, nutritional quality enhancement, and resistance to pests and diseases in the production of forage crops in semi-arid areas. Therefore, selecting oat forage varieties that exhibit high yield, superior quality, and enhanced pest resistance can substantially advance the forage industry and animal husbandry in semi-arid regions. In this study, ten oat varieties, including both domestic and international cultivars, were cultivated in a semi-arid region (Weiqi town, Gansu Province) during the 2023–2024 growing season. A comprehensive analysis was performed to assess the yield, quality, and pest resistance of these varieties. All ten oat varieties successfully completed their growth cycles. Among them, Everleaf 126 exhibited a shorter plant height compared to the other varieties, measuring 103.32 cm and 115.14 cm over two years. However, its superior leaf area and tiller number led to the highest hay yields (11,819.33 kg/ha and 13,550.67 kg/ha) and seed yields (4913.20 kg/ha and 5242.33 kg/ha). Additionally, Everleaf 126 demonstrated significantly higher leaf–stem ratios (0.35 and 0.41), crude protein content (8.52% and 9.13%), and crude fat content (2.19% and 2.69%) relative to other oat varieties (p < 0.05). Furthermore, it showed the best resistance to powdery mildew (MR), red leaf disease (HR), leaf spot disease (MR), and aphids (R). The plant height of Kona was the lowest, measuring 81.22 cm and 87.16 cm, respectively, with the fewest number of tillers and the smallest leaf area. Baler II exhibited the lowest hay yield at 8770.10 kg/ha and 7898.33 kg/ha, as well as the lowest seed yield at 3409.33 kg/ha and 3323.90 kg/ha. Kona also had the lowest leaf–stem ratio (0.19 and 10.13) and crude protein content (5.74% and 6.58%), while exhibiting the highest neutral detergent fiber (NDF) and acid detergent fiber (ADF) values. Furthermore, Kona showed the poorest resistance to powdery mildew (MS) and leaf spot (MS). Finally, based on the comprehensive evaluation analysis of the membership function, in the semi-arid region, Everleaf 126 achieved the highest overall performance based upon a comprehensive evaluation, followed by Molasses and Longyan No.3. In comparison, Kona received the poorest performance. Full article