Search Results (1,376)

Corydalis yanhusuo W. T. Wang, commonly known as Yanhusuo, is an important and rare medicinal plant resource in China. Its habitat integrity is facing severe challenges due to climate change and human activities. Establishing an integrative quality zoning system for this species is of significant practical importance for resource conservation and adaptive management. This study integrates multiple data sources, including 121 valid distribution points, 37 environmental factors, future climate scenarios (SSP126 and SSP585 pathways for the 2050s and 2090s), and measured content of tetrahydropalmatine (THP) from 22 sampling sites. A predictive framework for habitat suitability and spatial distribution of effective components was constructed using a multi-model coupling approach (MaxEnt, ArcGIS spatial analysis, and co-kriging method). The results indicate that the MaxEnt model exhibits high prediction accuracy (AUC > 0.9), with the dominant environmental factors being the precipitation of the wettest quarter (404.8~654.5 mm) and the annual average temperature (11.8~17.4 °C). Under current climatic conditions, areas of high suitability are concentrated in parts of Central and Eastern China, including the Sichuan Basin, the middle–lower Yangtze plains, and coastal areas of Shandong and Liaoning. In future climate scenarios, the center of suitable areas is predicted to shift northwestward. The content of THP is significantly correlated with the mean diurnal temperature range, temperature seasonality, and the mean temperature of the wettest quarter (p < 0.01). A comprehensive assessment identifies the Yangtze River Delta region, Central China, and parts of the Loess Plateau as the optimal integrative quality zones. This research provides a scientific basis and decision-making support for the sustainable utilization of C. yanhusuo and other rare medicinal plants in China. Full article

As the fundamental physical carrier for human production and socio-economic endeavors, enhancing urban land green use efficiency (ULGUE) is crucial for realizing sustainable development. To effectively enhance urban land green use efficiency, this study systematically examines the intrinsic relationship between industrial policies and ULGUE based on panel data from 286 Chinese cities (2010–2022), employing an integrated methodology that combines the Difference-in-Differences (DID) model, Super-Efficiency Slacks-Based Measure Data Envelopment Analysis model, and ArcGIS spatial analysis techniques. The findings clearly demonstrate that the establishment of the “Made in China 2025” pilot policy significantly improves urban land green use efficiency in pilot cities, a conclusion that endures following a succession of stringent evaluations. Moreover, studying its mechanisms suggests that the pilot policy primarily enhances urban land green use efficiency by promoting industrial upgrading, accelerating technological innovation, and strengthening environmental regulations. Heterogeneity analysis further indicates that the policy effects are more significant in urban areas characterized by high manufacturing agglomeration, non-provincial capital/non-municipal status, high industrial intelligence levels, and less sophisticated industrial structure. This research not only provides valuable policy insights for China to enhance urban land green use efficiency and promote high-quality regional sustainable development but also offers meaningful references for global efforts toward advancing urban sustainability. Full article

At the Politecnica Salesiana University (UPS) in Guayaquil, Ecuador, urban mobility challenges were addressed with the aim of improving students’ quality of life and promoting sustainability. This study evaluated the technical, economic, and social feasibility of implementing a shared transportation (carpooling) system using a quantitative-descriptive approach. Surveys were applied to a stratified sample of 256 students to analyze transportation habits. Route planning was performed using ArcGIS software, and costs were calculated with Microsoft Excel. Social impact assessment involved focus groups and analysis of variables such as changes in mobility patterns, system acceptance, and perceived safety, comfort, and accessibility. Key indicators included the percentage of students willing to participate in the pilot (82.7%), satisfaction with travel time savings (85.7% fully satisfied), and positive perceptions of safety and comfort. The results suggest that the proposed system is not only economically viable but also widely accepted by students, contributing to reduced stress, travel time, and single-occupancy vehicle use. This study demonstrates the feasibility of shared transport in urban universities and provides a replicable model to guide sustainable mobility policies that improve safety, comfort, and efficiency in student commuting. Full article

As an integral component of humanity’s cultural heritage, traditional villages universally confront challenges such as population loss and cultural discontinuity amid rapid urbanization. Cluster-based protection models have increasingly become the international consensus for addressing the survival crisis of such settlements. This study selects the Central Yunnan region of Southwest China—characterized by its complex geography and multi-ethnic habitation—as the research area. Employing ArcGIS spatial analysis techniques alongside clustering algorithms, we examine the spatial distribution characteristics and clustering patterns of 251 traditional villages within this region. The findings are as follows. In terms of spatial distribution, traditional villages in Central Yunnan are unevenly dispersed, predominantly aggregating on mid-elevation gentle slopes; their locations are chiefly influenced by rivers and historical courier routes, albeit with only indirect dependence on waterways. Regarding single-cluster attributes, the spatial and geomorphological features exhibit a composite “band-and-group” pattern shaped by river valleys; culturally, two dominant modes emerge—“ancient-route-dependent” and “ethnic-symbiosis”—reflecting an economy-driven cultural mechanism alongside latent marginalization risks. Concerning construction characteristics, the “Qionglong-Ganlan” and Han-style “One-seal” residential features stand out, illustrating both adaptation to mountainous environments and the cumulative effects of historical culture. Based on these insights, we propose a three-tiered clustering classification framework—“comprehensive-element coordination”, “feature-led”, and “potential-cultivation”—to inform the development of contiguous and typological protection strategies for traditional villages in highland, multi-ethnic regions. 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

Sensorimotor integration along the gastrointestinal (GI) tract is crucial for normal gut function yet remains poorly understood in the context of neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD). The genetic tractability of zebrafish allows investigators to generate molecularly defined models that provide a means of studying the functional circuits of digestion in vivo. Optical transparency during development allows for the use of optogenetics and calcium imaging to elucidate the mechanisms underlying GI-related symptoms associated with ASD. The array of commonly reported symptoms implicates altered sensorimotor integration at various points along the GI tract, from the pharynx to the anus. We will examine the reflex arcs that facilitate swallowing, nutrient-sensing, absorption, peristalsis, and evacuation. The high level of conservation of these processes across vertebrates also enables us to explore potential therapeutic avenues to mitigate GI distress in ASD and other NDDs. Full article

Using LULC change detection analysis, it is possible to identify changes due to urbanization, deforestation, or a natural disaster in an area. As population growth and urbanization increase, real-time solutions for the effects of urbanization on land use are required to assess its implications for food security and livelihood. This study seeks to identify and quantify recent LULC changes in Limbe, Cameroon, and to measure rates of conversion between agricultural, forest, and urban lands between 1986 and 2020 using remote sensing and GIS. Also, there is a deficiency of research employing these data to evaluate the efficiency of LULC satellite data and a lack of awareness by local stakeholders regarding the impact on LULC change. The changes were identified in four classes utilizing maximum supervised classification in ENVI and ArcGIS environments. The classification result reveals that the 2020 image has the highest overall accuracy of 94.6 while the 2002 image has an overall accuracy of 89.2%. The overall gain for agriculture was approximately 4.6 km², urban had an overall gain of nearly 12.7 km², while the overall loss for forest was −16.9 km² during this period. Much of the land area previously occupied by forest is declining as pressures for urban areas and new settlements increase. This study’s findings have significant policy implications for sustainable land use and food security. It also provides a spatial method for monitoring LULC variations that can be used as a framework by stakeholders who are interested in environmentally conscious development and sustainable land use practices. Full article

This study examined the integraftion of airborne Light Detection and Ranging (LiDAR), Simultaneous Localization and Mapping (SLAM)-based handheld LiDAR, and iPhone LiDAR to inspect forest road networks following forest operations. The goal is to overcome the challenges posed by dense canopy cover and ensure accurate and efficient data collection and mapping. Airborne data were collected using the DJI Matrice 300 RTK UAV equipped with a Zenmuse L2 LiDAR sensor, which achieved a high point density of 285 points/m² at an altitude of 80 m. Ground-level data were collected using the BLK2GO handheld laser scanner (HPLS) with SLAM methods (LiDAR SLAM, Visual SLAM, Inertial Measurement Unit) and the iPhone 13 Pro Max LiDAR. Data processing included generating DEMs, DSMs, and True Digital Orthophotos (TDOMs) via DJI Terra, LiDAR360 V8, and Cyclone REGISTER 360 PLUS, with additional processing and merging using CloudCompare V2 and ArcGIS Pro 3.4.0. The pairwise comparison analysis between ALS data and each alternative method revealed notable differences in elevation, highlighting discrepancies between methods. ALS + iPhone demonstrated the smallest deviation from ALS (MAE = 0.011, RMSE = 0.011, RE = 0.003%) and HPLS the larger deviation from ALS (MAE = 0.507, RMSE = 0.542, RE = 0.123%). The findings highlight the potential of fusing point clouds from diverse platforms to enhance forest road mapping accuracy. However, the selection of technology should consider trade-offs among accuracy, cost, and operational constraints. Mobile LiDAR solutions, particularly the iPhone, offer promising low-cost alternatives for certain applications. Future research should explore real-time fusion workflows and strategies to improve the cost-effectiveness and scalability of multisensor approaches for forest road monitoring. Full article

Unbalanced accelerations occurring during tram travel have a significant impact on passenger comfort and safety, as well as on the rate of wear and tear on infrastructure and rolling stock. Ideally, these dynamic forces should be monitored continuously in real-time; however, traditional systems require high-precision accelerometers and proprietary software—investments often beyond the reach of municipally funded tram operators. To this end, as part of the research project “Accelerometer Measurements in Rail Passenger Transport Vehicles”, pilot measurement campaigns were conducted in Poland on tram lines in Gdańsk, Toruń, Bydgoszcz, and Olsztyn. Off-the-shelf smartphones equipped with MEMS accelerometers and GPS modules, running the Physics Toolbox Sensor Suite Pro app, were used. Although the research employs widely known methods, this paper addresses part of the gap in affordable real-time monitoring by demonstrating that, in the future, equipment equipped solely with consumer-grade MEMS accelerometers can deliver sufficiently accurate data in applications where high precision is not critical. This paper presents an analysis of a subset of results from the Gdańsk tram network. Lateral (x) and vertical (z) accelerations were recorded at three fixed points inside two tram models (Pesa 128NG Jazz Duo and Düwag N8C), while longitudinal accelerations were deliberately omitted at this stage due to their strong dependence on driver behavior. Raw data were exported as CSV files, processed and analyzed in R version 4.2.2, and then mapped spatially using ArcGIS cartograms. Vehicle speed was calculated both via the haversine formula—accounting for Earth’s curvature—and via a Cartesian approximation. Over the ~7 km route, both methods yielded virtually identical results, validating the simpler approach for short distances. Acceleration histograms approximated Gaussian distributions, with most values between 0.05 and 0.15 m/s², and extreme values approaching 1 m/s². The results demonstrate that low-cost mobile devices, after future calibration against certified accelerometers, can provide sufficiently rich data for ride-comfort assessment and show promise for cost-effective condition monitoring of both track and rolling stock. Future work will focus on optimizing the app’s data collection pipeline, refining standard-based analysis algorithms, and validating smartphone measurements against benchmark sensors. Full article

Changes in habitat suitability are critical indicators of the ecological impacts of climate change. Syndiclis Hook. f., a rare and endangered genus endemic to montane limestone and cloud forest ecosystems in China, holds considerable ecological and economic value. However, knowledge of its current distribution and the key environmental factors influencing its habitat suitability remains limited. In this study, we employed the MaxEnt model, integrated with geographic information systems (ArcGIS), to predict the potential distribution of Syndiclis under current and future climate scenarios, identify dominant bioclimatic drivers, and assess temporal and spatial shifts in habitat patterns. We also analyzed spatial displacement of habitat centroids to explore potential migration pathways. The model demonstrated excellent performance (AUC = 0.988), with current suitable habitats primarily located in Hainan, Taiwan, Southeastern Yunnan, and along the Yunnan–Guangxi border. Temperature seasonality (bio7) emerged as the most important predictor (67.00%), followed by precipitation of the driest quarter (bio17, 14.90%), while soil factors played a relatively minor role. Under future climate projections, Hainan and Taiwan are expected to serve as stable climatic refugia, whereas the overall suitable habitat area is projected to decline significantly. Combined with topographic constraints, population decline, and limited dispersal ability, these changes elevate the risk of extinction for Syndiclis in the wild. Landscape pattern analysis revealed increased habitat fragmentation under warming conditions, with only 4.08% of suitable areas currently under effective protection. We recommend prioritizing conservation efforts in regions with habitat contraction (e.g., Guangxi and Yunnan) and stable refugia (e.g., Hainan and Taiwan). Conservation strategies should integrate targeted in situ and ex situ actions, guided by dominant environmental variables and projected migration routes, to ensure the long-term persistence of Syndiclis populations and support evidence-based conservation planning. Full article

Sports stadiums significantly influence urban morphology; however, empirical quantification of these effects remains limited. This study quantitatively examines the spatiotemporal relationship between sports architecture and urban functional evolution using Jiangwan Stadium in Shanghai—China’s first Western-style sports facility—as a case study. Employing Point of Interest (POI) data, ArcGIS spatial analyses, chi-square tests, and linear regression-based predictive modeling, we illustrate how the stadium has catalyzed urban regeneration and functional diversification over nearly a century. Our findings demonstrate a transition from sparse distributions to concentrated commercial and service clusters within a 1000 m radius around the stadium, notably in food and beverage, shopping, finance, insurance, and transportation sectors, significantly boosting local economic vitality. The area achieved peak functional diversity in 2016, showcasing a balanced integration of residential, commercial, and service activities. This research provides actionable insights for urban planners and policymakers on leveraging sports facilities to foster sustainable urban regeneration. Full article

The Cao’e-Jiaojiang-Oujiang River Basin possesses abundant vernacular architectural heritage with significant historical–cultural value. However, challenges like dispersed distribution and inconsistent conservation hinder its systematic protection and utilization within territorial spatial planning, necessitating a deeper understanding of its spatiotemporal patterns. Utilizing 570 identified heritage sites, this study employed ArcGIS spatial analysis (Kernel Density Estimation, Nearest Neighbor Index), correlation analysis with DEM data, and suitability analysis (Minimum Cumulative Resistance model, Gravity Model) to systematically examine spatial distribution characteristics, their evolution, and relationships with the geographical environment and historical context. Results revealed a distinct “four cores and three belts” spatial pattern. Temporally, distribution evolved from “discrete” (Song-Yuan) to “aggregated” (Ming-Qing) and then “diffused” (Modern era). Spatially, heritage showed density in plains, preference for low slopes, and settlement along waterways. Suitability analysis indicated higher corridor potential in the northern section (Cao’e-Jiaojiang) than the south (Oujiang), leading to the identification of a “Northern Segment (Shaoxing-Ningbo-Shengzhou-Taizhou)” and “Southern Segment (Wenzhou-Lishui)” corridor structure. This research provides a scientific basis for systematic conservation and integrated heritage corridor construction of vernacular architectural heritage in the basin, supporting Zhejiang’s Poetry Road Cultural Belt initiatives and cultural heritage protection within territorial spatial planning. Full article

Given the increasing challenges posed by frequent extreme climatic events, understanding the climate–human connection between the climate system and the transitions of ancient civilizations is crucial for addressing future climatic challenges, especially when examining the relationship between the abrupt events of the Holocene and the Neolithic culture development. Compared with the globally recognized “4.2 ka collapse” of ancient cultures, the initial start time and the cultural significance of the 5.5 ka climatic fluctuation are more complex and ambiguous. The Hongshan culture (6.5–5.0 ka) is characterized by a complicated society evident in its grand public architecture and elaborate high-status tombs. However, the driving mechanisms behind cultural changes remain complex and subject to ongoing debate. This paper delves into the role of climatic change in Hongshan cultural shifts, presenting an integrated dataset that combines climatic proxy records with archaeological data from the Hongshan culture period. Based on synthesized aeolian, fluvial-lacustrine, loess, and stalagmite deposits, the study indicates a relatively cold and dry climatic fluctuation occurred during ~6.0–5.5 ka, which is widespread in the Horqin dune field and adjacent areas. Combining spatial analysis with ArcGis 10.8 on archaeological sites, we propose that the climatic fluctuation between ~6.0–5.5 ka likely triggered the migration of the Hongshan settlements and adjustment of survival strategies. Full article

Orientation entropy serves as a critical metric for assessing the directional disorder of urban street networks. However, conventional two-dimensional (2D) approaches neglect vertical variations, limiting their applicability in cities with complex terrains. This study proposes a three-dimensional (3D) orientation entropy framework by integrating elevation data, providing a more comprehensive assessment of urban spatial complexity. We developed a computational workflow combining ArcGIS 10.8 for spatial data extraction and Python 3.10.10 for entropy calculation. A case study in Chongqing, China, explores the relationship between 3D orientation entropy and residents’ perceptions of spatial disorder through a small-scale survey. Although no statistically significant correlation was observed, the findings suggest emerging patterns and underscore the necessity of multidimensional frameworks in evaluating urban spatial experience. This research contributes a novel metric to urban design assessment, particularly in topographically diverse environments, and offers a foundation for future empirical studies. Full article

Landslides are among the most destructive natural hazards in the Western Ghats region of Kerala, driven by complex interactions between geological, hydrological, and anthropogenic factors. This study aims to generate a high-resolution Landslide Susceptibility Level Map (LSLM) using a machine learning (ML)-based Random Forest (RF) model integrated with Geographic Information Systems (GIS). A total of 231 historical landslide locations obtained from the Bhukosh portal were used as reference data. Eight predictive factors—Stream Order, Drainage Density, Slope, Aspect, Geology, Land Use/Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), and Moisture Stress Index (MSI)—were derived from remote sensing and ancillary datasets, preprocessed, and reclassified for model input. The RF model was trained and validated using a 50:50 split of landslide and non-landslide points, with variable importance values derived to weight each predictive factor of the raster layer in ArcGIS. The resulting Landslide Susceptibility Index (LSI) was reclassified into five susceptibility zones: Very Low, Low, Moderate, High, and Very High. Results indicate that approximately 17.82% of the study area falls under high to very high susceptibility, predominantly in the steep, weathered, and high rainfall zones of the Western Ghats. Validation using Area Under the Curve–Receiver Operating Characteristic (AUC-ROC) analysis yielded an accuracy of 0.890, demonstrating excellent model performance. The output LSM provides valuable spatial insights for planners, disaster managers, and policymakers, enabling targeted mitigation strategies and sustainable land-use planning in landslide-prone regions. Full article