Spatial Distribution Characteristics Research Articles

Rock failure deformation characteristics and mechanical parameter prediction of Xujiahe formation gas reservoir in Tianfu area, Sichuan Basin

The integrated geological-engineering reservoir reconstruction of Xujiahe Formation in Tianfu area needs accurate evaluation of rock mechanics characteristics and prediction of three-dimensional rock mechanics parameter field. The stress-strain curve characteristics, failure deformation mode, mechanical strength, and confining pressure effect are analyzed by mechanical tests. The longitudinal, lateral, and spatial distribution characteristics of rock mechanics parameters are evaluated through the combination of logging and seismic. The results show that damage morphology of mudstone is more complex than that of sandstone. With the increase of confining pressure, rock fracture pattern gradually changes from splitting failure to high angle shear failure. The mechanical strength of sandstone and mudstone increases with the increase of confining pressure, and high porosity of sandstone results in a higher confining pressure effect. The longitudinal distribution of rock mechanics parameters is significantly affected by lithology. Sandstone has high strength and little intra-layer difference, while mudstone is the opposite. The lateral distribution shows obvious sedimentary facies control characteristics, and the mechanical strength of rock in the northwest region is significantly lower than that in the southeast region. The spatial distribution is greatly affected by structural morphology and faults. The research will provide support for engineering dessert selection and fracturing reconstruction.

Heritage Tourism Development Should Take Care of Industrial Heritage Protection: A Study on the Development Strategy of Industrial Heritage Tourism in Nanjing

The tourism development of industrial heritage is an effective way to activate cultural heritage and can provide new solutions for the renewal and protection of industrial heritage. This study focuses on the industrial heritage in Nanjing, aiming to explore its spatial distribution pattern, tourism development strategy, and sustainable development model. This study adopts a combination of quantitative and qualitative research methods. First, relevant information on 93 sites of industrial heritage type historic buildings in Nanjing is collected. Secondly, ArcGIS was used to visualize the evolution of industrial buildings and the spatial distribution of industrial heritage type historic buildings. Finally, the spatial analysis tools of ArcGIS and the accessibility analysis method in space syntax theory are superimposed to comprehensively analyze the spatial distribution pattern and traffic accessibility characteristics of Nanjing’s industrial heritage. The research results propose a specific plan to promote the value transformation of industrial heritage through tourism: based on the spatial distribution characteristics of Nanjing’s industrial heritage along the water system and traffic arteries, a tourist route of “multi-point, two-axis, one-center” is planned; the tourism development strategy of “point protrusion, linear links, and surface darning” is implemented; and a sustainable development model under the guidance of low-carbon environmental protection goals is explored. This study provides a reference for the protective development of industrial heritage and the expansion of tourism and opens up a new perspective for the regeneration and planning of other urban heritage.

Study on the spatial distribution characteristics of traditional villages and their response to the water network system in the lower yangtze river basin

Traditional villages hold significant historical and cultural value as the precious heritage of China’s agricultural civilization. Currently, against the backdrop of increasing urbanization and rapid expansion of urban construction land, the spatial patterns of traditional villages across various regions in China are being encroached upon and damaged, with protection pressures growing daily. As one of the important cradles of Chinese civilization, the Lower Yangtze River Basin (LYRB) has traditional villages closely linked with its water systems, forming a unique human-land relationship and spatial distribution pattern. However, influenced by the rapid urbanization process, the spatial patterns of traditional villages in this region also face a crisis, and the contradiction between protection and development is becoming increasingly prominent. How to balance this contradiction and ensure the reasonable protection and sustainable development of traditional villages has become an urgent issue to address. Therefore, this study focuses on the LYRB. Using ArcGIS tools and combined with mathematical analysis methods, the spatial distribution characteristics and essential influencing factors of traditional villages in this area were screened and analyzed. The objective was to examine the spatial structural relationship between traditional villages, four water system types, and nine sub-basin units, intending to reveal the unique interdependence between the water system and traditional villages in this area. This would provide scientific support for the formulation of scientific conservation strategies. The research results show that: (1) Traditional villages in The LYRB form two core clusters spatially and exhibit substantial spatial accumulation; (2) Water system characteristics are the main factors affecting the distribution of traditional villages; (3) In the LYRB, the spatial distribution of the nine sub-basins is closely related to the spatial distribution of traditional villages, resulting in typical regional spatial differentiation of traditional villages in this area. This study is based on a watershed perspective, and the results highlight the importance of the water system network in the development of traditional villages, revealing a unique spatial dependency relationship between traditional villages and the water network in the LYRB. In order to ensure the comprehensive protection of the traditional village system in this region, it is essential to adhere to the fundamental principles that govern its spatial configuration. A tripartite collaborative protection system based on the watershed should be formulated from the perspective of the overall distribution relationship between the water network and the traditional villages. This system would serve to protect the overall landscape, the water network pattern, and the traditional villages. Establishing an overall pattern view of integrating the water system network and the traditional villages is essential.

An Integrated Frequency Regulation Method Based on System Frequency Security Posture

As the share of renewable energy in a grid increases, the grid’s frequency support capability weakens, and the spatial distribution of grid frequency becomes more pronounced. As a result, control strategies based on system frequency consistency and traditional frequency regulation dominated by synchronous machines are becoming increasingly inadequate for meeting the frequency regulation requirements of new-type power systems. To enhance the system’s frequency support capability, it is imperative to fully utilize the frequency regulation resources within the power system. To address this issue, this paper first introduces a system frequency security posture assessment method that accounts for the spatial distribution characteristics of the grid. Subsequently, a parameter optimization method for diverse frequency regulation resources is proposed in conjunction with the proposed comprehensive evaluation method for frequency regulation. Next, using a renewable energy feeder regional grid as an example, an integrated frequency regulation method based on the system frequency security posture is presented. Finally, the frequency regulation performance and economic costs of different frequency regulation methods are analyzed under various operating scenarios and disturbances using a model based on actual data from the renewable energy feeder regional grid. The simulation and index calculation results demonstrate that the method proposed in this paper effectively enhances the system’s frequency support capability, reduces the frequency disparity between different nodes within the grid, and maintains high economic performance.

Improving lithofacies prediction in lacustrine shale by combining deep learning and well log curve morphology in Sanzhao Sag, Songliao Basin, China

The accurate identification of shale lithofacies is crucial for characterizing the hydrocarbon potential of lacustrine shale oil reservoirs. Petrophysical logging, serving as an effective tool for acquiring subsurface lithofacies information, provides a convenient and reliable lithofacies identification solution. Deep learning technology, capable of adapting to the nonlinearity and non-stationarity inherent in geological statistics, exhibits unique advantages in conventional reservoir lithofacies prediction. However, the lithofacies of lacustrine shale formations undergo rapid spatial and temporal changes, rendering lithofacies prediction more complex compared to conventional reservoirs. In this study, the lower Qingshankou member in the Sanzhao Sag was selected as the research target, and the Deep Residual Shrinkage Network (DRSN), known for its ability to handle complex nonlinear relationships and mitigate the effects of noisy data through residual connections and shrinkage mechanisms, was employed as a deep learning framework for predicting lithofacies in lacustrine shale formations for the first time. Well logging data, including natural gamma ray (GR), acoustic (AC), deep investigate double lateral resistivity log (RD), shallow investigate double lateral resistivity log (RS), and corrected compensated neutron log (CNC), were used as input features for the model. The results indicate that the DRSN model achieves an accuracy of 76.3% in predicting lithofacies in lacustrine shale formations. However, the DRSN model still exhibits shortcomings in capturing lithofacies change information. To enhance the model's ability to identify lithofacies change interfaces, this study further explicitly introduces Well Logging Curve Morphological Features (WLCM) as additional features and establishes a recognition method combining DRSN with WLCM. The combined DRSN-WLCM model was validated using a separate test dataset, demonstrating an improved accuracy of 85.5%, using the five well logging attributes and the derivative of the AC as inputs. Furthermore, the study reveals the lithofacies spatial distribution characteristics of the lower Qingshankou member in the Sanzhao Sag. This method can be widely applied to lithofacies delineation in lacustrine shale formations and similar stratigraphic units.

Spatial distribution characteristics of Tibetan Buddhism principal-subordinate monastery systems in the Hehuang region

Tibetan Buddhist monasteries constitute significant cultural heritages of ethnic minorities, evolving into the Principal-Subordinate Monastery System (PSMS) with profound historical and cultural significance. This system exhibits an integrated hierarchical structure in terms of religious dominance, political administration, and cultural diffusion. Existing research primarily focuses on internal humanistic factors such as governance patterns, while there is not any research focused on its patterns and manifestations in spatial distribution. This study aims to elucidate the spatial distribution characteristics of the PSMS in Hehuang region, including the Tibetan Buddhist monasteries from all sects in the Hehuang region since the Song Dynasty It establishes a hierarchical PSMS database based on the affiliation relationships, aimed at storing spatial and property information related to PSMS. The database standardizes the naming and coding of monasteries, and classifies them through hierarchical relationships to ensure data consistency and usability. Finally, the classified and coded monastery data were analyzed by GIS tools to form the PSMS spatial distribution characterisation framework. Results reveal that (1) Monasteries demonstrate notable spatial clustering patterns from both holistic and sectarian perspectives, with density being influenced by the principal monastery’s position. (2) Almost every PSMS exhibits a spatial pattern centered around the principal monastery, with subordinate monasteries clustering within a defined range correlated with the administrative region of the principal monastery. (3) PSMS scale variations are controlled by principal monasteries, exhibiting positive correlations in hierarchical structure, control quantity, and distribution range. (4) The spatial orientation of PSMS correlates with river distribution, while the relationships among mountain ranges require further investigation. These findings provide initial insights into the spatial distribution characteristics of PSMS, confirming the spatial influence of the principal monastery. Besides, this study established an innovative spatial research framework for heritage clusters with multiple types and hierarchies. Thus, this study offers new insights into the spatial distribution of Tibetan Buddhist monastery heritage and presents a framework for further examining the spatial distribution of the Tibetan Buddhist monastery heritage in other regions, as well as other heritage clusters where connected and clustered through religious and cultural ties.

Association between Land Use and Urban Vitality in the Guangdong–Hong Kong–Macao Greater Bay Area: A Multiscale Study

Urban vitality, which indicates the development level of a city and the quality of life of its residents, is a complex subject in urban research due to its diverse assessment methods and intricate impact mechanisms. This study uses multisource data to evaluate the urban vitality of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) across social, economic, cultural, and environmental dimensions. It analyzes the spatial distribution characteristics of urban vitality and examines the relationships between urban vitality and land use at both regional and city scales. The results indicate that the urban vitality in the GBA generally exhibits a spatial distribution pattern of a high central density and a low peripheral spread, where built-up areas and cropland emerge as key influencing factors. Cities with different developmental backgrounds have unique relationships between land use and urban vitality. In high-vitality cities, the role of the built-up area diminishes, and natural ecosystems, such as wetlands, enhance vitality. In contrast, in low-vitality cities, built-up areas boost urban vitality, and agriculture-related land types exert a lower negative or even positive effect. This research contributes to the understanding of the spatial structures of urban vitality related to land use at different scales and offers insights for urban planners, builders, and development managers in formulating targeted urban vitality enhancement strategies at the regional collaborative and city levels.

Limitations and rotation of the two-armed phase spiral in the Milky Way stellar disc

Context. The Milky Way’s history of recent disturbances is vividly demonstrated by a structure in the vertical phase-space distribution known as the Gaia phase spiral. A one-armed phase spiral has been seen widely across the Milky Way disc, while a two-armed one has only been observed in the solar neighbourhood. Aims. This study aims to determine the properties of the two-armed phase spiral and to put it in a Galactic context, with the ultimate goal of understanding the structure and history of the Milky Way disc. Methods. The Gaia DR3 data were used to trace and characterise the two-armed phase spiral. Special focus was put on the phase spiral’s spatial distribution, rotational behaviour, and chemical characteristics. To quantify the properties of the phase spiral, we used a model that fits a spiral pattern to the phase space distribution of the stars. Results. We found that the two-armed phase spiral is detectable only within a narrow range of galactocentric distances and angular momenta in the solar neighbourhood, R = 8 ± 0.5 kpc, LZ = 1450 ± 50 kpc km s−1. Outside this region, the phase spiral is one-armed. The two-armed phase spiral rotates with the phase angle, in a similar way to the one-armed phase spiral, and changes axis ratio with phase angle. Additionally, stars within the phase-space overdensity caused by the two-armed phase spiral pattern have slightly higher mean metallicity than stars in the underdense regions of the pattern at equivalent galactocentric distances, angular momenta, and vertical orbit extents. Conclusions. The two-armed phase spiral rotates with phase angle and its effect can be seen in metallicity, in a similar way to the one-armed phase spiral. However, the limited range over which it can be found, and its variation in shape are quite different from the one-armed version, suggesting it is a much more localised phenomenon in the Galactic disc.

Analysis of changes and driving forces of landscape pattern vulnerability at Qianping Reservoir in Central China.

Reservoir projects often have significant impacts on ecosystems. The resulting environmental problems hinder the ecologically sustainable development of project areas. Research focusing on landscape pattern vulnerability could shed light on ecological restoration in disturbed sites. However, few studies have specifically examined reservoir areas in this context. This study investigates the spatial distribution characteristics, change rules, spatial autocorrelation, and driving forces of landscape pattern vulnerability in the Qianping Reservoir area (3859.16 hm2) from 2000 to 2020 using land use data. The findings reveal several key points: (1) Over the study period, cultivated land, grassland, and forest land are the key landscape types, covering more than 90% of the area. Cultivated land decreased by 481.57 hm2 as other land use types expanded. (2) Vulnerability remained stable in the first decade but sharply increased from 2010 to 2020, showing a trend of spatial aggregation. Reservoir construction and simultaneous ecological restoration efforts led to shifts in vulnerability zones across the landscape. (3) Spatial distribution of landscape pattern vulnerability shows a positive correlation, which strengthened by 2020 compared to earlier years. (4) Man-made factors, particularly land use changes, significantly influence landscape pattern vulnerability, with their impact growing over time. These findings not only provide a scientific basis for ecological restoration and landscape reconstruction in the Qianping Reservoir area but also offer insights applicable to similar environments. Overall, this study enhances theoretical understanding of reservoir landscape pattern vulnerability and contributes valuable perspectives on ecological restoration strategies for reservoir areas.

Identification of driving mechanisms of actual evapotranspiration in the Yiluo River Basin based on structural equation modeling

BackgroundActual evapotranspiration (ETa) is a crucial aspect of the hydrological cycle. It serves as a vital link between the soil–vegetation–atmosphere continuum. Quantifying the leading factors of regional ETa change and revealing the multi-factor compound driving mechanism of ETa evolution is necessary. Structural equation modeling (SEM) has been widely used to study the structural relationships between variables in large-scale areas. However, there is an urgent need for more in-depth exploration of these complex relationships at the grid scale. Therefore, the Yiluo River Basin, a representative area of soil and water conservation engineering demonstration in the Loess Plateau, was selected as the study area, and the SEM at the basin scale and grid-scale were constructed to carry out the research.ResultsThe data indicate that ETa decreased at 1.97 mm per year at the watershed scale from 1982 to 2020. Climate change had the greatest impact on the change of ETa in the watershed, with a total impact coefficient of over 0.9. The direct impact of climate change on ETa increased by 0.571 from 1982–1992 to 1993–2020. The direct impact coefficients of vegetation cover and soil moisture decreased by 0.402 and 0.102, respectively, while the impact coefficient of the water body factors increased by 0.096. At the scale of individual grid cells, the ETa in the watershed was affected by changes in watershed climate, vegetation, and soil moisture, with contributions ranging from − 0.31 to 0.22, − 1.09 to − 0.08, and 0.61 to 0.90, respectively. Spatially, vegetation and soil moisture had a stronger impact on ETa in the upstream area, while climate change had a negative effect, and the downstream region had the opposite effect. Furthermore, the regulatory impact of large reservoirs mitigated the response of water surface evaporation to climate change in the upstream region.ConclusionsThe application of SEM at different spatial and temporal scales has effectively quantified the driving mechanisms behind actual evapotranspiration in the Yiluo River Basin, while visually representing the spatial distribution characteristics of various influencing factors on ETa. This research provides a theoretical foundation for studying slope water consumption processes and circulation mechanisms.

Correlations between an Urban Three-Dimensional Pedestrian Network and Service Industry Layouts Based on Graph Convolutional Neural Networks: A Case Study of Xinjiekou, Nanjing

Urban high-density development has led to the emergence of complex three-dimensional pedestrian networks. As a crucial component of city centers, these networks significantly influence the spatial distribution of service industries. Understanding the correlation between pedestrian networks and service industry layouts is vital for effective planning and development. This study proposes a technical framework for analyzing the relationship between three-dimensional pedestrian networks and service industry layouts. Using the Xinjiekou central area in Nanjing as a case study, we constructed a three-dimensional pedestrian network model using the sDNA method. Focusing on catering formats, we introduced a method to study the spatial distribution characteristics of service industries in three-dimensional spaces and employed a graph convolutional network model to systematically analyze the correlation between pedestrian network closeness and betweenness with catering formats. The results indicate that pedestrian network closeness is significantly positively correlated with the number and average spending of catering formats, while betweenness shows almost no correlation. High-closeness areas, due to their traffic convenience and walkability, are more conducive to the concentration of catering formats and higher spending levels. Our findings provide valuable insights for catering format location decisions and the optimization of three-dimensional pedestrian networks, contributing to sustainable urban development.

Rockfall mapping and susceptibility evaluation based on UAV high-resolution imagery and support vector machine method

Abstract This study aims to develop a comprehensive method for automated rockfall mapping and susceptibility assessment using unmanned aerial vehicle (UAV) tilt photography and the support vector machine (SVM) algorithm. By employing Jinzhong Town in the mountainous forest landscapes of Southwest China as a case study, we leverage photogrammetry principles and computer vision algorithms to generate high-precision, high-resolution digital surface models (DSMs), and digital orthophoto maps through a UAV remote sensing system. The rockfall inventory is accurately and automatically mapped using the object-based classification method and SVM algorithm. The automated rockfall identification method achieves a 93% accuracy with a Kappa coefficient of 0.7967. Statistical analyses of spatial distribution characteristics reveal a significant correlation between rockfall volume and area with a correlation coefficient (R²) of 0.92316 under logarithmic coordinates. In addition, a power function relationship describes the link between rockfall volume and slope height (R² = 0.87), while the relationship with sliding distance is characterized by a weaker linear correlation (R² = 0.65). Rockfall runout distance also shows a significant linear correlation with slope height (R² = 0.79) but exhibits a less-pronounced association with rockfall volume (R² = 0.58). The SVM model employed to assess rockfall susceptibility indicates high accuracy (area under the curve = 0.896), affirming its efficacy in rockfall susceptibility assessment. Our findings underscore the utility of UAV remote sensing for rockfall information extraction and susceptibility evaluation, particularly in challenging mountainous forest environments characterized by intricate topography and geological complexities.

Prevalence and distribution of dissolved paralytic shellfish toxins in seawater in the Yellow Sea and the Bohai Sea, China

Paralytic shellfish toxins (PSTs) could be secreted by PSTs-producing microalgae or released by ruptured cells in seawater. In this study, the distribution of dissolved PSTs in the Yellow Sea and the Bohai Sea, China, was investigated by two cruises in April and July 2023. Seawater samples were collected from the surface, middle and bottom layers, and the profiles of PSTs were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and the spatial distribution characteristics of dissolved PSTs and their correlation with environmental factors were explored. Results showed that C1/2, GTX1/4, GTX2/3 and dcGTX2/3, were detected in seawater samples in both spring and summer, with the detection rates 100 % and 97.6 %, respectively. The total PST (ΣPSTs) concentrations ranged in 12 ∼ 590 pmol L−1, 9.3 ∼ 546 pmol L−1, 12 ∼ 2,452 pmol L−1, and not detected (nd) ∼ 188 pmol L−1 in seawater samples collected from the surface, middle and bottom layers in spring, and the surface layer in summer, respectively. Concentrations of PSTs markedly varied in the vertical water column in different sea regions. Generally, concentrations of ΣPSTs in the bottom seawater were higher than those in the surface and middle layers in the Bohai Sea and the North Yellow Sea, but no significant difference in the different water layers in the South Yellow Sea. In addition, concentrations of ΣPSTs in surface waters were much lower in summer than those in spring. In both spring and summer, dissolved PSTs in surface seawater were mainly distributed in the South Yellow Sea. These results indicate that PSTs were prevalent in the Yellow Sea and the Bohai Sea, of which the potential hazard to marine organisms should be highly concerned.

MH-DCNet: An improved flow field prediction framework coupling neural network with physics solver

With the development of intelligent computing technology, deep learning methods have provided an efficient solution for rapid flow field prediction in computational fluid dynamics (CFD) problems. However, existing methods have limitations in handling interference among physical variables due to different data distributions, leading to a decline in prediction performance. In this paper, we propose MH-DCNet, an improved flow field prediction framework that couples a neural network with a physics solver. Specifically, to address the data distribution problem, we design a multi-head deep convolutional neural network that decouples the prediction of physical variables through multiple encoders and decoders. We also develop a hybrid loss function by introducing the mean structural similarity to better capture the complex spatial structures and distribution features of flow fields. We evaluate MH-DCNet with unseen geometries and various flow conditions. Experimental results show that MH-DCNet outperforms other advanced models in efficiency and generalization capability. It accelerates the prediction process by 2.35 times compared to the CFD method while meeting the convergence constraints.

Spatial distribution characteristics and influencing factors of tourism resources based on point of interest data.

The agglomeration and dispersion of tourist attractions in space greatly affect the development of regional tourism resources and the consumption choice of tourism market. At present, the research on the spatial distribution characteristics of tourist attractions and their influencing factors mainly adopts induction and investigation, and there is a lack of effective statistical models for the research on the spatial distribution of tourist attractions and their influencing factors in some historical and cultural ancient cities. This paper uses Internet technology to obtain the spatial distribution data of tourist attractions in Shaoxing city, and uses mean nearest neighbor analysis, nuclear density analysis, imbalance index analysis, standard deviation ellipse and other spatial statistical analysis techniques and geographical detector methods to study the spatial distribution characteristics and influencing factors of tourist attractions in Shaoxing City. This paper studied the distribution characteristics of tourist attractions in Shaoxing city, such as spatial aggregation, distribution equilibrium and spatial orientation, and applied geographical detector to study the influencing factors of the spatial distribution of scenic spots. It was concluded that the spatial distribution pattern of scenic spots was affected by various factors such as natural environment, social environment and economic environment. The explanatory power of two-factor interaction is obviously stronger than that of single factor. The research results provide scientific basis for the planning, layout and development of tourist attractions in Shaoxing and its similar cities, and then promote the high-quality development of tourism in Shaoxing and its similar historical and cultural ancient cities.

An Evaluation of Ecosystem Quality and Its Response to Aridity on the Qinghai–Tibet Plateau

Exploring the response of spatial and temporal characteristics of ecological quality change to aridity on the Qinghai–Tibet Plateau (QTP) can provide valuable information for regional ecological protection, water resource management, and climate change adaptation. In this study, we constructed the Remote Sensing Ecological Index (RSEI) and Standardized Precipitation Evapotranspiration Index (SPEI) based on the Google Earth Engine (GEE) platform with regional characteristics and completely analyzed the spatial and temporal variations of aridity and ecological quality on the QTP in the years 2000, 2005, 2010, 2015, and 2020. Additionally, we explored the responses of ecological quality to aridity indices at six different time scales. The Mann–Kendall test, correlation analysis, and significance test were used to study the spatial and temporal distribution characteristics of meteorological aridity at different time scales on the QTP and their impacts on the quality of the ecological environment. The results show that the ecological environmental quality of the QTP has a clear spatial distribution pattern. The ecological environment quality is significantly better in the south-east, while the Qaidam Basin and the west have lower ecological environment quality indices, but the overall trend of environmental quality is getting better. The Aridity Index of the QTP shows a differentiated spatial and temporal distribution pattern, with higher Aridity Indexes in the north-eastern and south-western parts of the plateau and lower Aridity Indexes in the central part of the plateau at shorter time scales. Monthly, seasonal, and annual-scale SPEI values showed an increasing trend. There is a correlation between aridity conditions and ecological quality on the QTP. The areas with significant positive correlation between the RSEI and SPEI in the study area were mainly concentrated in the south-eastern, south-western, and northern parts of the QTP, where the ecological quality of the environment is more seriously affected by meteorological aridity.

Risk Assessment of Community-Scale High-Temperature and Rainstorm Waterlogging Disasters: A Case Study of the Dongsi Community in Beijing

With the advancement of urbanization and acceleration of global warming, extreme weather and climate events are becoming increasingly frequent and severe, and climate risk continues to rise. Each community is irreplaceable and important in coping with extreme climate risk and improving urban resilience. In this study, the Dongsi Community in the functional core area of Beijing was explored, and the risk assessment of high temperatures and rainstorm waterlogging was implemented at the community scale. Local navigation observations were integrated into a theoretical framework for traditional disaster risk assessment. The risk assessment indicator system for community-scale high-temperature and rainstorm waterlogging disasters was established and improved from a microscopic perspective (a total of 22 indicators were selected from the three dimensions of hazard, exposure, and vulnerability). Geographic Information Systems (GIS) technology was used to integrate geographic information, meteorological, planning, municipal, socioeconomic and other multisource information layers, thus enabling more detailed spatial distribution characteristics of the hazard, exposure, vulnerability, and risk levels of community-scale high temperatures and rainstorm waterlogging to be obtained. The results revealed that the high-risk area and slightly high-risk area of high-temperature disasters accounted for 13.5% and 15.1%, respectively. The high-risk area and slightly high-risk area of rainstorm waterlogging disasters accounted for 9.8% and 31.6%, respectively. The high-risk areas common to high temperatures and waterlogging accounted for 3.9%. In general, the risk of high-temperature and rainstorm waterlogging disasters at the community scale showed obvious spatial imbalances; that is, the risk in the area around the middle section of Dongsi Santiao was the lowest, while a degree of high temperatures or rainstorm waterlogging was found in other areas. In particular, the risk of high-temperature and rainstorm waterlogging disasters along Dongsi North Street, the surrounding areas of Dongsi Liutiao, and some areas along the Dongsi Jiutiao route was relatively high. These spatial differences were affected to a greater extent by land cover (buildings, vegetation, etc.) and population density within the community. This study is a useful exploration of climate risk research for resilient community construction, and provides scientific support for the planning of climate-adaptive communities, as well as the proposal of overall adaptation goals, action frameworks, and specific planning strategies at the community level.

Distribution and prediction of biocrusts under the canopy of typical vascular plants on the Loess Plateau, Northwest China.

Vascular plants exert significant effects on micro-environment, thereby affecting the distribution of biological soil crusts (biocrusts). The relationship between vascular plants and the spatial distribution characteristics of biocrusts is largely unknown. We investigated the distribution characteristics of biocrusts under the canopy of vascular plants in the water-wind erosion crisscross area of the Loess Plateau, where larger areas of biocrusts had been formed since the implantation of "Grain for Green" project. We analyzed the relationship between the canopy characteristics of different vascular plants and the spatial distribution of biocrusts using correlation analysis and random forest importance ranking methods, and further constructed a predictive model for the area of biocrusts under the canopy of vascular plants. The results showed that: 1) Cyanobacteria crust was the predominant biocrusts, followed by moss crust. 2) The canopy of vascular plants affected the spatial distribution of biocrusts, with notable differences in distribution pattern across different directions under the canopy of vascular plants. Biocrusts were primarily distributed in the 270°-315° and 315°-360° directions, while was less frequent in the 90°-135° and 135°-180° directions. 3) Radially, the coverage of biocrusts gradually increased from the root-base to the edge of the canopy of vascular plants. 4) The coverage of biocrusts under canopy was significantly related to the characteristics of vascular plants, including canopy area, long crown width, short crown width, litter area and plant height. 5) The relative importance of canopy area, long crown width, and short crown width to the biocrusts under the canopy was 13.7%, 12.1%, and 11.9%, respectively, while the relative importance of plant height and species type was relatively low, being 6.7% and 4.4%, respectively. 6) Results of the random forest model demonstrated strong predictive performance for biocrusts distribution based on canopy characteristics of vascular plants, with a prediction accuracy of 0.59 (R2) and a root mean square error of 1.2 m2. This model could be applied to predict and estimate the area of biocrusts under the canopy of vascular plants. This study provided a theoretical basis for in-depth understanding of the relationship between vascular plants and biocrusts in semi-arid climate regions, as well as for predicting the spatial distribution of biocrusts.

Dark field photon scattering state measurements from bumps on a gold nanofilm

Abstract A dark and bright field (BF) imaging technique explored plasmonic phenomena arising from bumps on a gold nanofilm coated on a silica substrate. The study employs dark field (DF) polarization indirect microscopic imaging to investigate the scattering photon state and reveal the spatial distribution characteristics with distinct multipolar features, contrasting with those observed in the BF imaging configuration. Computational simulations utilizing the finite-difference time-domain method were conducted to understand this behaviour further and consider the experimental setup’s impact. The observations of varying multipolar scattering features with changes in the incident angle of the DF illumination suggest that the excitation of plasmonic effects differs for light beams incident at different angles.

Spatial Influence of Digital Economy on Carbon Emission Efficiency of the Logistics Industry across 30 Provinces in China

The logistics industry (LI) is a key pillar of the global economy, and its carbon emission efficiency (CEE) is crucial for achieving carbon neutrality. The rapid development of the digital economy (DE) has had a profound impact on the LI, but the spatial impact on its CEE is currently unclear and requires further research. Firstly, based on the collection of relevant data, we use the entropy weight method and linear weighted sum method to measure the level of development of the DE. Secondly, the SBM model is used to measure the CEE level of the LI. Using Moran’s I index model and OLS and GWR models, we analyze the impact and spatial distribution characteristics of the DE on the CEE of the LI and propose development strategies. The article uses statistical data from 30 provinces in China from 2013 to 2022 as an example to demonstrate the implementation process of the method. The results show that the DE has a positive impact on the CEE of the LI, and there are spatial differences. Based on this, this article proposes policy recommendations for the development of green and low-carbon logistics and digital logistics that are tailored to local conditions, providing theoretical and methodological support for low-carbon research in the LI, and providing reference for other countries and regions to explore the path of green and low-carbon transformation.