Spatial Pattern Analysis Research Articles

Geospatial analysis of spatial distribution, patterns, and relationships of health status in the belt and road initiative

The Health Silk Road plays a crucial role in the Belt and Road Initiative, and comprehending the health status within the participating countries is fundamental for fostering cooperation in public health. This paper collected five health indicators to represent the health status of the Belt and Road countries. Employing spatial statistics, the spatial patterns of health indicators and the associations with influencing factors were investigated. The utilized spatial statistics encompass spatial autocorrelation methods, geographical detector and spatial lag model. The results revealed obvious disparities and significant positive spatial autocorrelation of health indicators within the Belt and Road countries. Specifically, countries in Sub-Saharan Africa exhibited significant clustering of limited health indicators, while countries in Europe and Central Asia demonstrated significant clustering of robust health indicators. Furthermore, the health indicators exhibited significant spatial heterogeneity and association with the influencing factors. Universal health coverage, household air pollution, and the prevalence of undernourishment emerge as influential factors affecting health indicators. Overall, our findings highlighted complex influencing factors that contributed to the profound health inequalities across the Belt and Road countries. These factors should be duly considered in public health collaborations within the Belt and Road Initiative.

The analysis of spatial distribution pattern of Chinese urban lakes and its influence factors

The analysis of spatial distribution pattern of Chinese urban lakes and its influence factors

Temporal and Spatial Analysis of Coastal Landscape Patterns Using the GEE Cloud Platform and Landsat Time Series

Temporal and Spatial Analysis of Coastal Landscape Patterns Using the GEE Cloud Platform and Landsat Time Series

Spatial Analysis for Better Marketing Decisions with Special Focus on Consumer Behaviour Patterns

The study explores the pivotal role of Geographic Information Systems (GIS) in shaping marketing decisions, with a special emphasis on consumer behaviour patterns. Distinct studies are scrutinized, spanning diverse applications of GIS in marketing, from spatial consumer behaviour in small towns to the visualization of consumer sales promotions. The analysis encompasses the integration of GIS with methodologies such as spatial point pattern analysis, kernel density estimation, and RFID systems, offering insights into optimal retail site locations, consumer preferences in shopping centers, and the spatial distribution of data. The findings underscore GIS's capacity to enhance decision-making processes, offering a valuable resource for marketers seeking to leverage spatial intelligence for strategic advantage.

Spatio-temporal dynamics and distributional trend analysis of African swine fever outbreaks (2020-2021) in North-East India.

African swine fever (ASF) is a highly contagious, notifiable, and fatal hemorrhagic viral disease affecting domestic and wild pigs. The disease was reported for the first time in India during 2020, resulted in serious outbreaks and economic loss in North-Eastern(NE) parts, since 47% of the Indian pig population is distributed in the NEregion. The present study focused on analyzing the spatial autocorrelation, spatio-temporal patterns, and directional trend of the disease in NE India during 2020-2021. The ASF outbreak data (2020-2021) were collected from the offices of the Department of Animal Husbandry and Veterinary Services in seven NE states of India to identify thepotential clusters, spatio-temporal aggregation, temporal distribution, disease spread, densitymaps, and risk zones. Between 2020 and 2021, a total of 321 ASF outbreaks were recorded, resulting in 59,377 deaths. The spatial pattern analysis of the outbreak data (2020-2021) revealed that ASF outbreaks were clustered in 2020 (z score = 2.20, p < .01) and 2021 (z score = 4.89, p < .01). Spatial autocorrelation and Moran's I value (0.05-0.06 in 2020 and 2021) revealed the spatial clustering and spatial relationship between the outbreaks. The hotspot analysis identified districts of Arunachal Pradesh, Assam and districts of Mizoram, Tripura as significant hotspots in 2020 and 2021, respectively. The spatial-scan statistics with a purely spatial and purely temporal analysis revealed six and one significant clusters, respectively. Retrospective unadjusted, temporal, and spatially adjusted space-time analysis detected five, five, and two statistically significant (p < .01) clusters, respectively. The directional trend analysis identified the direction of disease distribution as northeast-southwest (2020) and north-south (2021),indicatethe possibility of ASF introduction to India from China. The high-risk zones and spatio-temporal pattern of ASF outbreaks identified in the present study can be used as a guide for deploying proper prevention, optimizing resource allocation and diseasecontrol measures in NE Indian states.

Construction of Ecological Security Pattern of Urban Agglomeration Based on Multi-Scale Ecological Corridor Networks

The construction of an ecological security pattern (ESP) is an effective approach to addressing ecological concerns in urban agglomerations. However, previous research has often overlooked the ecological characteristics at different spatial scales, making it difficult to effectively tackle environmental issues. This study focuses on the Changsha–Zhuzhou–Xiangtan urban agglomeration (CZXUA) to construct an ESP from 2 scales: the urban agglomeration and the metropolitan area. First, ecological sources at different scales were identified and optimized using morphological spatial pattern analysis, ecosystem service supply assessment, landscape connectivity evaluation, and ecological demand intensity analysis. Next, spatial principal component analysis was employed to analyze resistance factors across different spatial scales, enabling the construction of a multi-scale landscape resistance surface. Finally, multi-scale ecological corridors were extracted using circuit theory, and the ecological corridors passing through the central urban area were optimized. As a result, 176 ecological sources, 337 ecological corridors, 60 ecological pinch points, and 30 ecological barrier points were identified, forming the overall ESP for the CZXUA. Furthermore, an ecological protection and optimization pattern, described as “One River, Seven Waters, One Heart, and Eight Wedges”, was proposed based on the ESP. This pattern highlights pivotal areas for ecological protection and restoration within the national land space. This study provides a comprehensive example of constructing a multi-scale ecological corridor network and identifying critical areas for ecological protection and restoration. The findings can serve as a reference for special ecological protection planning in urban agglomerations.

Trends and Spatial Pattern Analysis of Typhoid and Paratyphoid Fever Incidence — Yunnan Province, China, 1989–2022

Trends and Spatial Pattern Analysis of Typhoid and Paratyphoid Fever Incidence — Yunnan Province, China, 1989–2022

Integrating random forest and morphological spatial pattern analysis for predicting future land surface temperature dynamics: insights from urbanizing Saudi Arabia

In the face of rapid urbanization in Saudi Arabia, understanding the impact of landscape changes on land surface temperature (LST) is crucial for sustainable urban planning. This study assesses the influence of landscape morphology on LST and predicts future LST changes. A multi-temporal land use and land cover (LULC) analysis using random forest (RF) quantified urban expansion and its ecological impacts. Accuracy assessment using the kappa coefficient illustrated the precision of the classification techniques. Morphological Spatial Pattern Analysis (MSPA), developed in Python, analyzed the structural evolution of urban areas, vegetation and exposed rocks. Polynomial regression models established the relationship between landscape morphology and LST and predicted future temperature trends. Results for Asir show a significant improvement in accuracy of the LULC models over three decades, with overall accuracy increasing from 89.99% in 1990 to 91.72% in 2020. The bootstrapping trend analysis showed an urban expansion with a positive slope of 9.27 and a decline in water bodies with a negative slope of −0.03. The MSPA analysis reflected a significant urban expansion, with the core area growing from 45.19 km2 in 2001 to 230.33 km2 in 2021. The vegetated areas showed resilience and dynamic connectivity despite slight reduction and fragmentation. The polynomial regression predicted an increase in future average LST by 2030, with urban core areas reaching 58.47 °C, vegetated cores 42.19 °C and exposed rock cores 55.79 °C. These results highlight the link between urban expansion and LST rise and make the case for integrating green infrastructure and cooling strategies into urban development.

Childhood stunting is highly clustered in Northern Province of Rwanda: A spatial analysis of a population-based study

BackgroundIn Northern Province, Rwanda, stunting is common among children aged under 5 years. However, previous studies on spatial analysis of childhood stunting in Rwanda did not assess its randomness and clustering, and none were conducted in Northern Province. We conducted a spatial-pattern analysis of childhood undernutrition to identify stunting clusters and hotspots for targeted interventions in Northern Province. MethodsUsing a household population-based questionnaire survey of the characteristics and causes of undernutrition in households with biological mothers of children aged 1–36 months, we collected anthropometric measurements of the children and their mothers and captured the coordinates of the households. Descriptive statistics were computed for the sociodemographic characteristics and anthropometric measurements. Spatial patterns of childhood stunting were determined using global and local Moran's I and Getis-Ord Gi* statistics, and the corresponding maps were produced. ResultsThe z-scores of the three anthropometric measurements were normally distributed, but the z-scores of height-for-age were generally lower than those of weight-for-age and weight-for-height, prompting us to focus on height-for-age for the spatial analysis. The estimated incidence of stunting among 601 children aged 1–36 months was 27.1 %. The sample points were interpolated to the administrative level of the sector. The global Moran's I was positive and significant (Moran's I = 0.403, p < 0.001, z-score = 7.813), indicating clustering of childhood stunting across different sectors of Northern Province. The local Moran's I and hotspot analysis based on the Getis-Ord Gi* statistic showed statistically significant hotspots, which were strongest within Musanze district, followed by Gakenke and Gicumbi districts. ConclusionChildhood stunting in Northern Province showed statistically significant hotspots in Musanze, Gakenke, and Gicumbi districts. Factors associated with such clusters and hotspots should be assessed to identify possible geographically targeted interventions.

A Colourful Way to Unravel the Important Fluidization-Related Granule Size Effect on Semi-Continuous Drying.

Continuous twin screw wet granulation (TSWG) systems are possible pathways for oral solid dosage manufacturing in the pharmaceutical industry. TSWG requires a drying step after granulation before the tableting process. Typically, semi-continuous fluidized bed dryers (FBDs) are used for this purpose. At the same time, the pharmaceutical sector is interested in mathematical prediction models to save resources during the early drug product development (DPD) stage or to control manufacturing. Several authors have already developed prediction models for semi-continuous drying processes. However, these model structures reported systematic prediction offsets, which could be related to the incomplete implementation of fluidization and granule segregation phenomena. This study evaluates the complex fluidization behavior of wet granules in industrially relevant semi-continuous FBDs. A transparent perspex version of the dryer was used for the analysis of bed height, pressure drop, porosity, segregation, and spatial heating patterns at varying process settings. The investigated behaviors of the fluidizing bed will be helpful to derive phenomenological (sub)models for the detailed description of segregation in the semi-continuous fluidized bed system. In this study, it was found that semi-continuous FBDs are characterized by a change in fluidization regime from plug flow to a bubbling bed at the moment that the granule bed slumps. Secondly, the presence of size-based vertical segregation phenomena as well as spatial temperature differences were proven. The experimental results suggest that larger granules are dried under more intense drying conditions than smaller granules.

Temporal and spatial pattern analysis and susceptibility assessment of geological hazards in Hunan Province of China from 2015 to 2022

Temporal and spatial pattern analysis and susceptibility assessment of geological hazards in Hunan Province of China from 2015 to 2022

Environmental DNA, hydrochemistry and stable water isotopes as integrative tracers of urban ecohydrology

Urbanization and the persistent environmental changes present a major challenge for urban freshwaters and availability of water for humans and wildlife. In order to increase understanding of urban ecohydrology, we investigated the variability of planktonic bacteria and benthic diatoms - as two key biological indicators - coupled with insights from hydrochemistry and stable water isotopes across four urban streams characterized by different dominant water sources in Berlin, the German capital, over a period of one year (2021–2022). DNA metabarcoding results show that substantial spatio-temporal variability exists across urban streams in terms of microbial diversity and richness, with clear links to abiotic factors and nutrient concentrations. Bacterial communities showed clear distinction between effluent-impacted and non-effluent impacted streams as well as clear seasonal turnover. In-stream benthic diatom assemblages also showed robust seasonal variation as well as high species diversity. Our multiple-tracer approach is relevant for emerging questions regarding the increased use of treated effluent to supplement declining baseflows, the assessment of stream restoration projects and the impact of storm drainage and surface pollution on aquatic ecosystem health. eDNA analysis allows analysis of spatial and temporal patterns not feasibly studied with traditional analyses of macroinvertebrates. This can ultimately be leveraged for future water resource management and restoration planning and monitoring of urban freshwater systems across metropolitan areas.

Synergistic ecological network approach for sustainable development of highly urbanized area in the Bay Bottom region: A study in Chengyang District, Qingdao

Rapid urbanization has put the marine environment under great threat, and cities in the Bay Bottom area are more likely to cause a large number of ecological problems in urban development and construction due to their special land-sea interaction environment. Ecological network is an effective solution to coordinate regional ecological protection and sustainable urban development. This study focused on Chengyang District, one of the highly urbanized areas at the bottom of Jiaozhou Bay in Qingdao, China, was using Morphological Spatial Pattern Analysis (MSPA) to initially identify ecological source areas and extracting important ecological source areas in conjunction with the landscape connectivity assessment, and was determining ecological resistance values based on the importance of ecosystem services, and was optimizing ecological network by the minimum cumulative resistance model (MCR) and network structure analysis. The results indicated that: (1) the habitat in Chengyang District is severely fragmented, and the ecological network structure has significant features in terms of source area, type and corridor distribution, with a low percentage of source area, identification of characteristic source types such as reservoirs, wetlands, and aquaculture ponds, while the corridors are concentrated in the area of rivers and bays, and there is fragmentation in the inland areas of the city. (2) Preliminarily, 15 ecological source sites were identified, mainly distributed in the vicinity of Jiaozhou Bay Wetland, Jihongtan Reservoir and Laoshan Mountain, among which, Jiaozhou Bay Wetland is the most important ecological source in Chengyang District. Thirty-two ecological nodes and 24 ecological corridors were constructed. (3) By increasing the inland ecological sources in Chengyang District, the optimized ecological network forms a spatial pattern of “four cores, three belts, and four districts”, and proposes and formulates targeted ecological protection and management strategies to promote the sustainable development of the urban areas in the bottom of the bay. In addition, this study provides a new reference for the global ecological protection of cities in the bay area by improving the ecological network of cities in the Bay Bottom area.

Research on Development and Protection of Cultural Heritage Tourism Resources in the Age of Artificial Intelligence

Abstract This paper constructs the basic framework of the spatial pattern analysis method of historical, cultural heritage with the relevant technology of artificial intelligence and analyzes the spatial pattern of historical cultural heritage through spatial correlation analysis. ArcGIS and FineBI software are used to carry out correlation analysis on the degree of spatial aggregation, spatial distribution density, and related point and line distribution of cultural heritage tourism resources so as to derive the spatial distribution characteristics of cultural heritage tourism resources. Shanzhou Region, Sanmenxia City, Henan Province, is taken as the research object to empirically analyze the development and protection of its cultural heritage tourism resources. The results show that the values of global autocorrelation Moran’s I of spatial mismatch of cultural heritage tourism resources are all positive, and the mean value of Z(I) is 6.07956, P(I)&lt;0.05, indicating that the spatial mismatch index of cultural heritage tourism resources at the city level has a significant spatial clustering tendency and an obvious clustering tendency. This study offers scientific suggestions for the development of cultural heritage resources in tourism, and it is also crucial for the development of Chinese cultural heritage sites.

Temporal and Spatial Analysis of Vegetation Cover Distribution Patterns in Northern Basrah Governorate Using Geomatics Techniques

The study conducted within the administrative boundaries of Basrah Governorate, Iraq extending from the southern borders of Al-Haritha district to the northern borders of Al-Qurna district along the Shatt al-Arab River and its adjacent areas with a total area of approximately 354,450 Km2 . Landsat8Satellite imagery data were acquired processed and analyzed for the study area for the year 2022 covering four time periods with a temporal interval of three months each. The data were obtained from the Earth-observing sensors, specifically the Operational Land Imager (OLI). Subsequently a vegetation cover index was derived for the purpose of temporal and spatial monitoring and analysis aiding in the acquisition study and interpretation of agricultural activity patterns. The results revealed a clear temporal variation as the vegetation cover index showed an increase in the months of October and April, while the lowest values were recorded in January and July across all study stages. Field of remote sensing and vegetation analysis helps reduce the effort and time required.

Spatial analysis of primary healthcare accessibility patterns in Migori County, Kenya

The inequitable and insufficient evidence-based allocation of health resources has exacerbated the health disparities in developing nations. Indicators of inadequate accessibility and misuse of health resources include urban-centered health facility site selection and overlapping health service areas. This research employed Service area analysis and the Maximum Covering Location Problem (MCLP) to assess spatial accessibility while considering the operational schedules of basic healthcare providers. Utilizing the motorbike model, the spatial accessibility to basic healthcare facilities amounted to 84%. However, certain facilities did not operate during weekends or around the clock. During the weekends, accessibility decreased to 60%, and for 24-hour accessibility, it dropped to 49%. Consequently, it is evident that the operating hours of healthcare facilities have a significant effect on spatial accessibility. This study proposed the upgrade of strategically positioned healthcare facilities to enhance spatial access and bolster the referral network for the local population.

Distinguishing Laparoscopic Surgery Experts from Novices Using EEG Topographic Features.

The study aimed to differentiate experts from novices in laparoscopic surgery tasks using electroencephalogram (EEG) topographic features. A microstate-based common spatial pattern (CSP) analysis with linear discriminant analysis (LDA) was compared to a topography-preserving convolutional neural network (CNN) approach. Expert surgeons (N = 10) and novice medical residents (N = 13) performed laparoscopic suturing tasks, and EEG data from 8 experts and 13 novices were analysed. Microstate-based CSP with LDA revealed distinct spatial patterns in the frontal and parietal cortices for experts, while novices showed frontal cortex involvement. The 3D CNN model (ESNet) demonstrated a superior classification performance (accuracy > 98%, sensitivity 99.30%, specificity 99.70%, F1 score 98.51%, MCC 97.56%) compared to the microstate based CSP analysis with LDA (accuracy ~90%). Combining spatial and temporal information in the 3D CNN model enhanced classifier accuracy and highlighted the importance of the parietal-temporal-occipital association region in differentiating experts and novices.

Система мониторинга природной динамики лесного массива заповедника «Костомукшский»

The concept and current results of setting up the forest monitoring network at the Kostomukshska Strict Nature Reserve (Zapovednik) are presented. It has been demonstrated that pine forests predominate in the reserve’s forest cover (80.4 % of the forested area), followed by spruce (19.1 %) and birch (0.5 %). The ecological spectrum of the reserve’s forests comprises 7 groups of forest types, with the bilberry group prevailing (67 %) both among pine and among spruce stands. In terms of age structure, coniferous stands in the reserve are even-aged, multi-aged and all-aged, representing stages of the post-catastrophic regeneration succession and phases of subclimax and climax community cycles. Analysis of spatial patterns in the distribution of pristine and secondary forests has shown that anthropogenically altered forests are mainly situated in the western part of the reserve, at the border with Finland. The eastern part is a concentration of pristine north-taiga forests with a distinct mosaic of natural age dynamics phases. It was suggested that the forest monitoring network should be based on the landscape typological and spatial-temporal approaches taking into account the sublandscape-level structure of the reserve’s natural territorial complex and the distribution of forests in the study area by the rate of anthropogenic influence, prevalent species, forest types, and age structure types. Permanent sample plots will be established within 3 model areas (sites). For each of the 5 forest types of pine and 2 types of spruce stands, such plots should represent all age groups of even-aged stands (4 sample plots at maximum), and at least one sample plot should be allocated for each type (subtype) of the uneven-aged structure. The preliminary estimate is that, in total, there should be at least 98 permanent sample plots in the forest monitoring network of the Kostomukshskiy Zapovednik. So many units are needed to work out the algorithm for correcting the existing forest compartment characteristics given by the forest inventory in what concerns the age structure and the succession phase of stands. It is foreseen that all the factual material thus amassed will serve as the basis for modeling the scenarios of the natural dynamics of this forest massif and, perhaps, of other objects with similar structure. For citation: Raevsky B.V., Ilinov A.A., Medvedeva M.V., Rudkovskaya O.V. The Natural Dynamics Monitoring System of the Forests in the Kostomukshsky Reserve. Lesnoy Zhurnal = Russian Forestry Journal, 2023, no. 6, pp. 81–101. (In Russ.). https://doi.org/10.37482/0536-1036-2023-6-81-101

Which green is more equitable? A study of urban green space equity based on morphological spatial patterns

Urban green space (UGS) is an important factor in sustainable urban development. However, cities often experience unequal access to UGSs during the process of development, due to factors such as shrinkage and spreading. Many cities worldwide are facing urban shrinkage, which may lead to the deterioration of urban spatial environments and aggravation of inequities. In addition, due to urban land and financial constraints, it is not possible to maintain UGS equity by simply increasing the number of UGSs. Therefore, it is necessary to explore what defines a reasonable UGS structure from an equity perspective to support sustainable urban development. In this study, the UGS equity index of Yokosuka City was measured using the Gini coefficient. Morphological spatial pattern analysis (MSPA) was used to understand the morphological structure of UGSs in different regions and to transform them into potential structural classes. Finally, a UGS equity prediction model was constructed by ridge regression to provide a UGS morphological structure that is conducive to equitable UGS development. The main results indicate that 1) UGS inequity exists in Yokosuka; 2) no relationship was found between population decline and UGS inequity in Yokosuka; 3) UGS distribution is more equitable in towns with higher land values and population aging; 4) Islet, edge, loop, and branch components play an important role in the equitable development of UGS, and their corresponding potential UGS morphology is fragmentation, complexity, internal connectivity, and partial connectivity, respectively. This study further improves the analytical framework for describing the morphological structure of UGSs based on MSPA from a morphological perspective and provides a spatial morphological strategy to support the equitable development of UGSs.

Construction and Optimisation of Ecological Networks in High-Density Central Urban Areas: The Case of Fuzhou City, China

Constructing and optimising ecological networks in high-density cities plays an important role in mitigating urban ecological problems. Our study uses comprehensive evaluation methods such as Morphological Spatial Pattern Analysis (MSPA), the Remote Sensing Ecological Index (RSEI), and Connectivity to identify ecological source areas in Fuzhou City, and constructs and optimises the network using the Minimum Cumulative Resistance (MCR) model, current theory, and other methods. Meanwhile, the changes in urban landscape connectivity under different development scenarios were explored. The results show that the following: (1) the identification of ecological source sites based on the integrated approach is better than the single MSPA method; (2) the ecological network of Fuzhou City consists of 44 ecological source sites and 92 corridors; and (3) among the various development modes, transforming the top 30% of the bare land patches in Fuzhou City into green spaces improves the overall connectivity of the ecological network the most. The results can provide auxiliary decision-making for ecological construction in high-density cities.