Evolution Of Spatial Patterns Research Articles

El Niño‐La Niña Asymmetries in the Changes of ENSO Complexities and Dynamics Since 1990

AbstractIn around 1990, significant shifts occurred in the spatial pattern and temporal evolution of the El Niño‐Southern Oscillation (ENSO), with these shifts showing asymmetry between El Niño and La Niña phases. El Niño transitioned from the Eastern Pacific (EP) to the Central Pacific (CP) type, while La Niña's multi‐year (MY) events increased. These changes correlated with shifts in ENSO dynamics. Before 1990, El Niño was influenced by the Tropical Pacific (TP) ENSO dynamic, shifting to the Subtropical Pacific (SP) ENSO dynamic afterward, altering its spatial pattern. La Niña was influenced by the SP ENSO dynamic both before and after 1990 and has maintained the CP type. The strengthened SP ENSO dynamic since 1990, accompanied by enhanced precipitation efficiency during La Niña, make it easier for La Niña to transition into MY events. In contrast, there is no observed increase in precipitation efficiency during El Niño.

Analisis Perkembangan Kota Bukittinggi dan Sekitarnya Tahun 2005-2022 Menggunakan Metode Spatial Metric

The aim of this research is to: 1) Understand the physical development of Bukittinggi City and its surroundings in the period 2005-2015 and 2022, 2) Understand the spatial pattern of development of Bukittinggi City and its surroundings. This type of research is quantitative, using secondary data, namely SPOT images for the period 2005, 2015 and 2022. The analysis technique used is manual digitization to produce maps of built-up areas and metric spatial analysis to determine city development patterns using 5 methods, namely: PD , NP, LPI, LSI, and MPS. The overlay method is used to obtain patterns of development of built-up land regarding slopes, roads, distribution of facilities and population development. This research found: The physical development of the City of Bukittinggi and its surroundings in the period 2005-2022 shows a lot of development and improvement, which can be seen by the shrinking of non-built-up areas in each time period tending towards Urban Sprawl marked by an increase in built-up areas which spread towards the outskirts of the city. due to population growth. The development of built-up areas in the city of Bukittinggi and its surroundings tends to grow in areas with flat and gentle slopes and tends to gather on main and central roads, so it can be concluded that the development of the city of Bukittinggi and its surroundings is still concentric.

Spatiotemporal analysis of urban development patterns and COVID-19 in Mashhad, Iran

This study evaluates the impact of city spatial development patterns on the spread of airborne pandemics, focusing on Mashhad, Iran. Using ArcGIS spatial statistics, 91 spatial indices were examined between March 5, 2020, and October 2, 2021, during five distinct waves of the virus, revealing that private vehicle ownership and limited use of public transportation did not significantly reduce COVID-19 infection rates in Mashhad. Instead, factors such as proximity to transportation hubs, healthcare facility polarization, and retail shop distribution had a significant impact. Surprisingly, demographic vulnerability and conventional population-related factors had relatively minor effects. The study also highlights the influence of building concentration with high floor area ratios (FAR) and the impact of local authorities' optimism in reducing social distancing measures, especially in travel and traffic control, on the increased spread of the virus during recent waves.

Calculation of Urban Green Competitiveness and Analysis of Spatial and Temporal Evolution Characteristics in China

It is particularly important to analyze the influencing factors of urban green competitiveness and the spatial distribution characteristics under the constraint of carbon emissions. The research ideas of this paper: firstly, this paper selects the carbon emission intensity and urban green competitiveness data in 2010, 2013, 2015, 2018 and 2020 for panel data regression; secondly, this paper applies a variety of methods to carry out the robustness test, and the results show that the regression model is better, and analyzes the development of urban green competitiveness for the heterogeneity of large cities and small cities; subsequently, the use of inverse geographic matrix to analyze the spatial correlation between the global Moran index and local Moran index for urban green competitiveness, and to analyze the spatial and temporal pattern evolution of urban green competitiveness. The conclusions of the study show that, from the viewpoint of influencing factors, carbon emission intensity presents a significant negative effect on the development of urban green competitiveness, and has a greater impact on the green competitiveness of large cities than that of small cities. From the perspective of spatial correlation, urban green competitiveness presents positive spatial correlation and shows a growing trend over time. Finally, this paper puts forward relevant policy recommendations based on the findings of the study.

Mechanisms for realizing the ecological products value: Green finance intervention and support

The essence of ecological product value is the rational development and utilization of natural ecological and environmental resources, which are converted into social attributes or economic value. An accurate assessment of the value of ecological products is a prerequisite for realizing their economic value. However, few studies have measured the interaction mechanism between green finance and ecological products value. This study measured the ecological products value at the city level in China from 2010 to 2021, based on the dynamic equivalent moderator model. A spatial panel data model was used to analyze the spatial pattern and dynamic evolution of ecological products value and identify their driving factors. The ecological products value in China showed an increasing trend from 2010 to 2021, and there were obvious spatial correlations between regions. Green finance significantly contributes to the realization of ecological products value, and robust estimation results can still be obtained after controlling for endogeneity. Meanwhile, the role of green finance has a spatial spillover effect. This study provides a new research perspective for correctly assessing ecological products value and studying the role of green finance in realizing ecological products value.

Reducing the “digital divide” to reap the “digital dividend”: spatial differences and convergence of the digital economy in cities of China

Bridging the “digital divide” to benefit from the “digital dividend” reflects the inclusive development of the digital economy, which affects the sustainable development of the overall economy and society. Based on the different spatial perspectives of certain regions, city clusters, and cities, this study presents the “digital divide” and “digital dividend” for the development of China's digital economy. A combined entropy method was used to measure the development of the digital economy in cities of China from 2011 to 2019. The Dagum Gini coefficient and its decomposition were used to explore the spatial differences of the digital economy and their sources, while the coefficient of variation and the spatial panel model were used to examine the convergence of the digital economy. Our findings suggest that the development level of the digital economy in Chinese cities has continuously improved. Second, the spatial differences of the digital economy in the four regions and nine city clusters of China that were investigated are decreasing, indicating that the “digital divide” is narrowing and presenting a significant “digital dividend.” The total differences were mainly owing to those between the regions (among the city clusters). Third, the development of the digital economy in the four regions and nine city clusters demonstrated characteristics of σ, β, and club convergences. Finally, the evolution path of the spatial differentiation of the digital economy in cities of China is presented, and the “digital dividend” also demonstrates different stage characteristics. This study analyzed the spatial differences in the digital economy of cities in China and clarified the convergence and influence mechanisms of its development at different spatial scales. The findings provide a basis for the evolution of spatial and temporal patterns of the digital economy of cities in China and presents policy implications for promoting the regionally coordinated and sustainable development of the digital economy. Suggestions from the national and regional levels are more necessary to further narrow the “digital divide,” create a “digital dividend,” and digital drives sustainable economic development.

Study on the pattern evolution and reasons of the coordination between digital economy and green development

The Recommendations on the Fourteenth Five-Year Plan and the Vision and Goals for 2035 suggest that the digital economy and green development have risen to the level of a national strategy, and that the study of their coupling and coordination and their spatial relevance can serve as a strong theoretical support for major national strategies. Based on the connotation of digital economy and green development, this study analyses the evolution of the temporal and spatial patterns of digital economy and green development by plotting the temporal change of the coupling coordination degree and the kernel density estimation of the whole country and each region, respectively. Finally, based on the findings of this study, policy recommendations are made for China's digital economy and green development and the synergistic development of the two.

Spatio-temporal Evolution and Multi-scenario Simulation of Carbon Storage in Karst Regions of Central Guizhou Province：Taking Puding County as An Example

Regional land use change is the main cause for the change in karst carbon storage. It is important to analyze the spatial and temporal evolution and future spatial distribution trends of carbon storage in typical counties in central Guizhou's karst region， such as Puding County， to improve regional carbon storage， optimize land ecological security patterns， and promote low-carbon sustainable urban development. The PLUS-InVEST model was coupled， based on the interpreted land use data and future land prediction， the spatial and temporal evolution characteristics of land use change and carbon storage in Puding County from 1973 to 2020 were inverted， and the spatial pattern evolution of land use and carbon storage change under different scenarios in 2060 were simulated and predicted. The results showed： ① from 1973 to 2020， the overall carbon storage in Puding County increased by 6.61×105 t， showing an upward trend. The spatial distribution showed a significant increase in the northeastern and southwestern parts of Puding County and a significant decrease in the south-central parts. The change was due to the increase in carbon storage in dryland to shrubland and forest land and the decrease in carbon storage in areas where paddy fields are converted to construction land. ② The land use change in Puding County in the historical period was mainly reflected in the continuous expansion of construction land and the increased fluctuation of the proportion of forest land and shrub forest land， and the change in land use in different scenarios projected in 2060 retained the change characteristics of the historical period. ③ In 2060， the carbon storage in Puding County under the scenarios of natural evolution， ecological protection， and economic development increased by 2.93×105， 5.40×105， and 1.11×105 t， respectively， compared with that in 2020. Of these， the increase in ecological protection scenarios was the most significant， with the transfer of dryland to shrubland being the main reason for the increase in regional carbon sequestration capacity. These results can serve as a scientific reference for land use management decisions and the formulation of emission reduction and sink increase policies in Puding County. The future land use planning of karst areas should be guided by the goal of "carbon neutrality" in 2060， take appropriate ecological protection measures， strictly control the rapid expansion of construction land to paddy fields， optimize the land use structure， and effectively improve the level of regional carbon storage.

Spatial pattern evolution and driving factors of urban green technology innovation in China

Spatial pattern evolution and driving factors of urban green technology innovation in China

Study on spatial form evolution of traditional villages in Jiuguan under the influence of historic transportation network

Traditional villages are China's cultural heritage resources; they carry rich historical and cultural information and have important historical significance and cultural value. Studying their spatial forms can suggest new ideas for the protection of traditional villages. The spatial configuration of traditional villages is shaped by a complex interplay of natural geography, socio-economic factors, transportation infrastructure, and essential facilities. Various developmental scenarios lead to diverse spatial development patterns, each demonstrating unique dynamic characteristics throughout its evolution. This article focuses on the exploration of the spatial morphology of Jiuguan Village, located along the Jingxing Ancient Post Road. By using kernel density analysis, space syntax, spatial form index, and so on, the spatial form of Jiuguan Village was studied from three aspects: public facilities clustering degree, road system, and spatial form index. Through a hierarchical approach involving points, lines, and planes, our study unveils the multifaceted influence of transportation factors on the village's historical development and its dynamic adaptive attributes within the context of traditional village spatial morphology. The results indicated that the location advantage of traffic is the driving force behind land expansion. Secondly, the areas with high traffic accessibility tend to be public spaces in villages. Third, the change in the transportation market will lead to a change in village land use functions. Finally, the renewal of transportation modes will change the spatial scale of the village. This research offers a deeper comprehension of the historical context surrounding traditional villages and provides a scientifically guided framework for heritage preservation and sustainable village development.

A 31-year (1990–2020) global gridded population dataset generated by cluster analysis and statistical learning

Continuously monitoring global population spatial dynamics is crucial for implementing effective policies related to sustainable development, including epidemiology, urban planning, and global inequality. However, existing global gridded population data products lack consistent population estimates, making them unsuitable for time-series analysis. To address this issue, this study designed a data fusion framework based on cluster analysis and statistical learning approaches, which led to the generation of a continuous global gridded population dataset (GlobPOP). The GlobPOP dataset was evaluated through two-tier spatial and temporal validation to demonstrate its accuracy and applicability. The spatial validation results show that the GlobPOP dataset is highly accurate. The temporal validation results also reveal that the GlobPOP dataset performs consistently well across eight representative countries and cities despite their unique population dynamics. With the availability of GlobPOP datasets in both population count and population density formats, researchers and policymakers can leverage the new dataset to conduct time-series analysis of the population and explore the spatial patterns of population development at global, national, and city levels.

Genetic divergence and ecological adaptation of an eastern North American spring ephemeral Sanguinaria canadensis

AbstractAimDescription of the driving forces for genetic divergence is important for understanding spatial pattern of biodiversity and development of conservation plans. Paleo‐climate, geographical barriers and habitat heterogeneity are considered to be the main influential factors; however, an integrative study is still lacking to reveal their interactions.LocationEastern North America.MethodsHere, we generated MIG‐seq SNPs of 403 Sanguinaria canadensis samples and seven plastome data. The methods of phylogeography and landscape genomics were applied to infer their genetic divergence, demography, species distribution modelling, ecological differentiation and local adaptation.ResultsWe identified three distinct genetic lineages corresponding to geographical distributions isolated by the Appalachian Mountains and the Mississippi River. Ecological niche modelling and population demographic inference demonstrated that the response of S. canadensis to Pleistocene climate changes was consistent with the pattern of southward contraction during the ice age and northward recolonization during the inter−/postglacial period. Isolation in multiple southern refugia was a key factor resulting in the genetic divergence, whereas secondary contact triggered by repeated range shifts allowed gene flow among different lineages. A greater effect of isolation‐by‐environment than isolation‐by‐distance was founded, which suggested heterogeneous environment was also a promotor of genetic differentiation. Candidate adaptive loci related to transposable elements were identified under the influence of divergent environmental selection. Ecological niche divergence also reflected adaptation to different environments.Main ConclusionsThis study revealed that genetic divergence has occurred within S. canadensis populations under the combined effect of paleo‐climate, geographical barriers and habitat heterogeneity, and emphasized the necessity of establishing different conservation units in future biological conservation and management work.

Dynamic monitoring of vegetation growth in Engebei ecological demonstration area based on remote sensing

Vegetation growth and the ecological environment affect each other. Understanding vegetation growth trend and their spatial pattern evolution is of great significance for ecological environment assessment and protection. The spatial trend and pattern evolution of different vegetation growth in the ecological area are included in vegetation planning, which can be used as a reference for vegetation planning and development. Based on Landsat remote sensing data, the spatial evolution trend and dynamic evolution of vegetation patterns at different levels in the Engebei Ecological Demonstration Zone from 2000 to 2021 were revealed, and the degree of ecological vulnerability was determined. The results show that: during the growing season from 2000 to 2021, the vegetation growth of the study area showed an overall improvement trend (about 63.44%), and the vegetation growth trends was mainly not significant change (about 97.12%). The improvement of vegetation growth in the southern desert region was higher than that in the northern arid steppe region. In the future, the main growth types were non-significant improvement of sustainability, non-significant improvement of anti-sustainability, non-significant degradation of anti-sustainability, and non-significant degradation, accounting for 38.84%, 23.81%, 17.30%, and 17.16%, respectively. The spatial distribution of vegetation of different grades mainly showed aggregation patterns, and the spatial distribution evolvement was more and more uniform, the distribution range was gradually expanded, and the orientation was gradually weakened. The numerical clustering degree of ecological vulnerability of vegetation was constantly declining. The results can provide a scientific basis for vegetation planning in the Engebei ecological demonstration area.

Study on the multi-level evaluation method of small hydropower sustainable development

Currently, there is a lack of a comprehensive evaluation method for assessing the sustainability of small hydropower at different levels. This deficiency hinders the rational planning of small hydropower development and utilization, as well as the delicate balance between safeguarding and harnessing small hydropower resources. To address this gap, this study primarily focuses on establishing a comprehensive evaluation system for the sustainability of small hydropower at the international, national, and individual power station levels. On the international stage, an evaluation index system is formulated, and a national quantitative assessment model for small hydropower sustainability is developed using the Analytic Hierarchy Process (AHP) combined with fuzzy evaluation techniques. The research is exemplified by investigating countries within the Belt and Road Initiative. At the national level, models for assessing the overall development status and spatial distribution patterns of small hydropower are created. The study thoroughly examines the temporal and spatial evolution patterns and trends in the sustainable development of small hydropower in various provinces and states, with China serving as a case study. At the individual power station level, a green evaluation model is established to comprehensively assess small hydropower stations. This model considers ecological, social, managerial, and economic dimensions to evaluate the environmental sustainability of each small hydropower station.

Study on the Development Trends and Strategies of International Economy and Trade under the New Situation

Abstract In today’s increasingly globalized world, trade between countries has become more interconnected, and international trade has emerged as the primary driver of economic development for all nations. This paper proposes a standard trade model for the new situation using the Dixit-Stiglitz model. Starting from the consumer’s point of view, the two-stage maximum method is adopted. Using the Lagrange function, the demand utility function of consumer preferences is processed, and the model optimization scheme is deduced. The ARMA model is used to predict the volume of merchandise foreign trade, and the prediction range includes autoregressive and moving average processes. The indicators are used to evaluate the smoothness of the series within the sample period. A suitable sample of international trade data is selected. The results of the analysis are as follows: in the logistic autoregressive analysis test, the significance of all factors, except for the language and religion factors, passes the significance test of 0.001, and at the same time, the model goodness-of-fit is greater than 0.1, ranging from 0.115 to 0.175. In the analysis of the spatial evolution pattern of international economic trade and trade dynamic development, the spatial Gini coefficients of the first category of goods in 2000, 2014, and 2019 and the third category in 2000 are 0.4306, 0.4717, 0.4956, and 0.4673, respectively, which are lower than 0.5, showing a more balanced evolution pattern.

Multi-Scale Spatio-Temporal Fusion with Adaptive Brain Topology Learning for fMRI Based Neural Decoding.

Neural decoding aims to extract information from neurons' activities to reveal how the brain functions. Due to the inherent spatial and temporal characteristics of brain signals, spatio-temporal computing has become a hot topic for neural decoding. However, the extant spatio-temporal decoding methods usually use static brain topology, ignoring the dynamic patterns of the interaction between brain regions. Further, they do not identify the hierarchical organization of brain topology, leading to only superficial insight into brain spatio-temporal interactions. Therefore, here we propose a novel framework, the Multi-Scale Spatio-Temporal framework with Adaptive Brain Topology Learning (MSST-ABTL), for neural decoding. It includes two new capabilities to enhance spatio-temporal decoding: i) ABTL module, which learns dynamic brain topology while updating specific patterns of brain regions, ii) MSST module, which captures the association of spatial pattern and temporal evolution, and further enhances the interpretability of the learned dynamic topology from multi-scale perspective. We evaluated the framework on the public Human Connectome Project (HCP) dataset (resting-state and task-related fMRI data). The extensive experiments show that the proposed MSST-ABTL outperforms state-of-the-art methods on four evaluation metrics, and also can renew the neuroscientific discoveries in the brain's hierarchical patterns.

«Цифровой двойник» населения Арктики в демографических исследованиях и управлении развитием территорий

The article considers “digital twins” of the population as a tool for socio-demographic research and territorial management. The experience of creating digital twins of the population and interactive web-sites devoted to demographic issues is systematized. A methodology for creating a digital twin of the Arctic population is proposed, based on three methodological principles: consideration of the hierarchy of territories, spatial representation of data, and combining demographic statistics with new digital data sources. The author has developed the Digital twin of the Arctic population — an interactive website (dashboard) containing detailed data on the Arctic population, including municipal and settlement levels. It includes demographic statistics, census results and data from digital platforms. The Digital twin of the Arctic population covers such issues as the size, dynamics and composition of the population, resettlement, natural and migration movement, labor and employment, transport movements, science and education, and the impact of the pandemic on demographic processes. Tools of ranking, multivariate analysis, clustering and forecasting of indicator values are implemented for researchers. From the viewpoint of state and municipal management, the main interest is the demographic profiles of regions and territories, reflecting up-to-date information about the demographic situation. Using the Digital twin of the Arctic population, the author draws conclusions about the spatial patterns of the demographic development of the Russian Arctic.

Пилотные инновационные территориальные кластеры: пространственная дифференциация, закономерности развития и эффективность

The article is devoted to the study of an important component of innovative infrastructure – pilot innovative territorial clusters. The mainstages of their formation wereconsidered,spatial patterns of development,structure and economic efficiency were identified and analyzed. The purpose of the study is to analyze the spatial regularities of pilot innovative territorial clusters functioning to justify the promising directions of the state cluster policy contributing to the effective use of the financial resources of the federal budget by determining priority investment directions and establishing on this basis the recipients of state support in the cluster with the greatest potential in the context of limited financial resources. This is promising primarily for justifying the stimulation of new high-tech industries and enterprises. The study was carried out on the basis of materials from official federal and regional statistics, information and analytical reports of the Association of Clusters, Technoparks and SEZs of Russia, official ratings of regions innovative development, legislative acts of the federal and regional levels. Patterns of functioning and trends in the development of innovative territorial clusters have been identified. The main purpose of the emerging innovative territorial clusters is to saturate the huge domestic market with high-tech goods, services and technologies in order to achieve the country’s technological independence. Promising directions for improving the cluster policy of Russia are formulated.

Spatial Disparity of Sports Infrastructure Development and Urbanization Determinants in China: Evidence from the Sixth National Sports Venues Census

The improvement of well-being of residents is the core of the people-centred urbanization. Inhabitants’ emphasis on healthy lifestyle draws attention to the provision of sports infrastructure. However, the spatial pattern of sport infrastructure development and in particular the driving forces from urbanization across China have not been examined yet in the literature. This paper aims to explore how the national sports infrastructure in mainland China is driven and scaled by urbanization, using data from the sixth National Sports Venues Census and a multi-scale geographically weighted regression approach. The results revealed strong regional inequality in the development of sports infrastructure in the stage of accelerating urbanization in China, with better provision of sports infrastructure in eastern than in western regions. The three dimensions of urbanization (urban population, public financial expenditure and built-up area) significantly explained the spatial disparity between 289 cities at prefecture-city level. There should be a feedback loop between the accumulative developments of urbanization and sports infrastructure. The contributing driving forces and subsequent regional heterogeneity suggest that sports space theory, the inequality amplification model, and hysteresis effect are comparatively suitable for explaining the spatial inequality characteristics of sports infrastructure development in China. A Sport Inequality Alert was conceptualized as a policy instrument for monitoring regional inequality and governing the development of sports infrastructure. It is argued that sports infrastructure development should be integrated into the national strategy for sustainable New-type Urbanization.

Longitudinal development of the human white matter structural connectome and its association with brain transcriptomic and cellular architecture

From childhood to adolescence, the spatiotemporal development pattern of the human brain white matter connectome and its underlying transcriptomic and cellular mechanisms remain largely unknown. With a longitudinal diffusion MRI cohort of 604 participants, we map the developmental trajectory of the white matter connectome from global to regional levels and identify that most brain network properties followed a linear developmental trajectory. Importantly, connectome-transcriptomic analysis reveals that the spatial development pattern of white matter connectome is potentially regulated by the transcriptomic architecture, with positively correlated genes involve in ion transport- and development-related pathways expressed in excitatory and inhibitory neurons, and negatively correlated genes enriches in synapse- and development-related pathways expressed in astrocytes, inhibitory neurons and microglia. Additionally, the macroscale developmental pattern is also associated with myelin content and thicknesses of specific laminas. These findings offer insights into the underlying genetics and neural mechanisms of macroscale white matter connectome development from childhood to adolescence.