Spatial Analysis Methods Research Articles

Spatial analysis by current multiplexed imaging technologies for the molecular characterisation of cancer tissues.

Tumours are composed of tumour cells and the surrounding tumour microenvironment (TME), and the molecular characterisation of the various elements of the TME and their interactions is essential for elucidating the mechanisms of tumour progression and developing better therapeutic strategies. Multiplex imaging is a technique that can quantify the expression of multiple protein markers on the same tissue section while maintaining spatial positioning, and this method has been rapidly developed in cancer research in recent years. Many multiplex imaging technologies and spatial analysis methods are emerging, and the elucidation of their principles and features is essential. In this review, we provide an overview of the latest multiplex imaging techniques by type of imaging and staining method and an introduction to image analysis methods, primarily focusing on spatial cellular properties, providing deeper insight into tumour organisation and spatial molecular biology in the TME.

Spatial–Temporal Variation and the Influencing Factors of NO2 Column Concentration in the Plateau Mountains of Southwest China

Given the complex terrain and economic development status of Guizhou Province, research on tropospheric NO2 column concentration using satellite remote sensing is still insufficient. Observing the spatial–temporal evolution characteristics of tropospheric NO2 column concentration can ensure the stable development of air quality. Based on the Google Earth Engine (GEE) platform, NO2 column concentration data retrieved from Sentinel-5P TROPOMI were analyzed using spatial autocorrelation, hotspot analysis, and geographic detector methods (Geodetector). The results show that NO2 column concentration in Guizhou Province exhibits seasonal variation, characterized by higher levels in winter and lower levels in summer, with transitional values in spring and autumn. The annual average concentration was highest in 2021 at 3.47 × 10−5 mol/m2 and lowest in 2022 at 2.85 × 10−5 mol/m2. Spatially, NO2 column concentration displays a distribution pattern of “high in the west, low in the east; high in the north, low in the south”, with significant spatial clustering. The distribution of cold and hot spots aligns with areas of high and low values. NO2 column concentration is primarily influenced by socio-economic factors, with the interaction between any two factors enhancing the explanatory power of individual factors on NO2 column concentration.

An Analysis of the Spatiotemporal Distribution and Influencing Factors of National Intangible Cultural Heritage along the Grand Canal of China

Intangible cultural heritage (ICH) reflects a region’s history and culture, serving as a significant indicator of regional identity and cohesion. The Grand Canal Basin in China is rich in historical traditions, containing a rich array of ICH resources. Analyzing the spatiotemporal distribution characteristics and influencing factors of ICH within the Grand Canal Basin of China can provide a scientific basis for developing cultural industries and promoting sustainable regional economic growth. This study employed GIS-based spatial analysis methods, including kernel density estimation, the mean nearest neighbor index, and standard deviation ellipse, to investigate the spatiotemporal distribution of 504 national-level ICH items (including extensions) in the Grand Canal Basin of China. The results demonstrate the significant spatial clustering of ICH, with concentrations in high-density regions, particularly at the northern and southern ends of the canal. There is significant regional disparity in the distribution of ICH, with an uneven quantity and structure, predominantly featuring traditional skills and traditional drama categories. The average centroid shift of ICH exhibits a north-to-south oscillatory trajectory. However, overall, it demonstrates a southward-moving trend. This study also underscores the impacts of urbanization, population density, economic development, and transportation infrastructure on ICH distribution. Among these factors, urbanization exerts the strongest influence on the spatial distribution of ICH. The impact of the natural environment is relatively minor; however, it remains a significant element that cannot be overlooked during development. This research offers valuable data and insights for local governments and institutions to formulate evidence-based strategies for the protection and sustainable utilization of ICH resources, promoting sustainable cultural and economic development in the Grand Canal Basin.

Spatiotemporal Evolution and Driving Factors of Land Use Carbon Emissions in Jiangxi Province, China

Analyzing the spatiotemporal changes and influencing factors of carbon emissions generated by land use is of great importance for improving land use structure and promoting regional low-carbon economic development. This study, based on remote sensing and statistical yearbook data from 1995 to 2020, calculated the carbon emissions from land use in Jiangxi Province, China. Multiple spatial analysis methods and the logarithmic mean Divisia index were used to elucidate the spatiotemporal evolution and driving factors of carbon emissions, and the findings revealed the following: (1) The spatiotemporal changes in land use in Jiangxi Province during 1995–2020 were substantial as forest land accounted for 65% of the entire land area, while construction land increased by 98.1%. Cultivated land decreased the most, followed by forest land. (2) There was a fourfold rise in carbon emissions in Jiangxi Province, driven primarily by construction land, and northern areas produced higher carbon emissions compared with central and southern regions. Forest land was the main carbon sink. (3) Economic development (257.36%) and the impact of the proportion of construction land (211.31%) were the primary factors contributing to the increase in carbon emissions from land use, while other factors had inhibitory effects. This study transformed the macroscale low-carbon development strategy of cities into targeted local policies, and the research theories and methods adopted could provide scientific reference for other regions in urgent need of carbon reduction worldwide.

Spatiotemporal Analysis of Open Biomass Burning in Guangxi Province, China, from 2012 to 2023 Based on VIIRS

Open biomass burning has significant adverse effects on regional air quality, climate change, and human health. Extensive open biomass burning is detected in most regions of China, and capturing the characteristics of open biomass burning and understanding its influencing factors are important prerequisites for regulating open biomass burning. The characteristics of open biomass burning have been widely investigated at the national scale, with regional studies often focusing on northeast China, but few studies have examined regional discrepancies in spatiotemporal variations over a long timescale in Guangxi province. In this study, we used the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG), combined with land cover data and high-resolution remote sensing images, to extract open biomass burning (crop residue burning and forest fire) fire points in Guangxi province from 2012 to 2023. We explored the spatial density distribution and temporal variation of open biomass burning using spatial analysis methods and statistical methods, respectively. Furthermore, we analyzed the driving forces of open biomass burning in Guangxi province from natural (topography, climate, and plant schedule), policy, and social (crop production and cultural customs) perspectives. The results show that open biomass burning is concentrated in the central, eastern, and southern parts of the study area, where there are frequent agricultural activities and abundant forests. At the city level, the highest numbers of fire points were found in Baise, Yulin, Wuzhou, and Nanning. The open biomass burning fire points exhibited large annual variation, with high levels from 2013 to 2015 and a remarkable decrease from 2016 to 2020 under strict control measures; however, inconsistent enforcement led to a significant rebound in fire points from 2021 to 2023. Forest fires are the predominant type of open biomass burning in the region, with forest fires and crop residue burning accounting for 76.82% and 23.18% of the total, respectively. The peak period for crop residue burning occurs in the winter, influenced mainly by topography, planting schedules, crop production, and policies, while forest fires predominantly occur in the winter and spring, primarily influenced by topography, climate, and cultural customs. The results indicate that identifying the driving forces behind spatiotemporal variations is essential for the effective management of open biomass burning.

Analysis of the spatial characteristics and driving forces of underground consumer service space in Chinese megacities based on multi-source data

Underground consumer service spaces (UCSS) offer new solutions for urban residents’ daily needs, but existing studies on their distribution and driving forces are often fragmented and overshadowed by research on other underground spaces, lacking targeted analysis. This study examines UCSS in the central urban areas of seven representative Chinese megacities. Using spatial analysis methods like kernel density estimation, multi-distance spatial clustering, and geographical detectors, the spatial characteristics and driving forces of UCSS are analyzed alongside aboveground consumer service spaces (ACSS). Results show that both ACSS and UCSS exhibit multi-centered, concentric spatial patterns, though UCSS demonstrates higher spatial aggregation. Unlike other underground public spaces (UPS), UCSS relies more on service industry agglomeration and market factors, while other UPS are more influenced by surrounding development intensity. UCSS follows the core principles of central place theory but deviates from the market-driven patterns typical of ACSS. Socioeconomic conditions and transportation infrastructure form the foundational basis for UCSS distribution, while service industry agglomeration, market dependence, and land development intensity exert more direct influence. The commercial atmosphere and existing underground space development play critical roles in UCSS distribution. Two key spatial scales for understanding UCSS distribution are the strong influence zones of shopping malls and metro stations, and high-density urban areas.

Spatial Big Data and Analysis Strategies Supporting Geographic Information System for Transportation (GIS-T) in Conceptual Design, Modelling, and Decision-making: A Review

Abstract. Transportation is a key component in urban design for cities’ efficiency and residents’ life quality, and GIS has the capability of handling data management, model design, and scientific decision-making for transportation studies. This article reviews how spatial big data and analysis strategies help GIS-T studies from the phases of conceptual design, modelling, and decision-making. In this research, we firstly summarized categorizes of data objects and relevant information for real-world issues from transportation applications in the conceptual design phase. In the modelling phase, optimization strategies for transport planning and accessibility measures through network data were also summarized. Finally, we reviewed spatial analysis methods in supporting transport decision-making, and how spatial methods take advantage of geography features of transport variables in previous studies. Our research primarily focuses on geography research with transportation topics as applications, and this work can help transport experts to have a better understanding of GIS values for transportation modelling and planning.

Analysis of the Spatiotemporal Distribution Characteristics and Influencing Factors of High-Grade Cultural Heritage in the Region Surrounding Mount Song

Situated in central China, the region surrounding Mount Song is a pivotal area within the Central Plains, renowned for its extensive and high-grade cultural heritage. This study aims to analyze the spatiotemporal distribution of this heritage using advanced spatial pattern analysis methods, including the Average Nearest Neighbor Ratio and Kernel Density Estimation within ArcGIS. Our findings reveal a distinct continuity in temporal distribution and a pronounced clustering in spatial terms. By investigating the underlying factors such as the geographical setting, historical political capitals, cultural and religious influences, water transportation systems, and traditional Fengshan ceremonies, this research elucidates the dynamics shaping this distribution. This study’s outcomes provide essential insights for policymakers and stakeholders involved in the protection and revitalization of cultural heritage, ensuring informed decision making for sustainable cultural conservation.

Analysis on Ecological Network Pattern Changes in the Pearl River Delta Forest Urban Agglomeration from 2000 to 2020

The advancement of urbanization has led to a decline in the ecological function and environmental quality of cities, seriously reducing the services and sustainable development capacity of urban ecosystems. The construction of the National Forest Urban Agglomeration of China is conducive to alleviating the ecological and environmental problems brought about by rapid urbanization and promoting sustainable urban development. A time series analysis of ecological network changes can quickly and effectively explore the development and changes of ecological spatial patterns over time. Identifying ecological protection and restoration areas in urban agglomerations is an important way to promote ecosystem restoration and optimize ecological networks. This paper takes the Pearl River Delta forest urban agglomeration as the research area, uses multi-source remote sensing data from 2000 to 2020 (every 5 years), identifies ecological sources based on the morphological spatial pattern analysis (MSPA) method, generates ecological corridors based on the minimum cumulative resistance (MCR) model, constructs a time series ecological network pattern in the Pearl River Delta region, and analyzes the evolution process of the ecological network pattern over time. The results indicate that over time, the core green area in the ecological network pattern of the Pearl River Delta first decreased and then increased, and the complexity of ecological corridors first decreased and then increased. The main reason is that the urbanization process in the early 21st century led to severe ecological fragmentation. Under the promotion of the national forest urban agglomeration construction, the ecological network pattern of the Pearl River Delta was restored in 2015 and 2020. The time series analysis of the ecological network pattern in the Pearl River Delta region of this research confirms the effectiveness of the construction of forest urban agglomerations, providing a scientific reference for the identification of ecological networks and optimization of spatial patterns in forest urban agglomerations.

Spatio-temporal behaviour of cruise passengers at the destination: a big data approach using mobile location events

Purpose The purpose of this paper is to provide a deeper understanding of the spatio-temporal behaviour of cruise passengers at a given destination using the city of Hamburg as a use case. Design/methodology/approach Big data in the form of passive location events from smartphones were analysed to determine the spatio-temporal behaviour of cruise tourists. The data were filtered using a definition created specifically for determining the signals of cruise passengers and were analysed using spatial statistics and network analysis methods. Findings In Hamburg, cruise passengers have a relatively small area of activity that is concentrated in the city's core tourist area. Foreign cruise passengers are less spatially concentrated than German passengers. Foreign passengers generate most of their visits at the airport and in the city's shopping areas, while German passengers are most frequently seen at the railway station and at the city's maritime experience locations. Originality/value Although numerous publications have examined the spatio-temporal behaviour of cruise passengers at the destination, to the best of the authors’ knowledge, no studies have used big data sources for this purpose. This paper uses passive location events from smartphones to determine the routes taken by cruise tourists in Hamburg, shows the strengths and weaknesses of this data source and suggests how cruise tourists can be defined from the data.

Characteristics, Source Apportionment, and Health Risk of Heavy Metals in the Soils of Peri-urban Shanghai Chongming Island.

Heavy metals resulting from human activities pose significant threats to human health and the soil ecosystem. In the current study, 917 soil samples from Chongming Island in Shanghai, China, were examined for eight heavy metals. The sources of contamination were identified by using a Positive Matrix Factorization (PMF) model. Meanwhile, spatial interpolation and Moran's I index were applied to validate the model in terms of spatial linkages. The results revealed that the average concentrations of As, Cd, Hg, Pb, Cr, Cu, Zn, and Ni in the soil were 8.87, 0.19, 0.06, 28.75, 76.01, 37.74, 88.93, and 30.33 mg kg-1, respectively. The PMF analysis proved that heavy metals in the soil of the study area are mainly influenced by traffic sources (Cr and Pb), industrial sources (Zn, Cd, and Cu), station sources (Hg), and natural sources (As and Ni), with contribution rates of 22.23, 26.25, 36.38, and 15.14%, respectively. The combination of Moran's index and the spatial analysis method not only verified the analytical results of the receptor model on the one hand but also served as a supplementary explanation for the sources of heavy metals in the soil. The health risk assessment indicated that noncarcinogenic values were below the threshold values. The total carcinogenic risk (R T) of different heavy metals has a descending order of Cr > As > Ni > Cd. The R T values of multiple heavy metals for children and adults were 5.28 × 10-04 and 4.10 × 10-05, respectively, which were close to the risk threshold. Therefore, attention should be paid to the health risks, especially for children's skin contact, which is the main exposure pathway.

Spatial patterns of electoral support in the 2023 general election in Poland

RESEARCH OBJECTIVE: This article focuses on identifying the spatial patterns of electoral support for the main political actors, and searching for adequate determinants that explain this distribution of support, based on the results of the 2023 general election in Poland. THE RESEARCH PROBLEM AND METHODS: Is there a relationship between the basic morphological features of the voting space in Poland and the hierarchy of the settlement structure, along with the arrangement of regions associated with the country’s historical and political heritage? The methods used in the study include analysis of descriptive statistics, estimation of spatial autocorrelation, discriminant analysis, and cartographic methods. PROCESS OF ARGUMENTATION: The research process involves a two-stage procedure: 1) identifying a general picture of spatial variation in electoral support for selected groupings, and basic clustering patterns of electoral support; and 2) estimating links between the observed patterns of support and their presumed determinants; that is, the country’s settlement hierarchy and historical-political divisions. RESEARCH RESULTS: The spatial variability of the support indicators is characterised by a distinctive territorial distribution, based on the units of the settlement system and the boundaries of former historical divisions. The nature of this linkage indicates the changing layout of the voting space, associated with the increasing polarisation of citizens’ political preferences. CONCLUSIONS, INNOVATIONS, AND RECOMMENDATIONS: The current pattern of urban-rural differentiation is related to the different preferences of metropolitan (over 20,000 inhabitants) and rural or small-town (up to 20,000 inhabitants) communities. The east-west heterogeneity of Poland’s voting space is increasing due to similarities of preferences among the inhabitants of former Austrian and Russian Poland, on the one hand, and Prussian Poland and the Recovered Territories, on the other.

Does Urban Green Space Pattern Affect Green Space Noise Reduction?

The effect of urban green spaces on traffic noise reduction has been extensively studied at the level of single vegetation, hedges, etc., but there is a lack of corresponding studies at the scale of spatial patterns of urban green spaces. Therefore, this study aims to analyze the relationship between the spatial pattern of urban green space and the change in green space’s noise reduction capacity. Through the morphology spatial pattern analysis method, this analysis divides the urban green space in the Fuzhou high-tech zone into seven types of elements with different ecological definitions and simulates the noise condition of the urban environment with the presence of green space as well as without the presence of green space by computer simulation, calculates the distribution map of the noise reduction produced by the urban green space, and analyzes the correlation between the seven types of green space elements and the noise reduction with the geographically weighted regression modeling analysis. The study finds that (1) Urban green space patterns can significantly affect the net noise reduction of green space. Areas with high green coverage can produce a stronger green space noise reduction effect. (2) More complex green space shapes and more fragmented urban green space can produce higher noise reduction. (3) The green space close to the source of noise can exert a stronger noise reduction effect. Therefore, in the process of planning and design, from the perspective of improving the urban acoustic environment, the configuration of high-quality green spaces in areas with higher levels of noise pollution should be given priority, which may have better noise reduction effects.

A method for quantitative spatial analysis of immunolabeled fibers at regenerative electrode interfaces

BackgroundRegenerative electrodes are being explored as robust peripheral nerve interfaces for neuro-prosthetic control and sensory feedback. Current designs differ in electrode number, spatial arrangement, and porosity which impacts the regeneration, activation, and spatial distribution of fibers at the device interface. Knowledge of sensory and motor fiber distributions are important in optimizing selective fiber activation and recording. New MethodWe use confocal microscopy and immunofluorescence methods to conduct spatial analysis of immunolabeled fibers across whole nerve cross sections. ResultsThis protocol was implemented to characterize motor fiber distribution within 3 macro-sieve electrode regenerated (MSE), 3 silicone-conduit regenerated, and 3 unmanipulated control rodent sciatic nerves. Total motor fiber counts were 1485 [SD: +/- 50.11], 1899 [SD: +/- 359], and 5732 [SD: +/- 1410] for control, MSE, and conduit nerves respectively. MSE motor fiber distributions exhibited evidence of deviation from complete spatial randomness and evidence of dispersion and clustering tendencies at varying scales. Notably, MSE motor fibers exhibited clustering within the central portion of the cross section, whereas conduit regenerated motor fibers exhibited clustering along the periphery. Comparison with Existing MethodsPrior exploration of fiber distributions at regenerative interfaces was limited to either quadrant-based density analysis of randomly sampled subregions or qualitative description. This method extends existing sample preparation and microscopy techniques to quantitatively assess immunolabeled fiber distributions within whole nerve cross-sections. ConclusionsThis approach is an effective way to examine the spatial organization of fiber subsets at regenerative electrode interfaces, enabling robust assessment of fiber distributions relative to electrode arrangement.

Urban Sprawl and Imbalance between Supply and Demand of Ecosystem Services: Evidence from China’s Yangtze River Delta Urban Agglomerations

The contradiction between ecological resource protection and urban sprawl in urban agglomeration areas is becoming more and more prominent, facing a serious imbalance between the supply and demand of ecosystem services. To analyze the impact of urban agglomeration expansion on regional ecosystem services, based on multi-source data, an assessment model of supply and demand of ecosystem services for water conservation, carbon sequestration, soil conservation and crop production was constructed. With the help of value transformation model and spatial analysis method, this paper explores the risk of ecosystem service supply and demand imbalance faced by the Yangtze River Delta urban agglomeration in the process of expansion. This study found that the supply capacity of ecosystem services in the YRDUA has continued to decline at the spatial pixel scale; ecosystem service value deficits are a common problem in the YRDUA, with cities around Taihu Lake, such as Shanghai and Suzhou, being the most serious; the value surplus areas are concentrated in the southern cities, such as Xuancheng and Chizhou, but the balance between the supply of and demand for ecosystem services in these cities is also facing a challenge as the cities are expanding. This study analyzed the spatial pattern changes in the Yangtze River Delta region in the context of urban sprawl from the perspective of ecosystem service supply and demand, which helps to clarify the changing ecosystem service dynamics of the region and guide the formulation of urban planning policies and to achieve a balance between ecological supply and demand as well as sustainable development.

The Role of Spatial Morphology in Forest Landscape Fragmentation: Insights From Planted and Natural Forests of the Chinese Loess Plateau

ABSTRACTThis study aimed to emphasize the key role of spatial morphology of planted and natural forests on landscape fragmentation and to furnish a scientific foundation for the effective assessment of ecological restoration projects of vegetation on the Loess Plateau. The spatial morphological pattern and landscape fragmentation characteristics were analyzed using morphological spatial pattern analysis (MSPA) and forest area density methods. This is the inaugural study to reveal the linear and nonlinear relationships between forest landscape fragmentation and its driving factors using machine learning methods and introducing morphological indicators with two different strategies. The results showed significant differences in the spatial patterns and landscape fragmentation characteristics between planted and natural forests. The spatial patterns of planted and natural forests were found to be dominated by “Core” in terms of area, while “Branch” was more prevalent in terms of number. Compared to natural forests, planted forests were more fragmented. The introduction of the MSPA indicator significantly enhanced the explanatory power and predictive performance of the model despite the disparate contribution rates of the driving factors in planted and natural forests. This study highlights the importance of spatial morphology in understanding forest landscape fragmentation and provides a new combination of analytical techniques to better understand the complexity of forest ecosystems. These provide new insights into forest landscape restoration and sustainable management on the Loess Plateau.

Analysis Methods for Landscapes and Features of Traditional Villages Based on Digital Technology—The Example of Puping Village in Zhangzhou

Many traditional villages have been degraded to a certain extent due to urbanization and out-of-control management. In addition, due to the lack of recognition and continuation of spatial texture in some village conservation and planning that, in turn, resulting in the gradual disappearance of their distinctive landscape feature. Studying the spatial form of traditional villages helps preserve the authenticity of traditional villages as cultural landscape and inherits traditional historical characteristics. Using Puping Village in Zhangzhou City, Fujian Province as an example, this paper obtains the integrated information data of the village through UAV oblique photography, classifies and extracts the spatial constitution of the traditional village using digital technology, quantitatively analyses it from macroscopic to microscopic, and summarizes the spatial morphology analysis method of the traditional village. The results demonstrate that digital technology can effectively and accurately complete data collection and can provide an objective basis for zoning conservation of traditional villages based on the distinction between new and historic buildings. In addition, digital information collection on the traditional villages landscape features will prepare for the establishment of a database and comparative analysis in the future. We further suggest that digital technology analysis needs to be combined with traditional methods to have a deeper understanding of the formation process of village spatial morphology. The results of the practice in Puping Village show that the use of digital technology can provide a scientific basis for the protection and planning of traditional villages, and that this method is adaptable, which can help to efficiently collect and analyze data on landscape characteristics of other similar villages in China, and support innovative methodologies and technologies for China’s rural revitalization efforts.

The Spatial Patterns and Building Policies of Rural Settlements in the Context of Demolition: The Case of Xian’an, China

In China, the “land-restructuring” policy provides balanced land for urban settlements that is strictly limited in expansion. Therefore, reassessing and adjusting the layout of rural settlements is of great practical significance for promoting rural revitalization. In this paper, taking Xian’an district in Hubei Province as an example, we use the weighted rank-sum ratio comprehensive evaluation method and spatial association analysis method to analyze the development level and spatial pattern of settlements. The results show that: (1) The development level of settlements in Xian’an shows obvious spatial differences, with a spatial pattern of ‘high in the core–low in the periphery’ and ‘high in the northwest–low in the southeast’, which is the result of the combined effect of natural geographical conditions and socioeconomic conditions; (2) The comprehensive development level of settlements, evaluated based on four major indicators—population size, resource endowment, spatial characteristics, and material construction—reveals the presence of cluster effects, distance decay effects, administrative hierarchy effects, and “long board” effects; (3) Within village communities, settlements with significantly high levels and settlements with significantly low levels have a similar geographic distribution and mosaic spatial patterns. Lastly, based on the overall development level and spatial association patterns of settlements, this article presents possible options for governmental settlement governance from the standpoint of rural building management.

The Impacts of Urban Population Growth and Shrinkage on the Urban Land Use Efficiency: A Case Study of the Northeastern Region of China

In the context of rapid urbanization, urban population differentiation has become increasingly pronounced. Regional development strategies based on growth scenarios often lead to continuous expansion, regardless of urban population status. Such “one-size-fits-all” models exacerbate resource waste and negatively impact urban land use efficiency (ULUE). This study aims to explore the mechanisms by which urban population growth and shrinkage (UPGS) affect ULUE, with the goal of enhancing ULUE and promoting sustainable urban development. We analyzed 34 prefecture-level cities in China’s three northeastern provinces. First, we identified UPGS using population data. We then employed a three-stage SBM-DEA model to measure ULUE from 2000 to 2020. Spatial analysis methods were used to examine the spatiotemporal characteristics and correlations between UPGS and ULUE. Additionally, mediating effect models and spatial Durbin models were utilized to empirically test the impact processes, mechanisms, and spatial heterogeneity. Our findings reveal that: (1) Over the past 20 years, urban population shrinkage in northeastern China has intensified, and significant regional disparities in urban development are evident. (2) Population growth positively influences ULUE, while population shrinkage inhibits its improvement. (3) Economic development, technological innovation, and industrial structure upgrading are key factors in enhancing ULUE in this region, while the impact of public services on ULUE varies significantly at different stages of urban development. (4) Economic development, technological innovation, and industrial structure upgrading exhibit spatial spillover effects, whereas public services are constrained by regional limitations, resulting in minimal spatial spillover effects. To foster coordinated regional development, this study proposes policy recommendations, including strengthening support for resource-dependent cities, optimizing the allocation of public resources, and promoting technological innovation and industrial diversification.

Study on Urban Growth of Pakse City

This research has considered the growth and important changes of Pakse city in Lao PDR from 2005 to 2020. The city is strategically located as a commercial and tourism center in the Mekong sub-region. In addition, Pakse's rapid urban growth is fueled by economic development, infrastructure improvements, demographic changes and strategic geographic location, all of which contribute to making it an important urban center in the south. The research aims to study the growth of the city of Pakse to create an understanding of the phenomenon, the driving force as well as the factors that lead to the growth of the city as a way to plan and control the development of the city for sustainable growth using the integrated research method of spatial analysis, quantitative analysis and document survey which analyzes the growth of the population and households, economic growth and the growth of the urban area. The analysis results show a population increase of 32.30 percent (from 78,669 people in 2005 to 116,200 people in 2020). Economic growth is also clear GDP per capita increased by 56.86 percent (from 1,097 dollars in 2005 to 2,543 dollars in 2020). The growth of the construction area of the city increased by 47.03 percent (from 285 hectares in 2005 to 538 hectares in 2020) and in Pakse city municipality, there is a growth of 46.35 percent (from 279 hectares to 520 hectares in 2020). Most of the built-up area is concentrated in the city center, covering 96.65 percent, and the number of buildings has increased by 45.18 percent (from 17,262 to 30,870 in 2020). These findings indicate the growth of Pakse city during the study period.