Preamble

Spatiotemporal Evolution and Obstacle Factor Analysis of Territorial Space Efficiency in the Yellow River Basin

College of Tourism, Henan Normal University, Xinxiang, Henan; School of Urban Economics and Public Administration, Capital University of Economics and Business, Beijing

Examining and identifying the evolutionary trends and hindering factors of territorial space efficiency in key river basins provides a critical foundation for constructing a territorial spatial pattern characterized by complementary advantages and high-quality development. Taking 91 cities in the Yellow River Basin as a case study area, this research utilizes spatial classification methods, Kernel Density Estimation (KDE), and the obstacle degree model to reveal the spatiotemporal evolution patterns and obstacle factors of territorial space efficiency in the region. The results indicate that:

Regarding evolutionary patterns, the territorial space efficiency of the Yellow River Basin exhibited a fluctuating upward trend from 2005 to 2020, with differences across various spatial domains following a trend of ecological space > urban space > agricultural space. 1) From the perspective of spatial differentiation, there is significant spatial heterogeneity in territorial space efficiency, and the agglomeration patterns of different spatial efficiencies show distinct regional disparities. 2) In terms of spatial agglomeration characteristics, the evolution of territorial space efficiency exhibits spatiotemporal inertia and continuity, with "High-High" and "Low-Low" clusters serving as the primary agglomeration modes. 3) Analysis of obstacle factors reveals that ecological space efficiency presents the highest degree of obstruction to the overall improvement of territorial space efficiency. Specifically, non-agricultural output value, agricultural irrigation area, and ecosystem service value are the primary obstacle factors hindering the improvement of urban, agricultural, and ecological space efficiency, respectively. These research findings provide a new perspective for deepening the theoretical understanding of territorial space efficiency in key river basins and offer scientific support for optimizing the territorial spatial layout and enhancing spatial governance levels in the Yellow River Basin.

关键词

Territorial spatial efficiency; Spatio-temporal variation; Obstacle analysis; Yellow River Basin. Article ID: Territorial spatial efficiency is a significant indicator for optimizing regional territorial spatial patterns and a key criterion for measuring the level of synergy between regional socio-economics, resources, and the environment. Since the reform and opening up, the comprehensive and in-depth advancement of urbanization and industrialization has led to numerous problems, such as spatial functional mismatches and inefficient utilization in localized areas. The 20th National Congress of the Communist Party of China explicitly proposed the spatial optimization goal of "building a regional economic layout and territorial spatial system characterized by complementary advantages and high-quality development." It emphasized relying on territorial spatial planning to construct a management and control pattern for "urban space, agricultural space, and ecological space" that develops in coordination. As an important ecological barrier and economic belt in China, the Yellow River Basin supports the survival and development of the people along its course. It currently faces the dilemma of transitioning from "single-dimensional breakthroughs in spatial development" to "improving quality and efficiency through comprehensive utilization." Therefore, during this critical period of promoting coordinated and orderly development in the Yellow River Basin, addressing how to strengthen territorial spatial governance, build a high-quality territorial spatial system, and scientifically understand spatial functions and regional differentiation patterns has become a core issue for resolving conflicts between major functional zones and achieving sustainable development in the new era.

Given the urgency and necessity of optimizing territorial spatial patterns, the academic community has conducted extensive research on the laws of territorial spatial evolution. From the perspective of research systems, existing studies include analyses of territorial spatial patterns and functional evolution from a "production-living-ecological" perspective, as well as evaluations of territorial spatial functions and efficiency at the "urban-agricultural-ecological" spatial scale. With the accumulation of practical experience in territorial spatial planning, the latter is considered more consistent with planning realities. It represents an objective transition from "three-living spaces" to "three zones and three lines" research and better reflects the intersectionality and correlation between territorial spatial functions. Regarding methodologies, parametric methods represented by Stochastic Frontier Analysis (SFA) and non-parametric methods represented by Super-Efficiency models have become mainstream; both overcome the limitation where "efficiency values cannot be compared when they equal 1." In terms of research scales, the popularization of big data has facilitated diversified and comprehensive research extending from the national level to key river basins, economic belts, and typical urban scales. Regarding driving mechanisms, studies have explored both internal background factors, such as topography, temperature, and precipitation, and external socio-economic factors, such as "economic development and opening up."

These studies have laid a solid foundation for effectively constructing a territorial spatial layout with complementary advantages. Due to the uniqueness and importance of the natural environment and geographical location of the Yellow River Basin, research on the evolution of territorial spatial patterns and regional high-quality development in this area has provided important decision-making references for the formulation and implementation of spatial optimization policies. While academic evaluations of territorial spatial efficiency have evolved from shallow to deep and from local to holistic, several deficiencies remain. First, research on territorial spatial efficiency often focuses on single dimensions, such as urban spatial utilization efficiency, cultivated land use efficiency, or ecological efficiency, and suffers from the homogenization of evaluation indicators with land-use efficiency assessments. This paper integrates urban, agricultural, and ecological spaces and supplements the undesirable output aspects of existing indicators. Second, most existing studies evaluate driving mechanisms based on external socio-economic factors rather than identifying the obstacle factors within the spaces themselves. This leads to insufficient support for enhancing the internal drivers of territorial spatial efficiency. Taking this as a breakthrough point, this paper identifies the degree of obstruction to efficiency improvement at the macro level for each space and explores detailed obstacle factors at the micro level. Third, as the Yellow River Basin is a vital ecological barrier in China, there is a need to supplement the typical understanding of optimizing territorial spatial layouts in key basins. This paper employs multiple methods to analyze the spatio-temporal changes and obstacle factors of territorial spatial efficiency from 2000 to 2020. This aims to deepen the theoretical understanding of the spatio-temporal evolution of territorial spatial efficiency from a geographical perspective and provide case support and practical references for government departments to formulate cross-regional collaborative optimization strategies for territorial spatial patterns.

1 数据与方法

Analysis of the Essential Connotation of Territorial Space Efficiency

Territorial space supports and maintains the normal operation of the socio-economic system, which is composed of three subsystems: urban development, agricultural production, and ecological conservation. From the perspective of the functional roles of various spatial entities, urban space carries regional economic development, industrial structure upgrading, and the agglomeration of resource elements. Agricultural space serves functions such as agricultural production, rural culture, and social security, providing an important foundation for achieving rural revitalization. Ecological space is a vital link in ensuring human survival and development, performing functions such as maintaining biodiversity. National functional zone planning explicitly divides territorial space into urban, agricultural, and ecological spaces. Accordingly, this paper categorizes territorial space efficiency into urban spatial efficiency, agricultural spatial efficiency, and ecological spatial efficiency.

The measurement of territorial space efficiency is essentially a trade-off between territorial resource inputs, desired outputs, and undesired environmental outputs. The magnitude of this efficiency determines the optimization process of regional territorial spatial layouts and the formulation of regional territorial spatial planning and management policies. Its connotation emphasizes the synergistic, high-quality development between the socio-economic system and the resources and environment represented by territorial space utilization. It emphasizes achieving optimal regional territorial spatial benefits and layouts with minimum territorial resource inputs, while simultaneously producing the least negative impact on the ecological environment.

Overview of the Study Area

As an important ecological barrier and economic zone in China, the Yellow River Basin spans the eastern, central, and western regions of the country, including Henan and Shandong provinces. The types of land use within the region are complex and diverse.

Analysis of Spatiotemporal Changes and Obstacle Factors of Territorial Space Efficiency in the Yellow River Basin

The region includes construction land and other types, characterized by significant topographical fluctuations. The total population within the region is approximately...

8 人

The level of economic development exhibits a gradient of differential growth. The characteristics of economic disparity in the upper reaches are a realistic representation and objective manifestation of the unbalanced regional development in Eastern China. The base map was produced based on the standard map service website of the Ministry of Natural Resources (Review Number: GS(2019)1822), with no modifications made to the boundaries.

The construction of the evaluation index system for territorial spatial efficiency should fully reflect the contemporary characteristics of regional spatial development while ensuring data stability, availability, and universality. Building upon the aforementioned definition of territorial spatial efficiency and drawing on existing research, we constructed an evaluation index system encompassing urban spatial efficiency, agricultural spatial efficiency, and ecological spatial efficiency. The calculation process for integrated spatial efficiency follows the method of Li Qiang et al., where all input factors from the three subspaces are treated as input indicators, desirable output indicators as desirable output factors, and undesirable output indicators as undesirable output factors. This approach aims to measure the overall utilization of territorial space in the Yellow River Basin. To mitigate potential errors caused by data fluctuations in a single year, the average weight during the research period is taken as the final weight.

The model accounts for the influence of undesirable output factors by incorporating variables such as urban construction land area, non-agricultural employment, fixed capital stock, average wages of urban employees, and industrial wastewater discharge. For the agricultural dimension, indicators include total sown area of crops, agricultural practitioners, total power of agricultural machinery, chemical fertilizer usage, rural electricity consumption, pesticide usage, plastic film usage, effective irrigation area, and year-end livestock population, with agricultural value-added as the desirable output and agricultural carbon emissions as the undesirable output. Regarding ecological space, the system includes ecological land area, employment in environmental and public facility management, fixed asset investment in environmental and public facility management, and total energy consumption. Outputs are measured by green coverage, ecosystem service value, and the eco-environmental quality index. Furthermore, the system accounts for levels of mechanization, chemicalization, electrification, pharmaceuticalization, plasticization, and irrigation.

The radial distance function incorporates slack variables into the objective function, thereby mitigating bias caused by differences in angular selection. Three-dimensional kernel density estimation (3D-KDE) is a non-parametric estimation method used in probability theory to estimate unknown density functions. Its core principle involves performing a weighted summation of kernel functions within the neighborhood of each data point in a three-dimensional space. This method can, to a certain extent, avoid estimation errors caused by the specific functional settings of parametric models. A higher kernel density value indicates a higher concentration of data distribution. Its calculation formula is as follows:

$$ f(x) = \frac{1}{nh} \sum_{i=1}^{n} K\left(\frac{x-x_i}{h}\right) $$

...is the kernel density estimate, where $n$ represents the number of research units. The parameter $h$ is used to control the smoothness of the estimated density, while $K$ denotes the kernel density function for spatial efficiency. The term $x_i$ refers to the attribute value of the sample points.

Natural Breaks (Jenks)

The Natural Breaks (Jenks) method is the default data classification approach in ArcGIS. This method intuitively identifies "breaks" in the data through a histogram, allowing for the natural grouping of similar values. The ultimate goal of this classification is to maximize the variance between different groups while minimizing the variance within each group.

Hot Spot and Cold Spot Analysis

Hot spot analysis is a method used to investigate the spatial distribution of clusters with similar attributes within a study area. By identifying the spatial distribution patterns of hot spots and cold spots in territorial spatial efficiency, this method quantifies whether the spatial patterns are clustered, dispersed, or random.

Obstacle Degree Model

The obstacle degree model is frequently employed for pathological diagnosis regarding the level of intensive and economical utilization of territorial space. By identifying the factors that influence intensive and economical land use, this model effectively recognizes the key constraints hindering the improvement of territorial space efficiency. However, traditional obstacle degree models often fail to distinguish effectively between obstacle factors and non-obstacle factors. To address this limitation, an improved obstacle degree model based on the deviation of indicators from their optimal fitness values is introduced. This approach aims to refine and improve the traditional indicator deviation obstacle model. The calculation formulas are as follows:

$$ U_j = R_j \times W_j \tag{3} $$

$$ V_j = O_j - X_j \tag{4} $$

$$ M_j = \frac{V_j \times U_j}{\sum_{j=1}^{n} V_j \times U_j} \tag{5} $$

$$ B_j = \sum M_j \tag{6} $$

where $w_i$ is the factor contribution (the weight of the $i$-th indicator), $w_j$ is the weight of the secondary indicator to which the $i$-th indicator belongs, $R_i$ is the optimal target value, $x_i$ is the standardized value of the indicator, and $O_i$ is the obstacle degree of the secondary indicator.

Data Sources and Processing

Socioeconomic data were primarily sourced from the China City Statistical Yearbook and the China Statistical Yearbook. Ecological land area was specifically categorized into two primary land types: wetlands and other unused land. These data were indirectly obtained based on the national-scale land-use database of China developed by Ji Yuan et al.

The ecosystem service value (ESV) indicators were calculated using the equivalent factor method, based on the revised "Equivalent Table of Ecosystem Service Value per Unit Area of Ecosystems in China" by Xie Gaodi et al. The Eco-Environmental Quality Index (EQI) was directly obtained by referencing existing China urban eco-environmental quality evaluation datasets. Vector data were sourced from the Standard Map Service System.

2 结果与分析

General Evolution Patterns of Territorial Spatial Efficiency based on the Coefficient of Variation

By analyzing the mean values and coefficients of variation for urban, agricultural, and ecological spatial efficiency of cities in the Yellow River Basin from 2005 to 2021, it is observed that the territorial spatial efficiency of the Yellow River Basin fluctuated upward. The implementation of the Yellow River National Strategy has provided critical support for cross-regional factor mobility and spatial governance. Urban spatial efficiency rose from 0.452 to 0.518, reflecting internal differences in the Yellow River Basin.

Spatiotemporal Evolution and Obstacle Factor Analysis of Territorial Spatial Efficiency in the Yellow River Basin

The data for 2022 reflects a positive development trend in the process of new urbanization, where urban space has transitioned from over-exploitation to intensive and efficient utilization. Agricultural spatial efficiency increased continuously from 0.384 to 0.562, demonstrating the significant benefits brought by the upgrading of the agricultural industrial structure and large-scale development in the region. Ecological spatial efficiency rose from 0.125 to 0.186, though its absolute value remains relatively low, indicating that there is still substantial potential for optimizing the layout of ecological space. Regarding the trend of the coefficient of variation, the regional imbalance in ecological spatial efficiency is quite pronounced, primarily due to the vast span of the Yellow River Basin and the significant differences in habitat quality across different regions. The coefficient of variation for agricultural spatial efficiency fluctuated upward from 0.325 to 0.412, while the coefficient for urban spatial efficiency decreased from 0.486 to 0.354. This reflects that while focusing on improving agricultural spatial efficiency, attention must also be paid to regional imbalances in agricultural development. The internal differences in territorial spatial efficiency have gradually narrowed, with the coefficient of variation stabilizing at 0.25, laying a foundation for optimizing territorial spatial layouts and promoting high-quality regional development in the Yellow River Basin.

To further investigate the temporal evolution trajectory of territorial spatial efficiency based on Kernel Density Estimation, multi-period kernel density plots were generated using Matlab software. This allowed for an analysis of the multi-dimensional evolution of territorial spatial efficiency from 2005 to 2021, focusing on peak shapes, quantities, and distribution extensibility. Regarding peak shapes and quantities, the distribution curve for urban spatial efficiency exhibits a "bimodal" pattern, while the curves for ecological and comprehensive spatial efficiency are "unimodal." This indicates a significant polarization phenomenon in the Yellow River Basin, suggesting that the number of "high-efficiency clubs" and their internal members is limited, with low-efficiency units showing a concentrated distribution pattern. In terms of distribution position, the primary and secondary peaks of urban spatial efficiency shifted, and the density curve evolved from a "short-fat" type to a "tall-thin" type, indicating a gradual improvement in urban spatial efficiency. The center of the efficiency curve remained relatively stable. The center of comprehensive spatial efficiency first shifted right and then left, indicating that the overall efficiency value fluctuated upward. Regarding distribution extensibility, with the exception of the urban spatial efficiency curve, all other curves showed a significant right-tail phenomenon. This suggests an increased probability of extreme values in regional spatial efficiency, indicating that internal development imbalances persist.

Spatiotemporal Differentiation Patterns of Territorial Spatial Efficiency Based on Classification

The Natural Breaks classification method was employed to categorize territorial spatial efficiency into four levels: high efficiency, relatively high efficiency, average efficiency, and low efficiency.

Visual analysis of the spatial differentiation patterns of territorial spatial efficiency in the Yellow River Basin from 2005 to 2021 reveals distinct characteristics. High-value clusters coexist with continuous low-value areas. The high and relatively high-efficiency zones for urban space have increased significantly, gradually covering the upper and middle reaches, which reflects the objective reality of steady improvements in urbanization quality. Low-efficiency zones are primarily concentrated in the border areas of Inner Mongolia, limited by factors such as the vast territory and sparse population density. The dominance of low values in agricultural space was broken in 2013, after which high and relatively high-efficiency zones began to form clusters in Henan and Shandong. This likely benefits from the region's strong agricultural foundation and the orderly restructuring of regional industries. High and relatively high-efficiency zones for ecological space have gradually shifted eastward, and their clustering trend has become more dispersed, indicating that the carrying capacity of ecological space faces significant pressure during regional development. High-value zones for comprehensive territorial spatial efficiency are scattered across provincial capitals and core cities, with the southern belt showing an overall upward trend. However, there remains significant potential for improvement, and the spatial spillover effects of leading cities and core growth poles need further activation.

Spatiotemporal Clustering Characteristics of Territorial Spatial Efficiency Based on Cold and Hot Spot Analysis

Given that cold and hot spot analysis can directly identify high-value or low-value clustering characteristics through local spatial autocorrelation, this study conducted a clustering analysis of various spatial efficiencies in the Yellow River Basin from 2005 to 2021. The results were categorized into hot spots, sub-hot spots, sub-cold spots, and cold spots. From the perspective of spatiotemporal clustering, the distribution of cold and hot spots for territorial spatial efficiency in the Yellow River Basin exhibits spatiotemporal inertia and continuity. High-value and low-value clustering features are significant, with localized imbalances. Hot spots for urban spatial efficiency evolved from a scattered distribution to a continuous, concentrated distribution, eventually covering the region in clusters.

Spatiotemporal Evolution and Obstacle Factor Analysis of Territorial Spatial Efficiency in the Yellow River Basin

The number of cold spots has gradually decreased, and their clustering range has shrunk to northern Inner Mongolia, fully demonstrating the positive effects of new urbanization in promoting intensive and economical land use. Hot spots for agricultural spatial efficiency are distributed in clusters within Sichuan and Henan, reflecting the high agricultural economic output of these major grain-producing provinces. Cold spots are concentrated along the "spine" of the Yellow River Basin; these peripheral areas have not yet formed effective agricultural development synergies, resulting in lagging agricultural production. The number of hot spots for ecological spatial efficiency first increased and then decreased, and the clustering of cold spots gradually dispersed over time, indicating significant spatial imbalance. This aligns with the earlier conclusion regarding large regional differences in ecological spatial efficiency. High-value zones for comprehensive spatial efficiency migrated from west to east, while low-value zones migrated from east to west. This is primarily caused by the unbalanced distribution of different spatial efficiencies and highlights the difficulty and urgency of optimizing the territorial spatial layout of the Yellow River Basin.

Obstacle Factor Analysis

Combining the spatiotemporal evolution process of territorial spatial efficiency, an obstacle degree model was used to identify the obstacle and non-obstacle factors for efficiency improvement. The obstacle degrees of various original indicators for urban, agricultural, and ecological spatial efficiency were calculated. The analysis delved into how urban and ecological spatial efficiencies hinder the improvement of overall territorial spatial efficiency. At the urban spatial level, urban construction land area, fixed capital stock, and non-agricultural output value are the primary obstacle factors. The obstacle degree of non-agricultural output value fluctuated upward, with an average annual obstacle degree of 28.6%, making it the primary obstacle factor. The obstacle degrees of the non-agricultural population and urban construction land area fluctuated inversely, alternating between the second and third obstacle factors. This reflects that the roles of land and labor factors in promoting urban spatial efficiency cannot be underestimated.

This also conforms to the objective laws of urban transformation and development. Fixed capital stock was the fourth obstacle factor, with an average annual obstacle degree of only 12.4%, though it showed a steady increase. This reflects that the impact of capital factor input on urban spatial efficiency has significantly increased. At the agricultural spatial level, the average annual obstacle degrees for agricultural irrigation area, rural electricity consumption, year-end livestock numbers, and plastic film usage ranked from highest to lowest. Agricultural irrigation area remained the primary obstacle factor, showing a trend of increasing and then decreasing. Looking at the reality of agricultural development in the basin, issues such as soil erosion and water scarcity in some areas severely restrict high-quality agricultural development. Limited water resources and an overloaded agro-pastoral population have led to insufficient irrigation areas, necessitating an urgent adjustment of the agricultural industrial structure to ensure sustainable development. At the ecological spatial level, ecological land area, employment in environmental and public facility management, and fixed asset investment in water conservancy and environmental management are the main obstacle factors. This indicates that sufficient land, labor, and capital are essential for promoting the intensive use of ecological space. Rising environmental standards and higher land-use costs in the Yellow River Basin have placed greater pressure on ecological spatial optimization and efficiency improvement. On this basis, an in-depth analysis of the evolution and formation mechanisms of obstacle factors at all levels was conducted to reveal common problems and general patterns. In the obstacle diagnosis system for territorial spatial efficiency in the Yellow River Basin from 2005 to 2021, ecological spatial efficiency emerged as the primary obstacle factor, while the influence of urban and agricultural spatial efficiency showed an inverse relationship.

Spatiotemporal Evolution and Obstacle Factor Analysis of Territorial Spatial Efficiency in the Yellow River Basin: Evolution and Mechanism Analysis of Obstacle Factors

Agricultural and ecological spaces function as a complex open system where different spatial types influence one another. With the expansion of urban space and the scale clustering of industrial construction, the pressure on resource and environmental carrying capacity has gradually intensified, leading to a continuous increase in the obstacle degree of ecological spatial efficiency to the overall territorial spatial efficiency. However, with the implementation of Xi Jinping's Thought on Ecological Civilization and the deployment of the strategy for Ecological Protection and High-Quality Development of the Yellow River Basin, the regional ecological environment has been effectively improved. Consequently, the obstacle degree of ecological spatial efficiency has fluctuated downward, while the obstacle degree of urban spatial efficiency has gradually increased, becoming the second major obstacle to territorial spatial efficiency improvement. During this critical transition period for optimizing the territorial spatial layout of the Yellow River Basin, it is urgent to address the driving force of urban space and the industrial cultivation of agricultural space. It is essential to effectively maintain the coordinated relationship between ecological restoration/protection and high-quality socio-economic development. By gradually constructing an interactive development framework for "Urban-Agricultural-Ecological" spaces, the goal is to achieve a positive, triple-driven improvement in urban, agricultural, and ecological spatial efficiencies.

3 讨

Regional Differences and Evolutionary Patterns of Territorial Spatial Efficiency in the Yellow River Basin

An objective understanding of the regional differences in territorial spatial efficiency within the Yellow River Basin reveals comprehensive temporal evolutionary laws. The characteristics of these evolutionary patterns across ecological and agricultural spaces align with the basin's functional positioning as a critical ecological zone and a representative ecological region in China. Due to the vast geographical span of the basin and the varying developmental foundations of its constituent cities, an objective reality has emerged where the progress of ecological spatial efficiency improvement is inconsistent and characterized by significant regional disparities.

The differentiated characteristics of territorial spatial efficiency are long-term, objective phenomena resulting from variations in resource endowments and the uneven pace of socio-economic development across different regions. Both the spatial differentiation patterns and the clustering characteristics of territorial spatial efficiency in the Yellow River Basin indicate that different spatial efficiencies possess distinct developmental configurations. Therefore, all stakeholders should fully respect regional physical geographical laws and objectively acknowledge these regional differences. It is essential to avoid the "digital trap" of blindly pursuing numerical convergence in territorial spatial efficiency, which can lead to excessive competition or aggressive internal friction ("involution"). Instead, focus should be placed on addressing the shortcomings in efficiency improvement and recognizing the necessity of formulating coordinated, zone-based developmental measures.

The results of the obstacle factor analysis indicate that numerous hurdles still impede the improvement of territorial spatial efficiency in the Yellow River Basin, with varying contribution rates among different factors. Ecological spatial efficiency has been identified as the primary (first-level) obstacle to the overall improvement of territorial spatial efficiency, with the value of ecosystem services serving as the core constraint within this dimension.

In the current era of ecological civilization construction and the implementation of ecological protection strategies, it is imperative to confront the weaknesses in the process of enhancing territorial spatial efficiency. Starting with ecological space, improvements should be realized by integrating the elemental composition and calculation processes of ecosystem service values. This approach will facilitate the optimization of urban spatial utilization efficiency, production efficiency, and ecological space protection efficiency. Ultimately, it is necessary to refine the refined management system for territorial space and the differentiated regional development framework in the Yellow River Basin, fostering a positive interaction where multi-dimensional spatial efficiencies integrate and advance collectively.

结论

From the perspective of mean efficiency, the spatial efficiency of the Yellow River Basin's national territory exhibited a fluctuating upward trend over time. Significant differences exist across different spatial regions, particularly regarding the developmental trends of ecological and agricultural spaces. Based on kernel density curves, the peak shapes and quantities of different spatial efficiencies show distinct characteristics. High-value areas of spatial efficiency in the Yellow River Basin are concentrated in core nodes or provincial capital cities, while low-value areas are widely distributed as a foundational background. The heterogeneous patterns of agricultural and ecological spatial efficiency are particularly prominent, with clustering modes exhibiting clear regional differences.

The evolution of spatial agglomeration in the Yellow River Basin’s national territory efficiency demonstrates characteristics of spatio-temporal inertia and continuity. This is primarily manifested as a significant positive agglomeration pattern, dominated by "High-High" and "Low-Low" clusters. High-value clusters coexist with continuous distributions of low-value areas. The primary obstacle to the overall spatial efficiency of the basin is ecological spatial efficiency, the degree of which increased initially before declining. Meanwhile, the obstacle degrees of urban spatial efficiency and agricultural spatial efficiency fluctuate in an inverse relationship. Specifically, the proportion of secondary and tertiary industries, effective agricultural irrigation area, and ecosystem service value are the primary obstacles to urban, agricultural, and ecological spatial efficiency, respectively.

National territory possesses both spatial and resource attributes. The key to optimizing the development pattern of national territory lies in achieving the coordinated development of urban, agricultural, and ecological spaces. Based on the laws of spatio-temporal evolution and the identification of obstacle factors, the following regional regulatory measures are proposed:

1. Synchronous Development Leading Zone for Urban-Agricultural-Ecological Space
Cities such as Jiayuguan and Shuozhou should continue to promote the coordinated utilization of various spatial resources. They should fully leverage the economic leadership and dominant roles of core growth poles, orderly enhance the economic value generated by regional agricultural and ecological products, and steadily advance the optimization of the regional national territory spatial layout.

2. Synchronous Development Lagging Zone for Urban-Agricultural-Ecological Space
For cities like Ulanqab, Dingxi, and Lanzhou, it is essential to establish a comprehensive optimization system for national territory layout. Under the premise of strengthening ecological protection, these areas should rationally tap into the development potential of urban and ecological spaces. By guiding the structure of national territory utilization toward high-quality development, these cities can strengthen factor agglomeration and inter-regional connectivity, ultimately achieving diversified urban development and a high-quality transformation of land use.

3. Asynchronous Development Zone for Urban-Agricultural-Ecological Space
These regions should fully explore the specific development potential and characteristics of each space. In areas with low urban spatial efficiency, regional agricultural or ecological advantages should be leveraged to promote the gradient evolution of ecological and agricultural features into economic benefits, thereby improving urban spatial efficiency. In areas with low agricultural spatial efficiency, high-tech agricultural technologies and planting models should be gradually introduced, alongside accepting product transfers from high-efficiency agricultural zones to realize agricultural potential. In areas with low ecological efficiency, the economic leadership of core growth poles should be utilized to orderly increase the economic value generated by regional ecological products.

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Spatio-temporal Coupling Relationship Between Territory Spatial Utilization Efficiency and High-quality Development in the Wanjiang City Belt

The optimization of territory spatial utilization efficiency is a critical component of regional sustainable development. This study investigates the spatio-temporal coupling relationship between territory spatial utilization efficiency and high-quality development within the Wanjiang City Belt. By employing a multi-dimensional evaluation index system, we analyze the evolution of these two systems and their interaction over time.

1. Introduction

The coordinated development of spatial utilization and high-quality economic growth has become a central focus of regional planning in China. As a key national strategic region, the Wanjiang City Belt serves as a vital link for industrial transfer and ecological preservation. Understanding how spatial efficiency contributes to—or constrains—high-quality development is essential for achieving long-term regional prosperity.

[FIGURE:1]

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To quantify the relationship between these systems, we utilize a coupling coordination degree model. Territory spatial utilization efficiency is assessed through indicators representing land use intensity, economic output per unit of land, and ecological impact. High-quality development is measured across five dimensions: innovation, coordination, green development, openness, and sharing.

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[TABLE:1]

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- Production Space: Concentrated in areas with high industrial density and favorable infrastructure, showing a trend of expansion in urban fringes.
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The evolution of the PLE functional space is driven by a combination of natural conditions, socio-economic factors, and policy interventions. Key influencing factors include:

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Spatial Correlation Network Structure and Driver Identification of Green and Low-Carbon Agricultural Production Efficiency in the Yellow River Basin

1. Introduction

The Yellow River Basin serves as a critical ecological barrier and a vital economic zone in China, playing a strategic role in national food security and ecological civilization construction. As the global climate crisis intensifies, transitioning toward green and low-carbon agricultural production has become an inevitable choice for achieving sustainable development. Green and low-carbon agricultural production efficiency (GLCAPE) is a comprehensive indicator that accounts for both economic output and environmental costs, specifically incorporating carbon emissions and non-point source pollution as undesirable outputs.

Recent studies have shown that agricultural production efficiency is not isolated within administrative boundaries; rather, it exhibits complex spatial correlation characteristics due to the flow of production factors, technology spillovers, and regional policy coordination. Understanding the structural characteristics of the spatial correlation network of GLCAPE in the Yellow River Basin is essential for formulating differentiated regional development strategies and promoting synergistic emission reductions.

2. Research Methodology and Data Sources

2.1 Measurement of Green and Low-Carbon Agricultural Production Efficiency

This study utilizes the Super-Efficiency SBM (Slack-Based Measure) model, which accounts for undesirable outputs, to measure the GLCAPE of provinces and cities along the Yellow River Basin. The input indicators include labor, land, machinery, fertilizer, and water resources. The desirable output is the total value of agricultural production, while the undesirable outputs include agricultural carbon emissions and agricultural non-point source pollution.

2.2 Construction of the Spatial Correlation Network

To characterize the spatial associations, an improved gravity model is employed to determine the correlation intensity between regions. The basic form of the model is expressed as:
$$ y_{ij} = k \frac{\sqrt{P_i E_i} \sqrt{P_j E_j}}{D_{ij}^2} $$
Where $y_{ij}$ represents the correlation strength between region $i$ and region $j$, $E$ denotes the GLCAPE, and $D_{ij}$ represents the geographical distance between the two regions. Based on the correlation matrix, Social Network Analysis (SNA) is applied to investigate the structural characteristics of the network.

2.3 Identification of Driving Factors

To identify the factors driving the evolution of the spatial correlation network, this study utilizes the Quadratic Assignment Procedure (QAP). Unlike traditional regression methods, QAP is based on permutation tests, which effectively addresses the issue of multicollinearity in relational data. The potential drivers considered include differences in economic development, technological innovation levels, industrial structure, and environmental regulation intensity

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The Influence of the Population System on Regional Differences in Territorial Space Pattern Evolution in Border Areas: A Case Study of the China-Vietnam Border Belt

1. Introduction

The evolution of territorial space patterns is a complex process driven by the interaction of natural environments and socio-economic activities. In border regions, these patterns are uniquely influenced by geopolitical factors, cross-border trade, and demographic shifts. Understanding the role of the population system—including its distribution, structure, and mobility—is crucial for optimizing spatial planning and ensuring regional stability. This study focuses on the China-Vietnam border belt to analyze how population dynamics contribute to the regional differences observed in territorial space evolution.

2. Materials and Methods

2.1 Study Area

The China-Vietnam border belt serves as a critical gateway for the "Belt and Road Initiative" and the China-ASEAN Free Trade Area. This region exhibits significant geographical diversity, ranging from mountainous terrains to coastal plains, which inherently shapes the distribution of human settlements and land use patterns.

2.2 Data Sources and Processing

Data for this study were integrated from multiple sources, including land use remote sensing monitoring data, national census records, and socio-economic statistical yearbooks. Territorial space was categorized into three primary types: ecological space, agricultural space, and urban-industrial space.

2.3 Research Methodology

To quantify the influence of the population system, we employed a combination of spatial autocorrelation analysis, the Land Use Transition Matrix, and Geodetector models. The population system was characterized by indicators such as population density, urbanization rate, and the proportion of the non-agricultural population.

3. Results and Analysis

3.1 Evolution of Territorial Space Patterns

Over the study period, the China-Vietnam border belt has experienced significant spatial transformations. There has been a notable expansion of urban-industrial space, primarily at the expense of agricultural land. Ecological space has remained relatively stable in high-altitude regions but faces pressure in areas adjacent to expanding urban centers.

[FIGURE:1]

3.2 Regional Differences in Spatial Evolution

The intensity of spatial evolution varies significantly across the border belt. Eastern sections, characterized by more robust trade infrastructure and higher accessibility, show rapid urban expansion. In contrast, the western mountainous sections exhibit a slower pace of change, with land use remaining largely traditional and ecological.

[TABLE:1]

3.3 Impact of the Population System

The population system acts as

border areas: Take the China - Vietnam border zone as a case[J].

High-Quality Regional Development Research Based on Geographical Units: A Comparative Analysis of Development Conditions and Priorities in the Yellow River and Yangtze River Basins

1. Introduction

The pursuit of high-quality development represents a fundamental shift in China's economic strategy, moving from a phase of rapid growth to one focused on sustainability, equity, and efficiency. Regional development, as a critical component of this transition, requires a nuanced understanding of the spatial heterogeneity inherent in different geographical units. This study explores the theoretical and empirical dimensions of high-quality regional development, with a specific focus on the contrasting development conditions and strategic priorities of the Yellow River Basin and the Yangtze River Basin.

2. Theoretical Framework for High-Quality Regional Development

High-quality regional development is not a monolithic concept; rather, it is a multi-dimensional objective that integrates economic vitality, social equity, and ecological integrity. Unlike traditional development models that prioritized GDP growth, high-quality development emphasizes the "Five Development Concepts": innovation, coordination, green development, openness, and sharing.

From a geographical perspective, regional development must be grounded in the carrying capacity of the local environment and the specific functional orientation of the geographical unit. This involves optimizing the spatial distribution of population and industry to ensure that economic activities are commensurate with ecological constraints. The core of this approach lies in identifying the unique comparative advantages of different regions and fostering a specialized, yet integrated, spatial division of labor.

3. Comparative Analysis of the Yellow River and Yangtze River Basins

The Yellow River and Yangtze River basins serve as the primary ecological and economic arteries of China. However, they exhibit significant differences in their natural endowments, developmental stages, and ecological sensitivities.

3.1 Resource Endowments and Ecological Constraints

The Yangtze River Basin is characterized by abundant water resources, high biodiversity, and a robust ecological carrying capacity. In contrast, the Yellow River Basin faces severe water scarcity, fragile ecosystems, and significant soil erosion challenges. These physical differences dictate fundamentally different development trajectories. While the Yangtze River can support high-density industrial clusters and urban agglomerations, the Yellow River Basin must prioritize water conservation and ecological restoration as prerequisites for any economic activity.

3.2 Economic Structure and Innovation Capacity

The Yangtze River Economic Belt has emerged as a global hub for manufacturing and technological innovation, anchored by the Yangtze River Delta. It boasts a high degree of openness and integration into global value chains. Conversely, the Yellow River Basin's economy is heavily reliant on energy and

graphical units: Discuss on the difference in development condi ⁃

Characteristics of Potential Conflicts in Territorial Space and Optimization Patterns in the Yellow River Delta Based on Multi-functional Suitability

Abstract

The Yellow River Delta serves as a critical ecological barrier and a vital area for economic development in China. However, the increasing competition between ecological preservation, agricultural production, and urban expansion has led to significant territorial space conflicts. This study evaluates the multi-functional suitability of the Yellow River Delta—focusing on ecological, agricultural, and construction functions—to identify potential spatial conflicts and propose an optimized spatial pattern. By analyzing the spatial distribution and intensity of these conflicts, we provide a scientific basis for territorial spatial planning and sustainable development in the region.

1. Introduction

Territorial space is the physical carrier of human survival and development, characterized by multiple functions including ecological services, agricultural production, and urban-industrial construction. As regional development intensifies, the scarcity of land resources often leads to functional overlaps and competition, resulting in territorial space conflicts. The Yellow River Delta, characterized by its fragile ecosystem and strategic importance for food security and energy production, faces particularly acute challenges. Understanding the characteristics of these potential conflicts is essential for balancing development and protection.

2. Methodology and Data Sources

2.1 Multi-functional Suitability Evaluation

The suitability of territorial space was assessed across three dimensions: ecological suitability, agricultural suitability, and construction suitability. We employed a multi-criteria evaluation (MCE) framework, integrating natural environmental factors (e.g., soil quality, water availability, biodiversity) and socio-economic factors (e.g., infrastructure proximity, population density).

2.2 Identification of Potential Conflicts

Potential conflicts were identified by overlaying the suitability maps of different functions. Conflicts arise when a single land unit exhibits high suitability for two or more competing functions. We categorized these conflicts into several types, such as "Ecological-Agricultural Conflict" and "Agricultural-Construction Conflict," and quantified their intensity using a spatial conflict index.

[TABLE:1]

3. Results and Analysis

3.1 Spatial Distribution of Suitability

The evaluation results indicate that high-suitability areas for ecological functions are primarily concentrated in the coastal wetlands and nature reserves. Agricultural suitability is highest in the inland alluvial plains where soil salinity is lower. Construction suitability is centered around existing urban cores and industrial zones, following a corridor-like expansion pattern.

3.2 Characteristics of Potential Spatial Conflicts

The analysis reveals that potential conflicts in the Yellow River

[J]. Scientia Geographica Sinica, 2023 , 43 ( 2 ): 301 - 312 . ]

Change Characteristics and Formation Mechanism of the Territorial Spatial Pattern in the Yellow River Basin

The optimization of territorial spatial patterns is a critical component of regional sustainable development. Understanding the evolutionary characteristics and underlying drivers of these patterns is essential for ecological protection and high-quality development in the Yellow River Basin. This study examines the spatio-temporal dynamics of territorial space and explores the mechanisms that shape its configuration.

1. Introduction

The territorial spatial pattern reflects the complex interaction between human activities and the natural environment. In the context of China's national strategy for the Yellow River Basin, analyzing the transition between ecological, agricultural, and urban spaces is vital. Previous research, such as the work by Song Yongyong et al. \cite{Song2021}, has highlighted that the Yellow River Basin faces significant challenges, including fragile ecosystems and intense competition for land resources. Furthermore, Dong Yin et al. \cite{Dong2020} emphasize that the optimization of territorial space layout is fundamental to achieving balanced regional development.

2. Characteristics of Territorial Spatial Change

The evolution of the territorial spatial pattern in the Yellow River Basin is characterized by distinct regional variations and functional shifts. Over the past several decades, the basin has experienced significant land-use transitions driven by urbanization, industrialization, and ecological restoration projects.

[FIGURE:1]

The spatial distribution of these changes indicates a general trend of expanding urban construction land at the expense of agricultural areas, particularly in the middle and lower reaches. Conversely, the upper reaches have seen an increase in ecological space due to targeted conservation efforts. These shifts are not uniform; they are influenced by local topographical constraints and socio-economic demands.

3. Formation Mechanisms

The formation and transformation of the territorial spatial pattern are driven by a combination of natural foundations, socio-economic drivers, and policy interventions.

3.1 Natural Environmental Constraints

The physical geography of the Yellow River Basin, including its climate, hydrology, and terrain, sets the baseline for spatial distribution. Areas with high ecological sensitivity are naturally restricted from intensive development, while the alluvial plains provide the foundation for agricultural and urban expansion.

3.2 Socio-economic Drivers

Population growth and industrial transition are the primary engines of spatial change. The concentration of economic activities in major urban clusters, such as the Guanzhong Plain and the Central Plains, has led to a "polarization-diffusion" effect, where resources and land use gravitate toward core cities.

3

Sinica, 2024 , 79 ( 3 ): 672 - 687 . ]

Zhu Aiai, Yin Songkui, Liu Qionghui. Spatial and temporal differentiation and influencing factors of agricultural ecological efficiency in northwest China [J]. Arid Land Geography. Shi Caixia, He Xiaorong. Measurement and improvement path of urban green development efficiency in the Yellow River Basin under the carbon peaking and carbon neutrality targets [J]. Arid Land Geography. Li Yunyan, Zhang Shuo. Spatial-temporal characteristics, dynamic evolution of distribution and spatial differences of regional eco-efficiency in China [J]. Statistics & Decision. Liu Linke, Liang Liutao, Gao Pan, et al. Coupling relationship and interactive response between ecological protection and high-quality development in the Yellow River Basin [J]. Journal of Natural Resources. Land ecological quality and its change trend prediction in the Yellow River Basin. Arid Land Geography.

Liu Jiaqi, Zhou Luhong, Xi Xiaoya. Land ecological quality and its change trend prediction in the Yellow River Basin from 2000 to 2020 [J]. Arid Land Geography. He Yun, Wang Shaiyao, Xie Chi. Level measurement, spatio-temporal variation and obstacle factors of common prosperity in China at the provincial level [J]. Economic Geography. Meng Guangwen, Zhang Ningyue, Qi Honggang, et al. Transformation development and obstacle degree of Tianjin Economic-Technological Development Area [J].

opment area[J]. Acta Geographica Sinica, 2024 , 79 ( 8 ): 2042 -

Evaluation of Ecological Land Changes and Protection Effectiveness in China's Important Ecological Spaces

YUAN Youran, WEI Jianfei, LIU Xiaoman, WANG Chao, et al.

Abstract

Important ecological spaces serve as the fundamental spatial carriers for maintaining national ecological security and providing essential ecosystem services. Evaluating the changes in ecological land within these spaces and assessing the effectiveness of protection measures is crucial for optimizing spatial planning and enhancing ecological conservation strategies. This study utilizes multi-temporal land use data to analyze the spatio-temporal dynamics of ecological land within China's designated important ecological spaces. By employing a comprehensive evaluation framework, we quantify the effectiveness of protection efforts across different regions and types of ecological spaces. Our findings indicate that while the overall area of ecological land has remained relatively stable, significant regional variations exist, with some areas experiencing degradation due to human activities. The results provide a scientific basis for the refined management of ecological redlines and the sustainable development of regional ecosystems.

1. Introduction

Ecological space refers to geographical areas with natural attributes that primarily provide ecological services or maintain ecological security. These spaces, including forests, grasslands, wetlands, and water bodies, are vital for biodiversity conservation, carbon sequestration, and climate regulation. In recent years, China has prioritized the construction of an "Ecological Civilization," leading to the implementation of the Ecological Conservation Redline (ECR) policy to protect critical ecological functions and sensitive environments.

Despite these efforts, the rapid pace of urbanization and industrialization continues to exert pressure on ecological lands. Understanding the conversion patterns between ecological and non-ecological land (such as construction land and cropland) is essential for assessing whether current protection policies are achieving their intended goals. This paper aims to evaluate the changes in ecological land within China's important ecological spaces over the past decade and assess the effectiveness of protection measures using a multi-indicator approach.

2. Data and Methods

2.1 Data Sources

The primary datasets used in this study include:
1. Land Use/Land Cover (LULC) Data: High-resolution satellite-derived land use products for multiple periods (e.g., 2010, 2015, and 2020).
2. Ecological Space Boundaries: Spatial data defining national key ecological function zones, nature reserves, and ecological conservation redlines.
3. Socio-economic Data: Population density and GDP data used to analyze

in China [J]. Acta Geographica Sinica, 2021 , 76 ( 7 ): 1708 - 1721 . ]

Spatio-temporal Patterns and New Characteristics of Land Use Change in China

Abstract

Based on the continuous updating of the National Land Use/Cover Database of China (NLUD-C), this study analyzes the spatio-temporal patterns, evolutionary characteristics, and driving mechanisms of land use change across China from 2010 to 2015. The results indicate that the total area of cropland in China continued to decrease during this period, while the expansion of construction land slowed down compared to the previous decade. Significant regional differences persist: the "North-to-South" shift of cropland centers has stabilized, but the loss of high-quality farmland in coastal regions remains a critical concern. Forest and grassland areas showed a trend of recovery in specific ecological engineering zones, reflecting the initial success of national ecological restoration policies. This paper further explores the impact of socio-economic development and climate change on land use transitions, providing a scientific basis for optimizing territorial spatial planning and ensuring food security.

1. Introduction

Land use and land cover change (LUCC) is a core component of global environmental change research. As the world's most populous developing country, China has experienced unprecedented land use transitions driven by rapid urbanization and industrialization. Monitoring these changes is essential for understanding the interaction between human activities and the natural environment. Since the late 1980s, the Chinese Academy of Sciences has maintained a high-resolution national database to track these dynamics. This study focuses on the period between 2010 and 2015, a pivotal era characterized by the transition toward "ecological civilization" and high-quality development.

2. Data and Methodology

The primary data source for this study is the National Land Use/Cover Database of China (NLUD-C), generated through the visual interpretation of Landsat TM/ETM+ and HJ-1A/1B satellite imagery. The classification system includes six primary classes: cropland, forest, grassland, water bodies, construction land, and unused land.

[FIGURE:1]

The spatial resolution of the data is 30 meters, with an integrated mapping scale of 1:100,000. To ensure accuracy, extensive field surveys and cross-validation were conducted, achieving an overall accuracy rate exceeding 90% for primary classes. We utilized a transition matrix to quantify the gains and losses between different land categories:

$$ \Delta L_{i} = \sum_{j=1}^{n} (L_{ij} - L_{ji}) $$

Acta Geographica Sinica, 2018 , 73 ( 5 ): 789 - 802 . ]

Improvement of the Evaluation Method for Ecosystem Service Value Based on Per Unit Area Value Equivalent Factors

1. Introduction

Ecosystem services represent the natural environmental conditions and utilities that ecosystems and their ecological processes form and maintain to support human survival. These services not only provide the essential material foundations for human life—such as food, medicine, and raw materials—but also maintain the life-support systems of the Earth. The scientific evaluation of ecosystem service value (ESV) is a critical foundation for ecological compensation, environmental economic accounting, and sustainable development decision-making.

Since the seminal work of Costanza et al. \cite{1}, the valuation of ecosystem services has become a central focus of international ecological and economic research. In China, Xie Gaodi et al. \cite{2, 3} developed a "Table of Ecosystem Service Value Equivalent Factors per Unit Area" based on the specific characteristics of Chinese ecosystems. This method has been widely adopted due to its relatively low data requirements and high applicability across different spatial scales. However, as research has progressed, the need for more refined and dynamic valuation methods has become increasingly apparent.

2. Methodology and Improvements

The core of the equivalent factor method lies in determining the value of a single standard equivalent factor and adjusting the equivalent coefficients based on regional ecological characteristics.

2.1 Determination of the Standard Equivalent Factor Value

The value of one standard equivalent factor is defined as the economic value of the natural food production of 1 hectare of farmland. In previous studies, this was often calculated as 1/7 of the market value of grain yield. To improve the stability and representativeness of this value, we propose a multi-year average approach:

$$ D = \frac{1}{7} \sum_{i=1}^{n} \frac{P_i \times Q_i}{A} $$

Where $D$ represents the value of the standard equivalent factor (yuan/hm$^2$), $P_i$ is the average price of grain $i$, $Q_i$ is the total yield, and $A$ is the total area. By incorporating temporal dynamics, we can better reflect the actual fluctuations in natural resource value.

2.2 Refinement of Ecosystem Classification

To enhance the precision of the valuation, we have further subdivided the primary ecosystem categories. For instance, "Forest" is subdivided into evergreen broad-leaved forest, deciduous broad-leaved forest, and coniferous forest. "Grass

Improvement of the evaluation method for ecosystem service value

based on per unit area[J]. Journal of Natural Resources, 2015 , 30

Xu D, Yang F, Yu L, et al. Quantization of the coupling mecha

nism between eco - environmental quality and urbanization from

multisource remote sensing data[J]. Journal of Cleaner Production, , doi:

DONG Peipei LIU Jiurong Spatio-temporal variation and obstacle factors of territorial spatial efficiency in the Yellow River Basin LI Qiang . School of Tourism, Henan Normal University, Xinxiang , Henan, China; . School of Urban Economics and Public

Administration, Capital University of Economics and Business, Beijing 100070 , China)

gionally optimized land use patterns that promote sustainable development. This study investigated the Yellow River Basin s territorial spatial efficiency by examining cities over years ( ). We employed a methodological framework combining spatial classification techniques, kernel density estimation, and obstacle de gree modeling to systematically assess spatiotemporal patterns and limiting factors. The temporal analysis re vealed fluctuating efficiency trends throughout the study period, with a consistent hierarchy of performance across spatial categories (ecological space>urban space>agricultural space). Spatially, significant heterogeneity was observed in efficiency distribution, with distinct regional agglomeration patterns. These spatial configura tions demonstrated strong temporal inertia and continuity, characterized primarily by high-high low-low agglomeration patterns. Our obstacle factor analysis identified ecological spatial efficiency as the primary con straint as the primary constraint to overall territorial spatial improvement in the basin. Further investigation re vealed specific limiting factors for each spatial category: Non-agricultural output value (urban spaces), agricultur al irrigation area (agricultural spaces), and ecosystem service value (ecological spaces). These findings highlight the need for targeted interventions addressing these specific limitations. The research contributes to the theoretical understanding of territorial spatial efficiency dynamics in major river basins while providing scientific support for optimizing the territorial spatial layout and improving the level of spatial governance in the Yellow River Ba