Land-Use Conflict Dynamics, Patterns, and Drivers under Rapid Urbanization

Abstract

Conflict over land use is an issue that all countries are experiencing in the accelerated process of urbanization and industrialization. Research on the identification and characterization of land-use conflicts is an important basis for promoting the sustainable development of regional land use. Taking Hebei Province under the background of Beijing–Tianjin–Hebei integration as the research object, this article combines the SCCI model and the LUF model to study the land-use flush in the process of rapid urbanization from the dimensions of land-use landscape conflict and land-use function conflict. The results of this study point out that land-use conflicts in the region have gone through a developmental course of intensification of heavy conflicts, slowing down, and then smoothing out. The exacerbation of land-use conflicts is synchronized with the time pattern of construction and development in the accelerated industrialization and urbanization of Hebei, while the activities of arable land occupation and compensation balance and land ecological management produce lagging land-use conflicts. The spatial pattern is characterized by dispersed and random conflicts in the plains, concentrated conflicts in the mountain stream zones, and stable conflicts in the ecological zones within the mountains in the mountainous areas. The role of externalities and internalities from within the region and in the coordinated development of the region has led to the coexistence of developmental and governance land-use conflicts in Hebei Province, and the geographic environment has a constraining effect on the spatial differentiation of these conflicts. Along with the strong implementation of China’s eco-governance and use-control systems, developmental land-use conflicts from the region will be effectively curbed, but the risk of overlapping developmental conflicts and lagging governance conflicts from coordinated regional development is a key focus for conflict prevention in the future.

1. Introduction

All regions globally face the challenge of intersecting and overlapping land uses, known as land-use conflicts, amidst intense urbanization processes [1,2].

China’s urbanization and industrialization have accelerated since the twenty-first century [3,4]. The urbanization rate has surged from 36% in 2000 to 63% in 2020 nationwide and notably from 26.09% to 60.07% in Hebei Province. According to the Northan curve, Hebei has experienced rapid high-speed growth since 2005, driving substantial land demand across various industries [5,6]. Particularly, the rapid expansion for town, industrial, and cultural tourism development has exacerbated conflicts among different land-use stakeholders [7,8,9]. This expansion has encroached on agricultural and ecological lands [10] and intensified ecological and environmental challenges [1,2,3,4,5,6,7,8,9,10,11,12,13,14]. The disorderly spatial layout of towns and cities and chaotic national land development have triggered imbalances in various spatial functions. These changes have diversified and complicated land-use patterns and structures, significantly constraining land function optimization and effective resource allocation [15], thereby increasing risks to the sustainable socio-ecological and economic development of regions [16]. These issues fundamentally represent regional land-use conflicts and their chain reactions.

In general sociological research, “conflict” refers to the incompatibility or antagonism among different actors regarding their goals, leading to psychological and behavioral contradictions [17]. As academics increasingly focus on land resources and ecological environments, this theory has been gradually integrated into ecological conservation and land resource utilization studies [18,19], introducing the concept of land conflict, often described as “land use conflict” [20,21,22,23]. This study adopts the following definition of land-use conflict in economic geography: the phenomenon of spatial competition and conflict of interest between people and land caused by the land-use patterns and structures of stakeholders in the land-use process [24]. It is widely recognized in academia that land-use conflict arises from the mismatch between the limited nature of land resources and the purpose of the land-use subject. It is essentially a conflict of interest between people and land, people and people. The identification and mediation of land-use conflict is of great significance to maintain the sustainable development of land use. Currently, the most essential research on land-use conflicts in academia focuses on the identification of conflicts: scholars such as Greg Brown used participatory mapping to identify land-use conflicts [25]; Iwona Cieślak used multi-criteria decision making to identify land-use conflicts [26]; Yuan Gao and other scholars based their research on the functional context of production-ecology-life and used a multi-indicator model to identify land-use conflicts in mining cities [27]. In addition, some scholars have also conducted systematic research and discussion on the analysis of influencing factors and evaluation system construction of land-use conflicts [28,29], conflict evolution processes, and conflict governance [30,31,32]. The mainstream approach to the identification of land-use conflicts in current academia is multifactor superposition analysis. Usually, the grid or village or township-level administrative area is used as the unit, and the scores of each factor are weighted to identify the land-use situation, and then the type and intensity of conflicts in each land unit are identified by constructing a discriminant matrix. In previous studies, the evaluation system is also usually constructed with the combination of contributions from different land functions, differentiated spatial combinations of land landscapes, and the interest orientation of land-use subjects as elements. As a result, different themes have been formed around land-use conflicts, such as conflicts of land-use functions, conflicts of land-use landscapes, and conflicts of land-use rights. The research on land function conflicts focuses more on the multifunctionality of land; the research on land-use landscape conflicts focuses more on the natural attributes of land; and the research related to land tenure conflicts focuses on the social attributes of land. With the development of the concept of sustainable development, combining the multifunctionality and natural attributes of land from a quantitative perspective has gradually become an important issue.

Land-use functional conflicts primarily stem from land-use disorder due to the multifunctional nature of land [33], attributed mainly to external and internal factors [34]. Landscape conflicts reflect adverse impacts of human activities and natural disasters on landscape patterns and functions, while functional conflicts denote the incompatibility of multiple land-use patterns overlapping in space and time.

Hebei Province is geographically a peripheral region within the capital economic circle, experiencing relatively slow socio-economic development. Over the past 30 years, it has transitioned rapidly from traditional industrial dominance to de-industrialization [35], encountering significant land-use challenges during synergistic development [36,37,38]. Therefore, Hebei Province serves as a valuable sample for studying spatial land-use conflicts and dilemmas in developing capital peripheral areas.

This study aims to quantify the conflicting land use in the process of land-use conflict. Therefore, technically, it mainly initiates the exploration of conflicting land use in Hebei Province through the landscape conflict perspective and the functional conflict perspective. This study investigates the following dimensions of landscape and functional conflicts: (1) intensity, spatial, and temporal characteristics of landscape and functional conflicts in Hebei Province; (2) exploration of spatial coupling between landscape and functional conflicts; (3) driving factors of conflicting land use in Hebei Province under capital economic circle synergistic development and governance suggestions.

2. Study Area, Materials and Methods

2.1. Overview of the Study Area

Hebei Province is located in North China, at longitude 113°5′~119°50′ E and latitude 36°5′~42°39′ N, with a provincial area of about 188,800 square kilometers. Hebei Province is connected to the Inner Mongolian grassland in the north, the hinterland of the Central Plains in the south, and the western corridor of Liaozhou in the east, and it is a necessary corridor for Beijing and Tianjin to connect with other regions. Hebei Province has 11 prefecture-level cities under its jurisdiction, with 49 municipal districts, 21 county-level cities, 91 counties, and 6 autonomous counties. With a resident population of 74.2 million in 2022 and a GDP of CNY 423.7 billion, Hebei Province is located in the 12th place in the national rankings, but its per capita GDP level is low and in the 6th place in the national rankings at the bottom of the list. Along the Taihang Mountains in the west and Yanshan Mountains in the north, the city boasts numerous rivers, including major tributaries of the Haihe River Basin, such as the Luan River, the Hutuo River, and the Zhang River, making it an important ecological barrier for the Beijing–Tianjin region. Cities and towns are mainly concentrated in the plains and river valleys, with Shijiazhuang, the provincial capital, as the center, spreading out to the plains and mountainous areas to the east, west, and south to form dense clusters of towns and cities (Figure 1).

Hebei Province has an enclave located between Beijing and Tianjin, consisting of Dafang County, Xianghe County, and Sanhe County. Since part of the data does not cover this enclave, and its small area has less impact on the overall results, this enclave is excluded from this study to ensure the completeness and rigor of the study.

2.2. Data Sources

The data used in this study and their sources are detailed in

Table 1. Data and sources.

Utilization Data	Period of Data	Source of Data
Land-use data	2005, 2010, 2015, 2018, 2020	Center for Resource and Environmental Sciences and Data, Chinese Academy of Sciences https://www.resdc.cn, accessed on 15 February 2021
Population geo-grid data	2005, 2010, 2015, 2018, 2020
GDP geo-grid data	2005, 2010, 2015, 2018, 2020
Meteorological data	Day-by-day data for 2005, 2010, 2015, 2018, 2020
Data on geohazard sites	Until 2019
DEM	2000
Road network data	2005, 2010, 2015, 2018, 2020	Extracted from Openstreetmap
Educational resources POI data	Until 2020	Guihuayun guihuayun.com, accessed on 9 April 2021
Medical resource POI data	Until 2020

, in which the land-use data were generated by visual interpretation based on Landset 8 remote sensing images from the United States.

According to the existing studies [39,40] and the needs of this study, the above land-use types are divided into production–living space, production–ecological space, ecological–production space, and ecological space, which are used to measure the landscape conflict in the study area. The specific land-use type division is shown in

Table 2. Land function classification system in Hebei.

Land Function Type	Description	Land-Use Type
Production-living space	Land used primarily to meet the needs of human life and production	Town land, rural settlement land, other construction land
Production–ecological space	Land with predominantly productive functions and ecological functions, with the provision of crop products as the main function	Paddy field and dryland
Ecological–production space	Sites with predominantly ecological functions and production functions, which may combine the provision of agricultural and forestry products	Forested land, shrubland, open forest land, other forest land
Ecological space	Land with ecological value such as climate regulation and water conservation	Low-cover grassland, medium-cover grassland, high-cover grassland, rivers, canals, lakes, mudflats, beaches, marshes, reservoir pits, and ponds

.

2.3. Research Methodology

2.3.1. Evaluation of the Technical Process

From the two dimensions of land-use landscape conflict and land-use functional conflict, the SCCI model and the LUF model, constructed with reference to LUFs, are used to quantitatively analyze landscape and functional conflicts, respectively. This study aims to summarize the characteristics of land-use conflict in the study area, explore the driving factors of conflict and the development dilemmas of land use, and propose suggestions to resolve conflicting land use under the constraints of the capital city’s synergistic development (Figure 2).

2.3.2. Landscape Conflict Measurement Model

The SCCI model is a model that combines the complexity, vulnerability, and dynamic characteristics of spatial conflicts over land. In the process of land-use conflict generation and intensification, it will inevitably lead to changes in land parcels, and the more intense the conflict, the more it will lead to the emergence of more complex, fragile, and unstable landscapes. The application of this model is relatively mature and has been practiced by many scholars [41]. This study adopts the model, aiming to analyze the distribution characteristics of land-use conflicts under each study time point in the study area. The conflict level index (SCCI) for spatial conflict is calculated with the following formula:

$$\mathrm{SCCI}=\mathrm{SPI}+\mathrm{SFI}-\mathrm{SRI}$$

where SPI refers to the complexity of the space, SFI refers to the fragility of the space, and SRI refers to the stability of the space.

• Spatial complexity index SPI

The area-weighted mean patchwork fractal index (AWMPFD) is used to express the SPI, which reacts to the difficulty of the plot to be influenced by the neighboring plots. Generally speaking, the larger the area-weighted average patchwork fractal index, the higher the complexity of the shape of the plot, and the easier it is to be affected by the neighboring plots; the formula is the following:

$$\mathrm{AWMPFD}={{\displaystyle \sum }}_{\mathrm{i}=1}^{\mathrm{m}}{{\displaystyle \sum }}_{\mathrm{j}=1}^{\mathrm{n}}[{\displaystyle \frac{2\ln \left(0.25{\mathrm{P}}_{\mathrm{ij}}\right)}{\ln \left({\mathrm{a}}_{\mathrm{ij}}\right)}}\left({\displaystyle \frac{{\mathrm{a}}_{\mathrm{ij}}}{\mathrm{A}}}\right)]$$

where ij is the jth spatial type of the ith spatial cell, Pij is its plot perimeter, aij is its plot area, A is the total area of the spatial cell, m is the total number of spatial cells, and n is the total number of spatial types.

2.

Spatial Fragility Index SFI

The spatial vulnerability index reflects the vulnerability of a parcel unit when it is subjected to certain external pressures. According to the methods used in existing studies [42,43], the vulnerability of the four triple-life spatial types is ranked from strongest to weakest, and then its rank is standardized to obtain the vulnerability of each site. According to existing studies, generally the more human intervention sites are more vulnerable, resulting in the following: production and living space (0.4), production and ecological space (0.3), ecological production space (0.2), and ecological space (0.1). The formula is as follows:

$$\mathrm{SFI}={{\displaystyle \sum }}_{\mathrm{i}=1}^{\mathrm{m}}{\mathrm{f}}_{\mathrm{i}}\times {\displaystyle \frac{{\mathrm{a}}_{\mathrm{i}}}{\mathrm{A}}}$$

where fi is the vulnerability of spatial type i, m is the total number of spatial types, ai is the area of landscape type i within the cell, and A is the area of the landscape cell.

3.

Spatial Stability Index SRI

The more fragmented the parcel map spot is in spatial form, the lower its degree of stability and the stronger the conflict effect it produces. Therefore, the spatial fragmentation index is used for expression, i.e., spatial stability index = 1 − spatial fragmentation.

$$\mathrm{SRI}=1-{\displaystyle \frac{\mathrm{PD}-{\mathrm{PD}}_{\min }}{{\mathrm{PD}}_{\max }-{\mathrm{PD}}_{\min }}}$$

Here, $\mathrm{PD}={\displaystyle \frac{{\mathrm{n}}_{\mathrm{i}}}{\mathrm{A}}}$, n_i is the number of patches of space type i in the spatial cell, and A is the area of the spatial cell.

The selection of landscape cells has a greater impact on the calculation of landscape indicators, and the final selection of 3000 m × 3000 m as the basic landscape cell grid size was made by synthesizing factors such as calculation volume, data characteristics, and actual situation. In the calculation of landscape indexes, the standardization of each spatial landscape index is carried out by the method of extreme difference, which is used to eliminate the difference in the scale between the indexes. The results of all calculations are graded using the natural breakpoint method (see

Table 3. Classification of conflicting land use.

Type of Conflict	Conflict Value Classification	Description of the Type of Conflict
Stabilizing controlled conflicts	(0,0.34)	Stage of basic control of the conflict, where the external effects of the conflict are stable and manageable
Mild conflict	[0.34,0.45)	Conflict manifestation phase, where the external effects of the conflict are largely manageable, is a critical period for prevention
Moderate conflict	[0.45,0.58)	Heating up phase of the conflict, when the external effects of the conflict begin to spiral out of control and the results of the conflict begin to be seen
Serious conflict	[0.58,1)	Stalemate phase of the conflict, where the external effects of the conflict are seriously out of control and the outcome of the conflict affects the sustainable development of the region

).

2.3.3. Local Spatial Autocorrelation

The local Moran I index responds to the degree of correlation between individual spatial units and neighboring units, and its analytical results can reflect the clustering relationship between each spatial unit and neighboring units. The model adopted in this study aims to reflect the spatial correlation between the results of land landscape conflicts and land function conflicts in the study area and further demonstrate the spatial and temporal differentiation characteristics of land-use conflicts in the study area. Its calculation formula is as follows:

$$\mathrm{Local}\mathrm{Moran}\text{’}\mathrm{s}\mathrm{I}={\displaystyle \frac{\mathrm{n}\left({\mathrm{x}}_{\mathrm{i}}-\overline{x}\right){{\displaystyle \sum }}_{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{w}}_{\mathrm{ij}}\left({\mathrm{x}}_{\mathrm{j}}-\overline{x}\right)}{{{\displaystyle \sum }}_{\mathrm{i}=1}^{\mathrm{n}}{\left({\mathrm{x}}_{\mathrm{i}}-\overline{x}\right)}^2}}$$

where n is the number of spatial units within the distance threshold. x_i and x_j are the spatial conflict level values of the units located at positions i and j, respectively, and $\overline{x}$ is the average value of x_i. W_ij is the spatial weight matrix, and the default equal-weights matrix is chosen in the same way as the global spatial autocorrelation analysis for the selection of the spatial weight matrix.

2.3.4. Functional Conflict Modeling

Land function conflicts are driven by a variety of factors such as natural, social, economic, and human. Zou Lilin and other scholars constructed a land-use conflict identification model based on identifying land production and ecological and living functions and successfully identified the intensity and potential of land-use conflicts in the southeast coastal region of China [31]. Therefore, this study draws on previous research methods to construct an identification model of land function conflicts. It aims to grasp the characteristics of land function conflicts in the study area and to reflect the potential of conflicts in the study area in this way.

• Land function evaluation model construction

Drawing on previous research methods, this study constructed a land production, ecology, and life evaluation model to identify various types of land functions in terms of natural, locational, and socio-economic factors, respectively. Based on previous research, “functional source” is introduced into the evaluation system [31]. “Functional sources” refer to large land patches with internal homogeneity, and these “functional sources” have strong convergence in one function and diffusion effect on the surrounding land. In this paper, the main streams of rivers, forests with an area of more than 10 square kilometers, and lakes and reservoirs with an area of more than 1 square kilometer are identified as ecological functional sources; towns, villages with an area of more than 0.8 square kilometers, and cultivated land with an area of more than 10 square kilometers are identified as production functional sources; and towns and villages with an area of more than 0.8 square kilometers are identified as living functional sources.

The evaluation index system and the assignment table are as follows (

Table 4. Ecological function evaluation indexes and weights.

Target Layer	Criteria Layer (Weights)	Factor Layer (Weights)	Factor Grading and Score
			100	80	60	40	20
Ecological Functions	Natural factor (0.618)	Land-use type (0.75)	Woodlands, rivers, lakes, marshes	High and medium cover grassland, mudflats	Paddy land, dry land, other forest land	Bare land, low-cover grassland	Town land, rural settlement land, other construction land
		Forest cover (0.15)	Five levels of natural breakpoints are used, with scores assigned from high to low
		Climatic suitability (0.1)
	Location factor (0.284)	Distance to town/m (0.262)	>4000	2000–4000	1000–2000	500–1000	<500
		Distance to villages/m (0.161)	>2000	1000–2000	500–1000	250–1000	<250
		Distance from road/m (0.099)	>1000	500–1000	250–500	100–250	<100
		Distance from water body/m (0.062)	<100	100–250	250–500	500–1000	>1000
		Distance from ecological sources (0.416)	<500	500–1000	1000–2000	2000–4000	>4000
	Socio-economic factors (0.097)	Index of comparative advantage in land use (1)	Five levels of natural breakpoints are used, with scores assigned from high to low

,

Table 5. Production function evaluation indexes and weights.

Target Layer	Criteria Layer (Weights)	Factor Layer (Weights)	Factor Grading and Score
			100	80	60	40	20
Production function	Natural factor (0.154)	Land-use type(0.164)	Town land, rural settlement land, other construction land	Paddy land, dry land, other forest land	Forested land, high and medium cover grasslands, rivers, lakes, reservoirs	Low-cover grasslands, mudflats, beaches, shrublands, open woodlands	Bare land, marshland
		Topographic index (0.539)	Five levels of natural breakpoints are used, with points assigned in descending order
		Distance to geologic hazard sites/m (0.297)	>2000	1500–2000	1000–1500	500–1000	<500
	Location factor (0.64)	Distance to town/m (0.309)	<500	500–1000	1000–2000	2000–4000	>4000
		Distance to villages/m (0.121)	<250	250–500	500–1000	1000–2000	>2000
		Distance from roads above county level/m (0.096)	<250	250–500	500–1000	1000–2000	>2000
		Distance from sub-county roads/m (0.044)	<100	100–250	250–500	500–1000	>1000
		Distance from the river/m (0.121)	<500	500–1000	1000–2000	2000–4000	>4000
		Distance from production sources/m (0.309)	<500	500–1000	1000–2000	2000–4000	>4000
	Socio-economic factors (0.206)	Index of comparative advantage in land use (0.167)	Five levels of natural breakpoints are used, with points assigned in ascending order
		GDP distribution (0.416)
		Population distribution (0.417)

and

Table 6. Living function evaluation indexes and weights.

Target Layer	Criteria Layer (Weights)	Factor Layer (Weights)	Factor Grading and Score
			100	80	60	40	20
Living function	Natural factor (0.164)	Land-use type (0.30)	Town	Land for rural settlements	Other building land	Paddy land, dry land, other forest land	other
		Topographic index (0.30)	Five levels of natural breakpoints are used, with points assigned in descending order
		Distance to geologic hazard sites/m (0.40)	>4000	3000–4000	2000–3000	1000–2000	<1000
	Location factor (0.297)	Distance to town/m (0.327)	<250	250–500	500–1000	1000–2000	>2000
		Distance to villages/m (0.149)	<200	200–500	500–1000	1000–1500	>1500
		Distance from roads above county level/m (0.098)	<200	200–500	500–1000	1000–2000	>2000
		Distance from sub-county roads/m (0.066)	<100	100–250	250–500	500–1000	>1000
		Distance from the river/m (0.033)	<250	250–500	500–1000	1000–2000	>2000
		Distance from living sources/m (0.327)	<250	250–500	500–1000	1000–2000	>2000
	Socio-economic factors (0.539)	Distance to educational facilities/m (0.268)	<500	500–1000	1000–2000	2000–4000	>4000
		Distance to medical facilities/m (0.268)	<400	400–800	800–1500	1500–3000	>3000
		Population distribution (0.464)	Five levels of natural breakpoints are used, with points assigned in ascending order

).

The terrain index (TI) in the evaluation system is calculated as follows [34]:

$$TI=\lg \left[\left({\displaystyle \frac{E}{\overline{E}}}+1\right)\times \left({\displaystyle \frac{S}{\overline{S}}}+1\right)\right]$$

where TI is the terrain index, E is the elevation, $\overline{E}$ is the average elevation, S is the slope, and $\overline{S}$ is the average slope.

The climate suitability in the evaluation system is calculated as follows:

$$S=S\left(T\right)\times S\left(V\right)$$

where S is climate suitability, S(T) is temperature suitability, and S(V) is moisture suitability. Data during the growing season of vegetation in the study area were used in the calculation of temperature suitability and moisture suitability, and the growing season was determined to be May–October based on the geographic location of the study area.

$$S\left(T\right)={\displaystyle \frac{\left(T_m-T_{min}\right){\left(T_{max}-T_m\right)}^B}{\left(T_{opt}-T_{min}\right){\left(T_{max}-T_{opt}\right)}^B}}$$

$$B={\displaystyle \frac{T_{max}-T_{opt}}{T_{opt}-T_{min}}}$$

Here, S(T) is the temperature suitability, T_m is the average temperature of the growing season, T_min is the minimum temperature of the growing season, T_max is the maximum temperature of the growing season, and T_opt is the optimum temperature for vegetation. The vegetation cover in the study area is almost exclusively in the temperate deciduous broadleaf forest system, and T_opt was determined to be 21.45 degrees Celsius.

$$S\left(V\right)={\displaystyle \frac{VP{D}_{max}-VPD}{VP{D}_{max}-VP{D}_{min}}}$$

$$VPD=0.6108\times \exp \left({\displaystyle \frac{17.27\times T_m}{T_m+237.3}}\right)\times \left(1-RHU/100\right)$$

Here, S(V) is the moisture suitability, VPD is the water vapor pressure deficit during the growing season, VPD_max is the upper limit of the water vapor pressure deficit during the growing season, VPD_min is the lower limit of the water vapor pressure deficit during the growing season, Tm is the average temperature during the growing season, and RHD is the relative humidity of the air during the growing season.

2.

Land function conflict identification model

After calculating the scores of each type of land function, the natural breakpoint method was used to categorize the production, living, and ecological functions into strong (S), medium (M), and weak (W) and accordingly classified them into eight types of functional conflict types and four conflict stages (

Table 7. Functional conflict identification.

Description of the Conflict	Function Combination Type			Conflict Intensity Index/Level	Stages of Conflict Development
	Production	Life	Ecological
Largely conflict-free	W	W	W	1	Conflict-free zone
Single-function dominance	S	W	W	2	Basically manageable phase of the conflict
	W	S	W
	W	W	S
	M	W	W
	W	M	W
	W	W	M
Weak conflict between two types of functions	M	M	W	3
	M	W	M
	W	M	M
Moderate conflict between two types of functions	S	M	W	4
	S	W	M
	M	S	W
	W	S	M
	M	W	S
	W	M	S
Strong conflict between two types of functions	S	S	W	5	Stage at which the conflict starts to spiral out of control
	S	W	S
	W	S	S
Three types of functions in weak conflict	M	M	M	6
	S	M	M
	M	S	M
	M	M	S
Three types of functions are in moderate conflict	S	S	M	7
	S	M	S
	S	S	M
Three types of functions in strong conflict	S	S	S	8	The conflict is completely out of control

).

3. Results and Analysis

3.1. Characteristics of Temporal and Spatial Differentiation of Landscape Conflicts

3.1.1. Spatial and Temporal Differentiation of Landscape Conflicts

The analysis of landscape conflicts (

Table 8. Number and percentage of landscape conflict grid cells in the River Region, 2005–2020.

Type of Conflict	Conflict Value Classification	Number of Grid Cells/pc				Percentage of Grid Cells/%
		2005	2010	2015	2020	2005	2010	2015	2020
Stabilizing controlled	(0,0.34)	2981	2950	2867	2789	13.77	13.63	13.24	12.88
Mild conflict	[0.34,0.45)	5478	4341	4055	3994	25.3	20.05	18.73	18.45
Moderate conflict	[0.45,0.58)	10,669	9883	9627	9270	49.28	45.65	44.47	42.82
Serious conflict	[0.58,1)	2520	4474	5099	5595	11.64	20.67	23.55	25.85
Heavy conflict rings up		——	1954	625	496	——	77.54	13.97	9.77

and Figure 3) in 2005 reveals 2520 heavy conflict units in Hebei Province, concentrated mainly in the north of the Hebei region’s cultural and tourism industry base and the east of Hebei region’s coastal industrial zone. The moderate conflict zone surrounds the severe conflict zone, forming a buffer zone between the severe and mild conflict zones.

By 2010, Hebei Province saw a significant expansion of severe conflicts, with the number of severe conflict units rising to 4474. The two major conflict zones from 2005 (Zhangjiakou and Chengde in the north, Tangshan and Qinhuangdao in the east) saw an increase of 685 serious conflict units (a 40.6% rise), while the seven central and southern municipalities experienced a 1267-unit increase (a 152.9% rise), significantly shifting conflicts southward.

The landscape conflict distribution pattern stabilized from 2010 to 2015, with a slowing growth rate of severe conflict units. However, compared to pre-2010, central and southern Hebei’s production and living space shifted westward, occupying ecological and agricultural lands to the west.

3.1.2. Landscape Conflict Development Characteristics

Overall, from 2005 to 2020, Hebei Province’s landscape conflict types changed quantitatively, with stable and controllable units generally remaining stable. The number of severe conflict units rose sharply, transforming mild and moderate conflict units into severe ones in turn, showing a significant evolutionary trend (Figure 4). Notably, as conflict units transitioned to severe, some stable, controllable, and mild conflict units directly shifted to severe conflict.

Land-use changes in Hebei Province from 2005 to 2020 show that landscape conflict development closely correlates with development and construction land expansion and the replenishment of arable land under arable land occupation and compensation balance. From 2005 to 2010, landscape conflict development accelerated due to town and village construction [16]. During this period, new severe conflict units primarily saw land-use transfers from dryland to construction land (Figure 5a), particularly in rural residential areas, with unchecked residential land expansion intensifying southern central region conflicts. From 2010 to 2015, the conversion of agricultural land to construction land significantly decreased, while ecological land continued to transition to construction land. However, agricultural land experienced increased pressure from water canals and watersheds, especially in the South-to-North Water Diversion Project engineering basin line (Figure 5b). Post-2015, due to national ecological civilization reforms, strengthened basic farmland protection systems, and adjusted urbanization patterns in Hebei Province, severe conflict growth further slowed. Nonetheless, development and construction inertia, the integration of Beijing’s non-capital functions, and lagging arable land occupation and compensation balance continue to perpetuate conflicts (Figure 5c).

3.2. Functional Conflict Measurement and Spatial and Temporal Differentiation

Spatially (Figure 6), the levels of land-use function conflicts in Hebei Province from 2005 to 2020 exhibit geographic differentiation due to variances in geomorphic units. Conflict levels are relatively low and stable in the Taihang Mountains, Yanshan Mountains, and Damshang Plateau, whereas they are higher with significant variations in the North China Plain, Coastal Plain, and Hilly Mountainous Terrain.

Specifically, level 1 and 2 conflicts are concentrated in ecological areas within the two mountain ranges, with their land function conflicts generally stable and controllable. But, level 7 and 8 conflicts are primarily along major water system streams, with level 8 conflicts concentrated in river sections passing through urban areas of cities, such as the Busyang River and the Ziya River.

During the period 2005–2020, the escalation and expansion of conflicts were concentrated in the areas where level 6–8 conflicts are located, with some areas showing a tendency to move towards the extremes of uncontrolled conflicts, with the most serious level 8 conflicts increasing by as much as 675 percent (

Table 9. Percentage of functional conflicts at all levels in Hebei region, 2005–2020.

Level of Conflict	Year
	2005	2010	2015	2020
1	0.446%	0.564%	0.395%	0.305%
2	36.462%	37.312%	35.797%	36.998%
3	18.351%	28.298%	22.672%	21.007%
4	35.657%	21.022%	26.780%	27.120%
5	4.553%	7.924%	9.542%	6.498%
6	4.225%	4.474%	4.371%	7.285%
7	0.293%	0.375%	0.417%	0.746%
8	0.004%	0.020%	0.015%	0.031%

), demonstrating the phenomenon of “conflict polarization”: lower-level conflicts remained stable, while higher-level conflicts developed and spread to even higher levels. The outskirts of industrial cities and towns, riverbanks, and the “city-mountain” zones in the region of the two major mountain ranges emerged as significant areas of “conflict polarization” (Figure 7 and Figure 8).

3.3. Spatial Coupling Characteristics of Landscape Conflict and Functional Conflict

The study area exhibits heterogeneity in spatial distribution among the four types of aggregation (

Table 10. Classification of coupled land-use conflicts.

Landscape Conflict—Functional Conflict Spatial Aggregation Types	Coupling Type Description	Characteristics of Change
High–High	Land function conflicts are higher and conflicts are spatially manifested in higher landscape conflicts	Exacerbation followed by deceleration
Low–High	Functional conflicts are high, but spatially expressed landscape conflicts are low	Mitigation followed by stabilization
High–Low	Functional conflicts are low, but spatially expressed landscape conflicts are high	Decline but unstable
Low–Low	Land function conflicts are low and conflicts are spatially manifested in low landscape conflicts	Stabilization followed by gradual increase

and Figure 9):

The high–high aggregation type is predominantly found in the southeast, encompassing towns in the North China Plain, the interior of Tangshan-Qinhuangdao’s hilly town complexes, suburban areas, and parts of Zhangjiakou City connected to mountain ranges. These areas are spatially concentrated with diverse and robust land functionalities, leading to intense competition among production, living, and ecological functions. This competition poses a high risk of conflict polarization. Spatially and temporally, the escalation of this conflict type has slowed down, though significant manifestations persist at the landscape level. This is particularly evident in cities like Tangshan, once dominated by iron, steel, and mining industries, where industrial transformation lags, necessitating urgent optimization of old industrial lands. Moreover, the hilly and mountainous areas surrounding cities remain susceptible to intensifying conflicts.

The low–high aggregation type indicates low landscape conflict but high functional conflict. It is primarily distributed along major rivers, within large cultivated and agricultural lands, and within Zhangjiakou’s main urban complex. Concurrent with the high–high aggregation type, this type also faces a heightened risk of conflict. However, due to rigorous implementation of policies safeguarding basic farmlands and ecological zones, functions of cultivated lands and river/lake wetlands have strengthened, displaying characteristics of slowed-down stabilization over time and space.

The high–low aggregation type features higher landscape conflict but lower functional conflict, predominantly located around villages in the Taihang Mountains, Yanshan Mountains, and Damshang Plateau. These areas exhibit dispersed spatial distribution and lack high-grade ecological protection zones and extensive basic farmlands around villages. Consequently, production activities in these areas, including frequent small-scale agricultural and construction developments by rural households, dominate land use with low functionality and high landscape conflicts. This type shows a trend of slowing but unstable development over time and space.

The low–low aggregation type signifies low landscape and functional conflicts, mainly distributed within sparsely human-populated interior regions of the Taihang and Yanshan Mountains. These areas remain largely unaffected by intensive human activities due to strict ecological protection measures and limited development opportunities. They maintain predominantly ecological functions with low conflict levels and risks, showcasing stable spatial distribution and minimal changes over time.

4. Discussion

The development and evolution of conflicting land use in Hebei Province are driven by both internal and external factors. Internally, the pursuit of development needs in the face of regional imbalances and the constraints of natural spatial evolution [44] create underlying mechanisms. Externally, mandatory policies and events in regional coordinated development, such as policies compelling changes in behavior among various land-use stakeholders, further influence changes in land tenure, function, and structure [45]. This interplay is closely intertwined with the internalization needs and externalization strategies of socio-economic development within the province, heavily influenced by the Beijing–Tianjin–Hebei integration strategy.

4.1. Internal Driving Forces of Land-Use Conflicts:

4.1.1. Spontaneous Diffusion of Economically Active Areas

Increased human activity typically correlates with heightened demand for land resources [46,47]. Areas with intensive human activity experience increased conflict generation and escalation. Notably, during the study period, conflicts between construction land and cropland, as well as garden land, increased significantly by 35.71% and 31.27%, respectively. These conflicts were predominantly concentrated around towns, cities, and rural areas, driven by urbanization demands and residents’ aspirations for improved living spaces [7,9], leading to the disorderly expansion of construction land [10]. The increase in comparative efficiency caused by rapid urbanization leads to the diffusion effect on adjacent difference parcels, shaking the original utilization tendency of the surrounding parcels, the random changes in the extents of the land-use pattern lead to a more fragmented land landscape, and the changes in the land-use function lead to the evolution of contradictions [48], which threatens the stability of the land-use structure and creates a predominantly exploitative intensification of conflicting land use.

4.1.2. The Traditional Industrial Pattern and the Guiding Role of Industrial Policy

The time change characteristics of the level of conflict and Hebei’s industrialization and urbanization acceleration time pattern have synchronicity, while the balance of cultivated land occupation and compensation and land ecological governance activities produce a lag in conflicting land use and form a developmental flush and governance conflict coexistence situation.

During 2005–2010, Hebei’s heavy industries underwent rapid expansion, leading to intense competition for land with varied functions among industrial sectors [5,6]. This period saw a dramatic increase in heavily conflicted units, particularly in cities like Shijiazhuang, Handan, and Tangshan, dominated by iron, steel, and coal industries. Subsequently, from 2012 onwards, Hebei initiated supply-side structural reforms to align production capacity with market demands and environmental standards. This transformation temporarily stalled development but ultimately led to a significant slowdown in the expansion of heavily conflicted plots.

Simultaneously, conflicts over arable land saw a gradual slowdown and stabilization in later periods, directly influenced by robust enforcement of policies protecting basic farmland. Central and southern Hebei, with stringent implementation of these policies, generally exhibited lower conflict levels compared to northern and eastern regions. The vigorous implementation of national policies safeguarding arable lands, alongside governmental dependence on land revenues and comprehensive land improvement initiatives, fostered a coexistence of developmental and governance conflicts. Policies such as the balance system for land occupation and compensation, as well as ecological compensation mechanisms post-development, contributed to delayed conflicts emerging during the latter study period (2015–2020). These conflicts stemmed from compensatory development or remediation efforts on arable and ecological lands, post-construction, and development.

4.1.3. Spatial Differentiation of Conflicts Due to Geospatial Constraints

Diverse geospatial conditions play a pivotal role in constraining the spatial distribution of land landscape and functional conflicts. Plains and low-elevation hilly areas, ideal for agricultural and industrial production, as well as urban construction, are particularly susceptible to exacerbated conflicts [49,50]. The southeastern plains, dotted with numerous towns and villages, witness escalating land-use demands. Geomorphological constraints do not curtail conflict development in these areas, with heavily conflicted zones proliferating. Conversely, in the western and northern mountainous regions, towns and cities are nestled in high and low mountain areas, such as Zhangjiakou and Chengde. These areas face constraints imposed by topography and geomorphology, where urban, village, and town development predominantly occurs along mountain streams with accessible transportation. These regions exhibit conflicted land uses within confined spaces, characterized by significant overlap with mountainous topography. Geospatial constraints thus foster scattered and sporadic conflict patterns in plains, concentrated conflicts near mountain foothills, and minimal conflicts within mountain ecological zones.

4.2. LUC’s Drive from Regional Synergistic Development

4.2.1. Differentiated Zoning Strategy Drive under Regional Synergistic Development

Within the Beijing–Tianjin–Hebei regional integration strategy, Hebei Province assumes critical roles in industry transfer from Beijing and Tianjin, as well as in maintaining regional ecological barriers [51]. This strategic positioning generates differentiated land resource allocations, shaping conflict fluctuations amid regional synergistic development. For instance, Xiong’an New Area, a satellite city of Beijing established in Hebei, began construction in 2017 across a 1770 sq. km area. Notably, during 2005–2015, conflicts within Xiong’an remained at lower levels (Figure 10a–c). However, during 2015–2020, conflicts escalated, particularly around urban areas, and even reached grade 7–8 in some cases (Figure 10c,d). The development and construction of new districts encroached on arable lands, while delays in demolishing and renewing extensive old towns exacerbated functional conflicting land use.

4.2.2. Driven by the Flow of Industrial and Economic Factors

As a peripheral region in Beijing’s economic sphere, Hebei Province maintains close ties with Beijing in land use, environmental protection, and industrial development [52]. Post-2014, massive industries like iron and steel, culture, tourism, and education relocated from Beijing to Hebei, fueling economic growth. Notably, during 2015–2020, heavily conflicted units in cities like Shijiazhuang and Cangzhou grew by 5.16% and 5.74%, respectively, doubling the province’s five-year average growth rate (2.76%). The environmental pollution brought about by the relocation of industrial industries at the same time spawned a large demand for construction land, which contradicted the local goal of protecting the red line of arable land and ecological land use [52], and the spillover effect of economic activities triggered a fierce competition for land resources, which significantly exacerbated the expansion of regional land-use conflicts.

4.2.3. The Role of Integration of Internal and External Development Goals in the Context of Regional Synergy

Under the goal of synergistic sustainable development, Hebei Province, on the one hand, has to implement its own development strategy and, at the same time, has to fulfill the task of industrial layout under the national strategy. In recent years, governments at all levels in Hebei Province have stepped up their calls for coordinating the structure of ecology, production, and living spaces [53]. On the one hand, according to the synergistic development strategy, after the iron and steel and coal mining industries in Hebei Province have released their production capacity and reduced their production capacity due to environmental protection issues, the industrial positioning of the cities of Hebei, Central Hebei, and South Hebei has been tilted to agriculture to a certain degree, which in turn reduces fragmentation and vulnerability caused by the seizure of agricultural land for construction; the north of Hebei, which bears the ecological upstream responsibility of the capital, is a typical ecologically fragile area [54], with relatively slow industrial and economic development, which makes Zhangjiakou different from other areas of Hebei Province in its development model, with policies favoring ecological restoration and protection over “retreating into three”, industrial upgrading and transformation, and so on [55], while the site development and hosting of the 2022 Winter Olympics accelerated to a certain extent the shift of Zhangjiakou’s economic model to tourism, which has led to an intensification of land-use conflicts between the urban outskirts of the northern Jibei region, tourism resources, and ecological land use. Other cross-regional development projects, such as the South-to-North Water Diversion Project, have also contributed to the spread of conflicts by forcibly dividing and occupying arable land.

At the same time, the transfer of industries from outside the region and the coordinated development of industries have occupied a large amount of agricultural land and ecological land, and the corresponding activities of balancing the occupation and compensation of arable land and the comprehensive improvement of the entire territory have contributed to the further development and evolution of conflicts between ecological land and agricultural land.

4.3. Policy Implications and Future Directions for Governance

Conflicting land use is a serious problem in the process of land-use transformation. It is of great significance to explore land-use policy perspectives from the perspective of land-use transformation to promote the coordinated utilization of land. Land-use policy plays an important role in shaping the spatial development pattern of land and regulating conflicts. China has introduced many land-use policies that have had a serious impact on land-use conflicts, such as the arable land occupation balance policy, which has mitigated the negative impacts of the occupation of arable land by construction land but has also increased the fragmentation of arable land and the attitude of mobility to a certain extent; the ecological red line policy has protected the integrity of ecological land and has also effectively reduced the land-use conflicts within ecological land. In addition, China has introduced a number of ecological control policies, such as regulations on nature reserves, green grain projects, and national parks.

These policies have played an obvious role in protecting ecological land and arable land and mitigating land-use conflicts. However, it is pointed out in our study that, despite the implementation of the above policies, land-use conflicts are still serious due to rapid urbanization, to the extent that the status quo of developmental conflicts coexisting with governance conflicts has emerged. In existing national land development planning, attention should be paid to the coordination of arable land and construction land, the regularization of urban–rural boundaries, and the hollowing out of rural land.

4.3.1. Stabilizing Urban–Rural Construction Land Conflicts through Use Control: Preventing the Spread of New Conflicts Due to Construction and Development

This study reveals that the uncontrolled expansion of rural residential bases has encroached on arable and ecological land, particularly in the plains and the Damshang Plateau. This issue, coupled with rural population exodus and the intensification of village hollowing in Hebei Province, has significantly complicated land-use conflict governance. To address this, the following should be carried out: First, in conjunction with the national spatial planning and use control system, the government should rationally plan the village system, define the scale of village development, and curb re-expansion; second, the government should strengthen the system of confirming and registering the rights to homesteads, legally replace and make full use of unused homesteads, and prohibit the new occupation of arable land and other ecological land. Finally, the government should encourage non-existing owners to voluntarily withdraw from surplus residential land, so as to realize the rational allocation and sustainable use of rural land resources.

Heavy conflicts have erupted at the edges of almost all urban land during urbanization. In plain areas, this mainly manifests as conflicts over the conversion of collective land to state-owned land, threatening the acquisition of arable land. In areas where cities and mountains connect, mountain development has exacerbated the ecological risk at the urban–rural fringe. With regional urbanization entering a stable stage, measures such as land space planning and use control should, through land space planning and use control measures, strictly control the scale of urban construction land and urban and rural development boundaries, strictly abide by the red line of ecology and arable land protection, change the increment into the stock of construction land resources for high-quality development, enhance the degree of urban land intensification and utilization efficiency, resolve the lagging risk of conflicts, and promote the harmonious coexistence of urban development and the natural environment.

4.3.2. Ensure the Sanity of Arable Land Replenishment and Ecological Governance and Avoid Intensifying Lagging Governance Conflicts

Spatial coupling analysis shows significant north–south spatial differentiation between high–high and low–low aggregation type areas. Low–high and high–low aggregation units are interspersed within these areas, suggesting that external factors in the region impact LUCs more than internal factors. Between 2015 and 2020, policy activities for arable land replenishment and ecological remediation triggered numerous conflicts. These irrational and hasty land governance decisions did not effectively alleviate LUCs. Therefore, it is recommended that the management authorities rationally formulate the relevant land-use policies and control the over-excited land-use industry, intervene in the improper policy-based land-use behaviors in a timely manner, and avoid the risk of new conflicts due to governance.

4.3.3. Ensure Land-Use Coordination in the Process of Regional Synergistic Development and Reduce the Externality Drivers of Conflict

In the process of Beijing–Tianjin–Hebei integration, the pursuit of comprehensive, coordinated, and sustainable regional development is a long-term task. Facing the gap with the international metropolitan area [56], the social, economic, and land-use structure of Hebei Province will also be affected by macro-strategic policies and the evacuation activities of the capital city’s functions for a certain period of time [52]. The regional industrial structure and land-use pattern in this context will also generate different forms of land-use conflicts [57,58,59]. From the perspective of enhancing the international competitiveness of the metropolitan area, Hebei Province should take the initiative to respond to the needs of the integration strategy under the linked land-use planning mechanism of Beijing–Tianjin–Hebei, in line with the strategic requirements of the transfer of industries in Beijing–Tianjin and the relocation of non-capital functions in Beijing, to minimize disordered development, to prevent over-consumption of land resources and environmental pollution, and to take effective measures to minimize the risk of land conflicts arising from new construction and development.

In conclusion, in the context of regional synergistic development, conflicts arising from previous construction and development still exist in Hebei Province and are superimposed on lagging governance conflicts, which will be the focus of future conflict risk prevention.

4.4. Implications and Limitations for Future Research

This study is based on the context of urbanization and regional synergistic development to explore land-use conflicts, exploring the distribution and potential changes in conflicting land use in Hebei Province from two perspectives: landscape conflicts and functional conflicts. And it qualitatively analyzes the driving factors of conflicts in less developed areas in synergistic development. In terms of research objectives and research methods, the field of land conflicts is extended to a certain extent.

This study also has some limitations. (1) Due to the limitations of data acquisition, fewer indicators were selected for functional conflict analysis, which did not fully reflect the conflict potential of land functions and reduced the accuracy of the results; (2) this paper only provides a superficial discussion of conflict resolution and future policies, and further research is needed in the future; (3) the purpose of identifying and analyzing land-use conflicts is to mediate them, but other unquantifiable conditions (e.g., political, social, communication, etc.) were not taken into account, so future research is needed to supplement and improve this study.

5. Conclusions

The thesis explores the conflicting land use in Hebei Province, which is on the periphery of the capital’s coordinated development economic circle, from 2005 to 2020. This exploration occurs within the context of rapid urbanization and industrialization and considers both landscape conflicts and functional conflicts, drawing the following conclusions.

The temporal pattern of conflicting land use shows a development course of intensification, slowing down, and smoothing out. In terms of landscape conflicts, four heavy conflict zones have formed. In terms of functional conflicts, lower-level conflicts remain stable, middle- and high-level conflicts transform sequentially, and there is a phenomenon of “conflict polarization”. The outskirts of industrial cities and towns, river coasts, and the “city-mountain connection” zones in two mountainous regions are the hotspots of “conflict polarization”. On the double autocorrelation coupling of land-use landscape conflict and land-use function conflict, the high–high aggregation type area and the low–low aggregation type area differ from the plain area and the mountain area. A large number of low–high aggregation units and high–low aggregation units are staggeringly confined to the first two types of areas. This is manifested in the spatial pattern where conflicts in plain areas are dispersed and random, while conflicts in mountain stream belts are concentrated, and conflicts in the internal ecological zones of the mountains are stabilized.

The development of conflicts is synchronous with the time pattern of construction and development during the acceleration of industrialization and urbanization in Hebei. Meanwhile, the balance of cropland occupation and land ecological governance activities produces lagging conflicts. These conflicts are characterized by the coexistence of conflict development and recession and the coexistence of developmental and governance conflicts. As a peripheral area of the capital economic circle, Hebei Province is subject to the internal drive of its own development needs and the external influence from the Beijing–Tianjin–Hebei synergistic development. The internal drive mainly manifests in the internal diffusion of the intensive economic activity area, the guiding role of the traditional industrial pattern and industrial policy, and the constraints of geospatial space. Under regional synergistic development, the natural spillover of economic activities from the Beijing–Tianjin region, ecological and environmental protection requirements, differentiated zoning strategy, economic factor flow, and the integration of internal and external development goals form the external influences on conflicting land use in Hebei Province.

In land use, three suggestions are made to reduce and defuse the risk of future land conflicts: first, stabilize urban–rural construction land conflicts through use control to prevent new conflicts from spreading due to construction and development; second, ensure the rationality of arable land replenishment and ecological governance to avoid intensifying lagging governance conflicts; and third, enhance land-use coordination during regional synergistic development to reduce the externality-driven role of conflicts.