Comprehensive Land Consolidation Zoning Based on Minimum Cumulative Resistance Model—A Case Study of Chongqing, Southwest China

Abstract

Comprehensive land consolidation (CLC) has become an effective tool for promoting the coordinated development of production, living, and ecological spaces (PLES) in rural China. Given the remarkable territorial differentiation, planning strategies that are geared towards local conditions are indispensable for implementing CLC projects. This study employs the minimum cumulative resistance (MCR) model to simulate the horizontal competition among PLES in Chongqing. The suitability evaluation index system for PLES was developed using natural ecological data, socio-economic data, and land use data from Chongqing Municipality. The results show that: (1) Based on the principles of productivity, livability, and sustainability, the suitability of PLES in Chongqing is classified into highly suitable, moderately suitable, generally suitable, unsuitable, and extremely unsuitable areas. The spatial distribution of suitability across different levels in Chongqing exhibits certain degrees of overlap, intersection, and clustering. (2) Based on the different resistance relationships, 1031 townships in Chongqing were divided into seven types of CLC areas. The northeastern and southeastern regions of Chongqing Municipality exhibit distinct ecological and functional advantages, whereas the northern and western parts of the city are characterized by greater multifunctionality. (3) Tailored CLC measures are suggested for various suitability scenarios, aligning with local conditions and planned developments. The MCR model and PLES theory integrated zoning methods for CLC are practicable and effective, providing a scientific foundation for the construction of land consolidation plans in Chongqing and important references for regional sustainable development.

1. Introduction

Rapid urbanization and industrialization have created significant changes in land use and coverage [1]. Arable land and forests globally have declined markedly, while the demand for food and natural resources continues to surge [2]. This dynamic has strained the relationship between humans and the environment [3,4]. A crucial issue demanding prompt resolution for the sustainable development of China and the world is the harmonization of economic and social development with ecological and environmental protection. This includes coordinating the contradictions between the continuous decline in environmental carrying capacity and the escalating demand for resource utilization [5,6,7]. To address this challenge, the Chinese government proposed the construction of “intensive and efficient production space, livable and moderate living space, and beautiful ecological space” in 2012 [8]. The production, living, and ecological spaces (PLES) concept mirrors the internationally popular “Three Pillars” theory, both focusing on multifunctional land use [9]. A series of policies and documents have been enacted to foster the coordinated development of PLES [10]. However, China’s extensive rural areas continue to confront challenges including disordered spatial development, inefficient land and resource utilization, degradation of the human settlement environment, and ecological pollution, which can be attributed to the long-standing absence of planning guidance and constraints. Achieving the coordinated development of PLES in rural areas, given multiple pressures such as environmental stress, resource limitations, and economic development, necessitates exploring the optimal utilization of multifunctional land based on the natural background conditions and local circumstances [11].

Practice has found that comprehensive land consolidation (CLC) can be an excellent tool for coordinating PLES [12]. CLC plays a pivotal role in facilitating agricultural and rural modernization, improving human settlements and environmental conditions, and promoting ecological governance [13,14,15]. CLC is a vital means to achieve the coordinated development of PLES, and the organic integration and development of PLES also rely on the key support of CLC. However, as an emerging rural governance tool that extends beyond traditional land consolidation, CLC in China faces problems such as single-minded goals, rigid consolidation models, and a focus on engineering but not on overall planning. The phenomenon of regional homogenization severely restricts the actual effectiveness of CLC. Considering the regional spatial differentiation and development stages, conducting differentiated CLC based on the characteristics of PLES and its functional differentiation is essential to ensuring its effective implementation [16,17,18]. Up to this point, some scholars have carried out a series of beneficial research and explorations on CLC zoning, which has played an important role in the sustainable development of the region, but there are still some limitations. (1) In terms of research perspectives, most studies are limited to a single functional perspective, such as farmland protection [19,20], optimization of rural settlements [21,22], or ecological conservation [23,24]. While these studies achieve optimal resource allocation, they do not consider the multifunctionality of land. (2) In terms of research methods, qualitative methods such as expert meetings and public discussions [25], as well as quantitative methods such as gray constellation clustering [26], neural network models [27,28], and fuzzy clustering [29], have been employed. However, qualitative methods are subjective and one-sided, while conventional quantitative methods often only meet the requirements of single-function zoning evaluation, which is insufficient to match the needs of the coordinated development of PLES. (3) At the research scale, many scholars have proposed differentiated CLC models at the provincial [27,30], city [23], and county levels [31]. However, there is limited research on land consolidation zoning at the microscale of townships. This is inconsistent with the current situation in China, where townships are the basic unit for CLC, and its practicality needs to be strengthened. As the core force of China’s grassroots governments, townships have relatively obvious regional characteristics and differences in socio-economic conditions, and they also have strong organizational and executive capabilities. Carrying out CLC with townships as the basic research units is more conducive to unified planning, resource coordination, and work advancement.

Therefore, it is of great significance to explore a zoning method that comprehensively considers PLES and proposes a differentiated CLC model with townships as the basic implementation unit. This approach can improve resource utilization efficiency and promote coordinated development between regions [32]. The minimum cumulative resistance (MCR) model has been widely utilized in landscape ecological security pattern analysis [33], suitability evaluation of building land [34], and other sectors to analyze the suitability of land expansion by generating resistance surfaces for various parameters within a region. The MCR model can simulate the process of mutual balance and constraint among PLES, achieving the comprehensive maximization of production, living, and ecological benefits. By introducing the MCR model into CLC zoning research, it is possible to differentiate the suitability evaluation of regional PLES and seek an optimal solution in terms of economic development and ecological conservation.

Chongqing Municipality represents the integration of diverse characteristics, including being a major city with a large rural area, a mountainous region with a significant reservoir area, and the coexistence of economic development and ecological conservation. Since becoming a direct-controlled municipality, Chongqing has experienced rapid urban expansion and substantial economic development. Nonetheless, it has also encountered notable challenges, including disorderly spatial expansion, extensive land use, and environmental degradation [35]. Moreover, due to its location in the mountainous region of southwestern China, Chongqing Municipality displays characteristics such as fragmented land use, dispersed settlements, and a high degree of ecological vulnerability. Therefore, the complex coordination between production, livelihoods, and ecology, as well as the quest for sustainable development in Chongqing, has received considerable attention from scholars. Moreover, Chongqing’s practice of CLC has been at the forefront nationwide [36,37]. Exploring the violent conflicts and sustainable development paths among PLES in Chongqing makes the research more comprehensive and representative.

Based on the preceding discussions and reviews, this study aims to address the following scientific questions: (1) How can CLC effectively resolve the practical dilemma of coordinating the development of PLES in the face of declining resources and environmental carrying capacity and the growing demands for resource utilization? (2) Considering the significant variations in natural resource endowments and socio-economic conditions, how should the differentiated CLC model be implemented in Chongqing Municipality to suit the local context? Consequently, this study takes 1031 townships in Chongqing as the basic research unit. The research employs 2020 data on land use types, socio-economic factors, and natural ecology as the foundational dataset. The MCR model was used to determine the functional strength of PLES in Chongqing, to identify optimal land use ways. Subsequently, distinct CLC strategies are suggested, taking into account the characteristics and requirements of PLES, to achieve efficient utilization of land resources and coordinated development. This approach can offer valuable insights and serve as a reference for land consolidation planning not only in China but also in other developing countries worldwide.

2. Analytical Framework

2.1. The Development Dilemma of PLES

PLES are defined by the dominant functional types of production, living, and ecological functions (PLEF) [38], which categorize land into production space, living space, and ecological space. These spaces are essential for human development [39], human life [40], and human existence [41], respectively. PLES are interconnected, with mutual influence, dependencies, and pressures among them [9,42]. These three types of spaces are essentially functional complexes within the urban and rural regional systems, where elements such as land, population, industry, ecology, technology, and information are interconnected through specific structures and organizational methods. The essence of the PLES conflict is the competition and game process of various types of interest subjects for the pursuit of different economic interests, ecological interests, social interests, etc., on the same element. With the continuous advancement of urbanization and industrialization, it is difficult to satisfy the diversified needs of human beings with single-function advantageous space, which leads to the intensification of this competition and game process. The competition for land within the PLES has become increasingly prominent, exacerbating the contradiction between human beings and land. This situation poses challenges for the coordinated development of PLES, making it more complex [43].

Firstly, the PLES concept encounters significant challenges in its internal development. Regarding production space, the cultivated land in most areas of China is fragmented and scattered due to the comprehensive influence of long-term institutional factors biased towards urban areas and natural resource conditions. Additionally, the basic production facilities are incomplete, and there is a significant issue of the short-term abandonment of cultivated land. Moreover, the rural processing and manufacturing industry has a weak industrial foundation, resulting in low comprehensive benefits. Furthermore, the emerging rural tourism industry exhibits a more serious homogeneous development phenomenon and lacks attractiveness. In terms of living space, there is an uneven configuration of public service infrastructure, including rural medical and health services, culture, sports, and entertainment facilities, as well as education and health care, due to the comprehensive influence of planning management and traditional concept factors. Additionally, rural buildings are in disarray, the living environment is deteriorating, and there is a lack of management and repairs for ancient villages and other valuable cultural heritage sites. Regarding ecological space, there is a severe imbalance in the structure and function of the ecosystem, and rural areas frequently experience natural disasters such as droughts, floods, soil erosion, and pest and disease attacks. The forest composition is predominantly homogeneous, and there are significant issues of grassland desertification, land desertification, and other phenomena.

Secondly, the mutual influence and restrictions between different components of the PLES concept create additional obstacles to its coordinated development. The adoption of traditional agricultural production models, such as a single planting structure and extensive production methods prevalent in rural areas of China, has led to issues such as agricultural non-point source pollution, decreased soil fertility, reduced biodiversity, and an accelerated degradation process of the ecosystem. The fragmentation of rural land reduces the level of concentration in both rural production space and living space, thereby exacerbating the process of rural labor migration. However, the absence of mechanisms for homestead transfer and withdrawal has increased, rather than decreased, the scale of rural construction land. Moreover, the dispersed nature of rural settlements adds to the challenges of domestic waste and sewage treatment, consequently exacerbating point source pollution that contributes to ecological space degradation. The reckless exploitation of ecological space to fulfill the production and living demands of urban and rural residents has resulted in issues including groundwater depletion, land salinization, and river eutrophication. These problems, in turn, limit rural production and living functions.

2.2. The Versatility of CLC

In China, after nearly three decades of practice and policy evolution, land consolidation has evolved from isolated and scattered practices focused on agricultural land, construction land, and ecological protection and restoration into CLC that integrates mountain–river–forest–farmland–lake–grassland systems [44]. Compared with the traditional land consolidation model with a single element and a single method, CLC is a more systematic, comprehensive, and full-cycle method. CLC integrates economic, social, and engineering characteristics. The timely development of CLC helps to gradually reduce the unbalanced development between urban and rural areas, activate the endogenous development power of rural areas, and coordinate the harmonious development of man and nature [45,46].

In terms of production space, CLC enables the optimal allocation of spatial elements in production space by modifying land use patterns and spatial allocation, thereby facilitating the adjustment and optimization of the rural industrial structure. The main measures that can be implemented include: (1) Merging fields, eliminating field ridges, increasing the net cultivated land coefficient, and increasing the effective cultivated land area. Simultaneously, enhancing the quality of cultivated land through soil improvement and other methods significantly boosts agricultural product yields. (2) Implementing rational layouts of irrigation ditches and roads and promoting agricultural mechanization to increase the efficiency of agricultural production, reduce costs, and enhance agricultural product productivity. (3) Achieving centralized and contiguous land transformation through measures such as adjusting land ownership and developing unused land, thereby facilitating the adjustment of the industrial land structure and the development of rural characteristics or advantageous industries. (4) Enhancing the construction of agricultural facilities, improving the establishment of cultivated land quality monitoring, soil moisture monitoring, and insect pest monitoring stations in the region, and reinforcing agricultural science and technology service capabilities.

In terms of living space, CLC can optimize the spatial layout of rural residential areas and enhance the construction of rural public service infrastructure by implementing construction land remediation and residential environment improvements. The main measures that can be implemented include: (1) Reclaiming construction land with low utilization value and meeting reclamation criteria, guiding villagers to live in appropriately scaled areas, and optimizing the layout of construction land. (2) Enhancing courtyard beautification, toilet renovation, house style renovation, etc., in large village settlements to improve living infrastructure and enhancing the level of public service provision. (3) Constructing new rural communities to cater to the demands of rural tourism development and rural industry growth, fostering large-scale settlements and industrial clusters. (4) Restoring courtyards in villages and towns with local folk customs to preserve traditional rural features and the local historical context.

In terms of ecological space, CLC can improve the diversity and stability of the ecosystem through ecological protection and restoration, the construction of ecological environment protection facilities, and other means. Possible measures mainly include: (1) Establishing plant corridors, farmland buffer zones, etc., and transforming and optimizing the spatial layout of existing corridors to facilitate material flow exchange between ecosystems. (2) Constructing green ecological facilities, such as ecological drainage ditches and ecological pest-killing lamps, to mitigate the risks of agricultural pests and diseases, minimize ecological pollution caused by pesticides, and simultaneously purify farmland runoff to reduce ecosystem pollution. (3) Implementing projects such as mine ecological restoration, water pollution control, and woodland ecological protection, restore the landscape, and repair mountains, water bodies, forests, etc. (4) Conducting water quality improvement and environmental monitoring at critical nodes of the ecosystem, such as rivers, lakes, mountains, and grasslands, to enable real-time monitoring and systematic protection of ecological environment quality.

While CLC is highly versatile, it should be acknowledged that it may not be suitable for all areas. Considering the ongoing decline in resource and environmental carrying capacity, the practice of CLC must adhere to the laws of nature. Otherwise, it will further aggravate the contradiction between the PLES. This would defeat the original purpose of CLC. However, considering the increasing demand for resource utilization, it is crucial to maximize land resources. Therefore, it is extremely necessary to evaluate the suitability of the PLES. Regional sustainable development can only be achieved by implementing CLC based on suitability evaluation and adapting it to local conditions. Figure 1 shows the logical analysis framework for the study.

3. Materials and Methods

3.1. Study Area

Chongqing is situated on the upper reaches of the Yangtze River. It covers 82,400 km², consisting of 38 districts and counties, including 1031 townships. As of 2022, Chongqing has an approximate population of 32.12 million, with an urbanization rate of 70.96%. As shown in Figure 2, chongqing’s topography is primarily composed of hills and mountains, with mountains making up 76% of the region. The terrain gradually decreases from the south and north to the Yangtze River Valley, and Chongqing experiences a subtropical humid monsoon climate. Positioned at the intersection of the “Belt and Road” initiative and the Yangtze River Economic Belt, Chongqing plays a distinctive and vital role in the nation’s regional development and opening-up strategy. Nevertheless, there are notable disparities in the development of various regions within Chongqing concerning natural resource distribution, geographical location, and socio-economic conditions. Consequently, this has led to significant conflicts among the PLES, for which immediate actions are required to promote balanced and sustainable development in this region.

3.2. Data Sources and Processing

The data utilized in this study include information on distance accessibility, socio-economic factors, and the natural environment (

Table 1. Key data and sources.

Type	Data Name	Type Format	DATA Resolution	Data Source
Land use data	Land use data	Raster	30 m × 30 m	Resource and Environment Science and Data Center https://www.resdc.cn/Default.aspx (accessed on 20 May 2023)
Distance accessibility data	The downtown, rural settlement, river	Raster	30 m × 30 m	Land use data extraction
Socio-economic data	GDP	Raster	1 km × 1 km	Resource and Environment Science and Data Center https://www.resdc.cn/Default.aspx (accessed on 21 May 2023)
	Points of interest	Vector	-	Resource and Environment Science and Data Center https://www.resdc.cn/Default.aspx (accessed on 20 May 2023)
	Geological disaster	Vector	-	Global Disaster Data Platform https://www.gddat.cn (accessed on 20 May 2023)
	Road network	Vector	-	Open street map
	NPP-VIIRS	Raster	500 m × 500 m	National Earth System Science Data Center http://geodata.nnu.edu.cn (accessed on 20 May 2023)
Natural environment data	DEM	Raster	30 m × 30 m	Geospatial data cloud platform https://www.gscloud.cn (accessed on 20 May 2023)
	Slope, topographic position index	Raster	30 m × 30 m	DEM extraction
	Precipitation	Raster	1 km × 1 km	Resource and Environment Science and Data Center https://www.resdc.cn/Default.aspx (accessed on 22 May 2023)
	NDVI	Raster	30 m × 30 m	Resource and Environment Science and Data Center (https://www.resdc.cn/Default.aspx) (accessed on 22 May 2023)
	Biological richness index	Raster	30 m × 30 m	Calculated according to the proportion of different land use types in the grid [47]
	Ecosystem service value	Raster	30 m × 30 m	The calculation is based on the unit ecosystem service equivalent factor [48]

). The land use types are classified into cultivated land, forest land, grassland, waterbodies, construction land, and unused land. Distances from rivers, rural settlements, townships, and main roads were calculated using the Euclidean distance function in ArcGIS 10.8. The POI data mainly comprise national and provincial scenic spots, national forest parks, world natural and cultural heritage sites, schools, hospitals, and markets. The biological richness index and ecosystem service values were calculated using land use and relevant socio-economic data, following established methodologies. Through comparative analysis, all the data are integrated into raster format with a grid cell size of 30 × 30 m, using the same projection coordinate system. This can improve the reliability of research results and better reflect the spatial heterogeneity of resource endowments and socio-economic conditions in the study area.

3.3. Research Methods

3.3.1. Overview of the MCR Model

The MCR model was initially proposed by Knaapen [49], considering three factors: source, distance, and landscape interface characteristics. The model characterizes the distance of material flow, energy flow, and information flow from the source to other landscapes, as well as the minimum cost required in this process [50]. This study utilizes the MCR model to investigate the optimal spatial layout of PLES. The principle involves simulating the process of the PLES expansion source spreading into the surrounding space. Areas with lower resistance encountered in this process are considered more suitable for the spatial layout of the corresponding source. Equation (1) is used to calculate the MCR.

$$\begin{array}{c}WMCR=f_{min}{\displaystyle \sum _{j=n}^{i=m}}\left(D_{ij}\times R_i\right)\end{array}$$

(1)

In Equation (1), WMCR represents the minimum cumulative resistance value; the variable “f” represents the minimum cumulative resistance of any point and its positive correlation function with the distance to the source and the land landscape feature; Dij represents the spatial distance that a species travels through landscape unit i from source j to a specific point; R_i is the resistance coefficient of landscape unit i for movement; and the cumulative value of (D_ij × R_i) can be considered a measure of the relative accessibility of a species along a specific path from a source to a point in space.

The evaluation method comprises the following four steps:

Step 1: Determine the expansion sources of PLES.

Step 2: Select the resistance factors that affect the expansion of PLES.

Step 3: Construct the minimum cumulative resistance surface of PLES.

Step 4: According to the different relationships between the minimum cumulative resistances of PLES, the study area is divided into 7 types of CLC.

3.3.2. Determination of the Expansion Source for PLES

The term “source” refers to the starting point of outward expansion, characterized by strong external expansion capability, internal consistency, and significant attraction ability. For the production space, the “source” is selected as various types of industrial development land with scale agglomeration and an area exceeding 100 mu. For the living space, the “source” refers to urban or rural residential areas with strong public service capabilities, including schools, hospitals, supermarkets, and an area of more than 20 mu, which are selected based on POI data. For the ecological space, the “source” includes ecological lands within the ecological protection red line, national forest parks, world cultural and natural heritage sites, water conservation areas, and national and provincial key scenic spots.

3.3.3. Select the Resistance Factors That Affect the Expansion of PLES

The regional distribution of PLES is influenced by multiple variables, such as natural regulation, socio-economic factors, and development convenience. This study conducted a statistical analysis of the PLES suitability evaluation indicators identified in the relevant literature. Based on the concepts of productivity, livability, and sustainability, as well as the actual situation in Chongqing and experts’ comments, a total of 18 resistance elements were identified. Each resistance component was categorized into five groups (ranging from 10 to 90) based on its resistance level. The weights were calculated using AHP, yielding CR values of 0.026 for productive space, 0.007 for dwelling space, and 0.003 for ecological space. All these values successfully passed the consistency test.

Table 2. Resistance system for the expansion of PLES in Chongqing.

Items	Resistance Factor	Factor Classification and Score [51,52,53,54,55]					Weight
		10	30	50	70	90
PS	Land cover	Cultivated land	Unused land	Construction land	Grassland, Forest land	Waterbody	0.265
	Annual temperature	>17.3	15.4–17.3	13.1–15.4	10.2–13.1	≤10.2	0.112
	Slope	≤2	2–6	6–15	15–25	>25	0.208
	Distance from water source (m)	≤500	500–2000	2000–5000	5000–10,000	>10,000	0.159
	Distance from main road (m)	≤500	500–1500	1500–2500	2500–5000	>5000	0.119
	Distance from settlement (m)	≤500	500–1000	1000–1500	1500–2000	>2000	0.137
LS	Land cover	Construction land	Unused land	Grassland	Cultivated land	Waterbody, Forest land	0.251
	Topographic position index	≤0.40	0.4–0.5	0.5–0.6	0.6–0.7	>0.7	0.127
	Economic density (Yuan∙108/km2)	>35.28	4.45–35.28	1.57–4.45	0.33–1.57	≤0.33	0.152
	Distance from geologic calamity (m)	>10,000	5000–10,000	2000–5000	1000–2000	≤1000	0.175
	Distance from POI (m)	≤500	500–1500	1500–3000	3000–5000	>5000	0.164
	Distance from urban area (m)	≤1000	1000–5000	5000–10,000	10,000–15,000	>15,000	0.131
ES	Land cover	Waterbody, Forest land	Grassland	Cultivated land	Unused land	Construction land	0.243
	Elevation (m)	>1652	1169–1652	801–1169	488–801	≤488	0.122
	NDVI	>0.8	0.6–0.8	0.4–0.6	0.2–0.4	≤0.2	0.133
	Ecosystem service value (Yuan∙104/hm2)	>2268	1652–2268	1290–1652	844–1290	≤844	0.182
	Brightness at night	≤4.5	4.5–15.8	15.8–32.6	32.6–79.9	>79.9	0.144
	Biological richness index	>79.3	67.3–79.3	54.7–67.3	40.7–54.7	≤40.7	0.176

displays the resistance system for the expansion of PLES in Chongqing.

3.3.4. Construct the Minimum Cumulative Resistance Surface of PLES

Firstly, the single-factor resistance layer is combined with different weights to generate a comprehensive resistance surface. Secondly, the “cost-distance” analysis module in the ArcGIS platform is used to select the source and the corresponding comprehensive resistance surface in the dialog box. This technique results in the generation of the minimal cumulative resistance layer for PLES. A lower minimum cumulative resistance value indicates a better spatial layout of the specific space type and a stronger function of the related PLEF. Based on the minimum cumulative resistance distance value, the production suitability, life suitability, and ecological suitability are graded as highly suitable areas (P1/L1/E1), moderately suitable areas (P2/L2/E2), generally suitable areas (P3/L3/E3), unsuitable areas (P4/L4/E4), and extremely unsuitable areas (P5/L5/E5).

3.3.5. Establishing the Differential Resistance Surface

Record the MCR values of production space, living space, and ecological space as MCR_P, MCR_L, and MCR_E, respectively, and make a difference between them. The modeling formula is as follows:

$$\begin{array}{c}{MCR}_{dif1}={MCR}_P-{MCR}_L\end{array}$$

(2)

$$\begin{array}{c}{MCR}_{dif2}={MCR}_E-{MCR}_P\end{array}$$

(3)

$$\begin{array}{c}{MCR}_{dif3}={MCR}_E-{MCR}_L\end{array}$$

(4)

The different relationships indicate the most suitable development direction for the township. For instance, if MCR_dif1 > 0, MCR_dif2 < 0, and MCR_dif3 < 0, it indicates that the ecological function is the strongest in the township, followed by the living function, while the production function is the weakest. When the difference between two MCR values is within a threshold range near “0,” it suggests that the township should aim for coordinated development with multiple functions. The threshold value is determined based on the MCR difference and the area curve [56]. As shown in Figure 3, the resistance difference between MCR_E and MCR_L becomes 0 at point A; the inflection point of the negative territory is B (−72,177); and the inflection point of the positive territory is C (87,250). Therefore, the study believes that the ecological function and living function of townships with a resistance difference between −72,177 and 87,250 are relatively close and should be developed in a coordinated manner. Based on the difference in resistance, the area is divided into several functional advantage zones: production functional advantage zones (PFZ), living functional advantage zones (LFZ), ecological functional advantage zones (EFZ), production–living functional advantage zones (PLFZ), ecological–living functional advantage zones (ELFZ), ecological–production functional advantage zones (EPFZ), and production–living–ecological functional coordination zones (PLEFZ).

4. Results

4.1. Construction of Comprehensive Resistance Surface

Figure 4 shows the comprehensive resistance values that need to be overcome for the expansion of PLES in Chongqing. The results indicate the following:

• For the spatial expansion of production spaces in Chongqing, the lowest comprehensive resistance is 10.0, while the highest is 84.7. Regions such as Tongnan District, Dazu District, Hechuan District, and Dianjiang District, located in the western and northern parts of Chongqing, exhibit relatively lower comprehensive resistance values due to factors such as flat terrain, abundant water resources, and developed transportation. In contrast, areas such as Chengkou County, Wushan County, and Youyang County in the northeast and southeast regions face higher comprehensive resistance due to factors such as steep terrain, water scarcity, and pressures related to ecological conservation.
• For the spatial expansion of living space in Chongqing, the lowest comprehensive resistance is 13.0, while the highest is 90.0. Regions such as Yuzhong District, Jiangbei District, and Nan’an District, which fall within the urban functional core area, exhibit lower comprehensive resistance values. These areas are generally economically developed and offer convenient living conditions. In contrast, the northeastern and southeastern parts of Chongqing experience higher comprehensive resistance due to factors such as topography, level of economic development, and public service capacity.
• For the spatial expansion of ecological space in Chongqing, the lowest comprehensive resistance is 10.0, while the highest is 84.7. The northeastern and southeastern parts of the city exhibit relatively lower comprehensive resistance values. In contrast, the areas within the urban functional core zone, such as Yuzhong District, Nan’an District, and Jiangbei District, have the highest comprehensive resistance values. The western and northern regions form larger-scale high-resistance areas due to factors such as high human activity intensity and relatively lower ecological conservation importance.

4.2. Suitability Analysis of PLES Based on the MCR Model

Figure 5 illustrates the minimum cumulative resistance for the production, living, and ecological spaces in Chongqing.

Table 3. Area composition of PLE suitability in Chongqing.

Type	Suitability Grades	Range of Minimum Cumulative Resistance	Proportion of Total Townships (%)
Production space	P1	0–1216	18.58
	P2	1216–5133	30.88
	P3	5133–17,742	31.07
	P4	17,742–58,341	15.14
	P5	58,341–189,054	4.33
Living space	L1	0–114,254	29.69
	L2	114,254–149,740	11.41
	L3	149,740–263,994	25.47
	L4	263,994–631,856	25.96
	L5	631,856–1,816,252	7.47
Ecological space	E1	95–1328	20.16
	E2	1328–6082	20.64
	E3	6082–24,404	17.80
	E4	24,404–95,022	31.27
	E5	95,022–367,199	10.13

reflects the area composition of PLE suitability in Chongqing. The different intervals of minimum cumulative resistance values also correspond to varying PLES suitability levels. In terms of production suitability (as shown in Figure 5a), Chongqing shows a general pattern of high suitability in the northern and western regions and low suitability in the northeastern and southeastern regions, which aligns with the Municipal Agricultural Development Plan of Chongqing. The most suitable areas (P1) account for 18.58% and are primarily dispersed in Chongqing’s western regions, including Tongnan District, Dazu District, and Hechuan District, as well as the northern regions, including Changshou District and Dianjiang District. These townships benefit from relatively level topography, good irrigation, and better land productivity. The moderately suitable areas (P2) account for 30.88% and are predominantly concentrated in Chongqing’s central and northern sectors, including Banan District, Fuling District, Kaizhou District, and Wanzhou District. Despite the relatively flat topography, irrigation conditions are average, and the cultivation radius is greater. The generally suitable areas (P3) account for 31.07% and are concentrated in Chongqing’s northeastern and southeastern regions, including Yunyang County, Pengshui County, and Qianjiang District. These areas are mainly distributed along valleys, and the land is relatively fragmented. Unsuitable areas (P4) account for 15.14% and are dispersed in a “striped” pattern throughout Chongqing’s northeastern and southeastern regions, including Chengkou County, Wuxi County, Wulong District, and Youyang County. These areas are predominantly mountainous, with limited accessible agricultural land, and they are significantly influenced by slope and water supplies. The extremely unsuitable areas (P5) account for 4.33% and are scattered across Chongqing. These areas have steeper terrain and are often home to famous mountains and rivers in Chongqing, such as Simian Mountain, Jinfo Mountain, and Daba Mountain.

In terms of living suitability (as shown in Figure 5b), the highly livable areas in Chongqing are mainly located in the central urban area and along the river, with a general pattern of high livability in the central-western region and low livability in the northeast and southeast. The most livable areas (L1) account for 29.69%, exhibiting the characteristic of a large cluster with several small clusters. The large clusters radiate outward from the core of the main urban area of Chongqing City, while the small clusters are scattered around the surrounding counties. These areas generally have flat terrain, well-developed public infrastructure such as education and healthcare facilities, and a relatively high proportion of built-up areas. The moderately livable areas (L2) account for 11.41% and are sporadically distributed around the most livable areas and towns, with a higher concentration in the central-western region. These areas are farther away from the city center but still within the reach of public services such as healthcare and education. The moderately livable areas rely heavily on the public infrastructure services provided by the city center but have relatively average living conditions. The generally livable areas (L3) account for 25.47% and are widely distributed throughout various regions, with fragmented distribution. They depend on the basic public services provided by the city center but are located at a greater distance, resulting in relatively average living conditions. The unsuitable areas (L4) account for 25.96% and are mostly located in the northeastern and southeastern parts, including Yunyang County, Fengjie County, Wulong District, and Pengshui County. These areas are predominantly mountainous, limited by certain topographical constraints, and have a lower level of economic development. However, they possess abundant ecological resources. The extremely unsuitable areas (L5) account for 7.47% and are concentrated in the central areas of the unsuitable regions, mainly in the northeastern and southeastern parts, such as Chengkou County, Wuxi County, Shizhu County, and Youyang County. These areas have steep terrain, a lower proportion of developed land, and a higher number of geological hazard points within their jurisdiction, resulting in a lower level of livability.

In terms of ecological suitability (as shown in Figure 5c), Chongqing City exhibits a pattern of high ecological suitability in the northeast and southeast and lower suitability in the north and west. The most suitable areas (E1) account for 20.16% and are predominantly distributed in the northeastern and southeastern parts, including Chengkou County, Wuxi County, Shizhu County, and Pengshui County. These areas have higher elevations, abundant forest resources, and high species richness. Ecological protection is extremely important in these regions. The moderately suitable areas (E2) account for 20.64% and are mainly distributed around the most suitable areas. These areas are often located along the valleys of mountain ranges and have relatively lower elevations. The generally suitable areas (E3) account for 17.80% and are primarily located in the northern part of Chongqing, including Fuling District, Fengdu County, and Zhong County. These regions have relatively limited ecological resources, such as forests and grasslands, but they are adjacent to important ecological protection barriers, such as the Yangtze River. The unsuitable areas (E4) account for 31.27% and are mostly distributed in the western and northern parts of the study area, including Bishan District, Ba’nan District, Dianjiang County, and Liangping District. These areas have abundant arable land resources, but they have limited species richness and ecosystem service value. The extremely unsuitable areas (E5) account for 10.13% and are located in the central areas of the unsuitable regions. These areas serve as important bases for human productive activities, resulting in high human activity intensity and a low Normalized Difference Vegetation Index.

4.3. Differentiated Strategy of CLC

According to Figure 5, the spatial distribution of the different levels of PLES appropriateness in Chongqing City exhibits some overlap, intersection, and aggregation. This suggests that conflicts over the utilization of PLES are unavoidable in the city. By using the ArcGIS platform to calculate the minimum accumulative resistance representing the suitability of PLEF, pairwise differences were computed. Based on the combination of different values, the dominant functional types for each township were determined, resulting in the zoning map of PLES suitability in Chongqing City (Figure 6). Overall, the northeastern and southeastern parts of the study area show notably advantageous ecological functionality. Conversely, the northern and western regions exhibit stronger production and living functions, which highlights their multifunctionality. Therefore, CLC should implement a differentiated model based on the functional characteristics of each area and maximize the multifunctional attributes of land use as suitability permits.

The production function advantage zones (PFZ) account for 38.64% of the total number of townships, primarily concentrated in the western and northern regions of Chongqing, such as Tongnan District, Dazu District, Dianjiang County, and Liangping District. These townships serve as the primary source of agricultural product supply in Chongqing and must strictly adhere to the protection of permanent basic farmland, prohibiting any form of land development or construction activities that encroach upon arable land. CLC should consider the following four aspects to enhance production efficiency and achieve sustainable development. (1) Optimize spatial planning by scientifically designing the spatial layout based on natural conditions such as geography, climate, and soil, as well as socio-economic factors such as market demand and technological advancements. This optimization aims to improve land utilization efficiency. For instance, the residential areas with poor basic living conditions in the area should be relocated as a whole and transformed into more advantageous production spaces for development and utilization. (2) Vigorously promote the construction of high-standard basic farmland, enhance soil fertility, improve basic production facilities such as irrigation, drainage, and roads, and establish modern agricultural production facilities to enhance both production efficiency and quality. (3) Increase investment in agricultural science and technology, actively provide technical training, elevate farmers’ production skills, enhance their capacity to cope with risks and disasters, and ensure the quantity and quality of agricultural production. (4) Develop corresponding processing and manufacturing industries, rural e-commerce, and other industries to establish a complete agricultural industry chain, increase the added value of products, and improve farmers’ income levels.

The living functional advantage zones (LFZ) account for 2.95% of the total number of townships, primarily concentrated in the core areas of cities such as Shapingba, Jiulongpo District, Nanan District, and Jiangbei District. CLC should prioritize meeting residents’ needs and improving their quality of life. (1) Actively carry out land consolidation for construction purposes, guide residents to live in moderate concentration, optimize the spatial layout of construction land, and allocate surplus indicators for the resettlement of villagers, rural infrastructure construction, and industrial development land construction. (2) Improve public service infrastructure such as education, healthcare, cultural, and recreational facilities and ensure equitable spatial distribution to meet residents’ material, cultural, and spiritual needs. (3) Implement habitat environment improvement projects, including architectural facelifts, courtyard beautification, toilet renovations, etc., to create unique rural landscapes and enhance the landscape coordination of living spaces. (4) While pursuing a comfortable living environment, also develop supporting industries such as the service sector and light industry to provide residents with diversified employment opportunities.

The ecological function advantage zones (EFZ) account for 39.92% of the total number of townships, primarily concentrated in the northeastern and southeastern parts of Chongqing, including counties such as Chengkou, Fengjie, Youyang, and Pengshui. These townships largely fall within the ecological conservation red line and serve as important ecological product supply areas in Chongqing. CLC should focus on ecological restoration and systematic protection. (1) Optimize rural ecological spaces by implementing poverty alleviation relocation for residential land within the ecological conservation red line. Additionally, sporadic farmland outside the red line that is unsuitable for large-scale development should be transformed into forested land through land retirement. (2) Implement ecological restoration projects for mining areas, water pollution control, and forest ecosystem protection. Restore landforms and rehabilitate mountains, water bodies, and forests. Simultaneously, improve water quality and environmental monitoring for vital ecological nodes such as rivers, lakes, mountains, and grasslands to ensure real-time monitoring of ecological system protection, restoration, and environmental quality. (3) Develop eco-tourism and ecological products without compromising the integrity of the ecosystem. Improve relevant tourism infrastructure and convert ecological resources into ecological assets, promoting local economic and social development.

The production–living functional advantageous zones (PLFZ) account for 8.55% of the total area of townships, with significant distribution in Yongchuan District, Yubei District, Dazu District, Tongliang District, and Changshou District in Chongqing City. These townships boast favorable topographical conditions and convenient water sources and serve as important industrial production bases. Additionally, they are located close to urban areas and fall within the radius of public infrastructure services, thus possessing strong living functions. During the implementation of CLC, it is essential to strike a balance between industrial development and the needs of the local communities. (1) By comprehensively considering factors such as market conditions, climate, and available resources, it is crucial to develop a well-planned spatial layout for industrial parks, residential areas, and public service facilities. This approach promotes the development of industrial zones, capitalizing on the advantages of economies of scale and agglomeration, while ensuring that public service facilities radiate to all residential areas as much as possible, thereby enhancing land utilization efficiency. (2) Active efforts should be made to carry out land improvement projects for both agricultural and construction purposes. Measures such as the increase–decrease linkage should be employed to coordinate the development demands of industrial land with the expansion needs of residential living spaces. This coordination ensures a harmonious balance between the requirements of industrial land development and the necessary expansion of living spaces for residents. (3) The introduction of environmentally friendly, modern, and sustainable production technologies should be prioritized. While improving quality and efficiency, it is crucial to minimize the environmental impact. Create a high-quality composite space for the coordinated development of modern industrial development and environmentally friendly community construction.

The ecological–production functional zones (EPFZ) account for 3.74% of the total number of townships, with scattered distribution in areas such as Hechuan District, Fuling District, Jiangjin District, and Wanzhou District. These townships have a significant amount of arable land, and their jurisdictions also encompass abundant ecological resources such as forests and water bodies. CLC should consider both economic development and ecological conservation. (1) It is necessary to optimize the ecological and spatial aspects by implementing ecological land retirement within the ecological protection redline. This should be carried out while ensuring that arable land is concentrated, expanded in quantity, and improved in quality, and rationally optimizing the layout of permanent basic farmland. (2) Vigorously implement efficient and stable production methods such as precision agriculture and organic agriculture to ensure food security while promoting resource conservation. At the same time, strengthen the prevention and control of agricultural non-point source pollution to reduce the impact on the ecological environment. (3) Based on the local ecological advantages, it is essential to focus on the development of green agricultural products that possess local characteristics. This can be achieved by exploring the integrated development model of “agriculture + tourism,” which aims to harmoniously unite economic development and ecological protection.

The ecological–living functional zones (ELFZ) account for 3.15% of the total number of townships, primarily located around the city center. A few scattered distributions exist in areas such as Fuling District and Wanzhou District. These townships are situated near the ecological protection barrier of the Yangtze River, exhibiting prominent ecological functions. Additionally, they are close to the city center, ensuring a strong capacity for providing living services. In the implementation of CLC, it is necessary to balance the needs of residents and ecological conservation: (1) Define ecological protection boundaries, restore natural ecosystems, strictly control the increase in construction land, and avoid encroachment on ecological spaces. (2) Strengthen environmental governance and monitoring, adhere to waste-sorting practices, strictly prohibit the indiscriminate discharge of sewage, and utilize green and sustainable modern environmental remediation technologies to restore ecological spaces. (3) Enhance environmental protection advocacy and education, raise residents’ awareness of environmental conservation, and vigorously develop environmental protection industries such as environmental governance and waste recycling, providing employment opportunities while prioritizing environmental protection. (4) Promote a moderate concentration of the population in residential areas and increase the availability of urban parks and green spaces. Improve the efficiency of public service facility utilization, reduce resource consumption, and create resource-efficient and environmentally friendly composite spaces.

The production–living–ecological functional coordination zones (PLEFZ) account for 3.05% of the total number of townships, with relatively concentrated distributions in areas such as Beibei District, Yongchuan District, Jiangjin District, and Wanzhou District. These regions are mainly located around urban areas, have a certain level of public service provision, and are close to water sources. They feature flat terrain and prominent production functions. Additionally, they possess certain ecological resources, making them the most diverse in terms of spatial utilization functions. In the implementation of CLC, it is crucial to effectively coordinate industrial development, livable conditions, and ecological conservation in these areas: (1) Systematic planning should be carried out to first meet the needs of ecological space protection and then consider the needs of the livable construction of living space and the development and expansion of production space. Based on this foundation, more detailed and accurate functional zoning should be delineated. (2) Adhere to green, coordinated, and innovative development principles by introducing modern technologies for production, construction, and management, which aim to minimize the impact of human activities on the ecological environment. (3) Utilize the comprehensive advantages of coordinating production, living, and ecological functions. Establish and improve infrastructure for industrial development while actively cultivating distinctive industries that prioritize green and environmental protection. Create a harmonious rural environment that is suitable for both living and business activities. Explore the integrated development model of “agriculture + culture + tourism”.

Table 4. Classification of suitability-type zones in Chongqing.

Suitability Zoning	Proportion (%)	Main Features	Main Measures
PFZ	38.64	The main source of agricultural product supply	(1) Improvement of agricultural production infrastructure to increase the efficiency of agricultural production. (2) Strengthen investment in agricultural science and technology to improve the yield and quality of agricultural products. (3) Construct the whole industrial chain of agricultural products and improve the income level of farmers.
LFZ	2.95	Urban functional core area	(1) Optimize the spatial layout of construction land and guide residents to live in a moderate concentration. (2) Improve public service infrastructure and balance its spatial allocation. (3) Develop certain supporting industries and provide diversified employment opportunities for residents.
EFZ	39.92	Important Ecosystem Conservation Area	(1) Implement ecological protection and restoration projects and conduct real-time monitoring of the quality of the ecological environment in key areas. (2) Develop rural tourism and turn ecological resources into ecological assets without destroying the local ecosystem.
PLFZ	8.55	Public service supply capability and productivity are equally outstanding	(1) Coordinate the development needs of industrial land and the expansion needs of residents’ living space through measures such as increasing and decreasing linkage and the balance of entry and exit. (2) Introduce green, modern, and sustainable production technology to improve production quality and efficiency while minimizing environmental impact.
EPFZ	3.74	Balance economic development and ecological protection	(1) Vigorously implement efficient and stable production methods such as precision agriculture and organic agriculture to reduce the impact on the ecological environment. (2) Based on the advantages of local ecological functions, explore the integrated development model of agriculture and tourism.
ELFZ	3.15	Taking into account the need for livable life and ecological protection	(1) Strictly control the increment in construction land to avoid the extrusion of ecological space. (2) Promoting moderately concentrated population living, reducing resource consumption, and creating resource-saving and environment friendly composite spaces.
PLEFZ	3.05	It is necessary to coordinate the relationship between industrial development, livable life, and ecological protection.	(1) First, meet the needs of ecological space protection, and then consider the need for livable living space construction and production space expansion. (2) Utilize the comprehensive advantages of the coordination of the functions of the PLES, actively cultivate green and environmentally friendly characteristic industries, and create a livable, suitable, and beautiful rural natural and social environment.

summarizes the characteristics of the classification of suitability-type zones in Chongqing and the main rectification measures.

5. Discussion

This case study of Chongqing found that an integrated approach using the MCR model and PLES theory in the zoning of CLC was feasible and effective. Utilizing the PLES theory for suitability assessment is indeed helpful in identifying the strengths and weaknesses of diverse PLEF zones in different regions [36,55]. This assessment serves as a foundation for formulating distinct CLC strategies. The study utilizes the MCR model to simulate the competitive process among PLES within a specific region. The results indicate that regions with higher suitability for production also possess prominent living functions, highlighting a significant conflict between production space and living space, especially in the western areas of Chongqing. If these regions also contain abundant ecological resources such as forests and water bodies, the ecological space will also become part of this competition. This has been confirmed in some townships in the western and northern regions of Chongqing. Based on the differences in resistance observed during the competition process, suitable CLC models for township development are identified. Ultimately, Chongqing is categorized into seven types of CLC zones, encompassing areas dominated by a single function as well as regions with coordinated development of multiple functions. The resulting CLC zoning is in alignment with the local natural conditions and location factors, and it is generally consistent with the findings from previous studies [36,57]. This study is also in line with the spatial development pattern of “one zone and two groups” outlined in the “Territorial spatial planning of Chongqing municipality (2021–2035)”. The western region of Chongqing serves as a significant hub for high-quality development. Going forward, it is crucial to continuously explore the multifunctional utilization of land and establish it as a leading zone for industrial upgrading and a high-quality livable area within the city. The northeastern and southeastern parts of Chongqing should focus on promoting ecological protection based on local ecological resources and regional characteristics and build green development demonstration areas under the principle of ecological priority.

It should be noted that although this study explores the optimal method of land use from the perspective of suitability, it can only inform the systematic planning of CLC from a macro perspective. CLC is a complex social endeavor that engages various stakeholders, including the government, enterprises, villagers, and the market. It manifests not only in the direct transformation of fields, water, roads, forests, and villages but also in the indirect role of talent, technology, industry, information, and other elements [58]. These indirect effects exhibit noticeable delays [43,59]. This delayed effect is the key to truly stimulating rural hematopoietic function and achieving sustainable development [60]. Achieving this delayed effect necessitates the synergy among multiple government departments, support from land use policies [61,62], and adaptability to market mechanisms [63]. In addition, due to the complex relationship of mutual influence and mutual restriction between the PLES, adjustments to one or more spaces will inevitably cause overall changes in other spaces and even the entire domain [64]. Therefore, in the practical process of CLC, it is often necessary to dynamically adjust the remediation measures according to changes in PLES.

Compared to existing research, the method that utilizes the MCR model and PLES theory more accurately captures the multifunctionality of land use. The attributes of the production, living, and ecological functions of land are indivisible [55]. These three aspects form an organic entity, competing and limiting each other. The balance among the scale, structure, and spatial distribution of these three land types manifests as the equilibrium of their expansion processes. The most common form of competition occurs when production and living spaces continually encroach upon and occupy ecological spaces, leading to their degradation. Suitability analysis conducted from a single perspective invariably overlooks the other functional attributes of the land [65]. Given the ongoing decline in resource and environmental carrying capacity, coupled with increasing demand for resource utilization, the ultimate goal of land use should be to optimize ecological, social, and economic benefits comprehensively. To realize this comprehensive benefit maximization, it is necessary to maximally expand PLES. In the past, the methods of CLC zoning only considered a certain aspect of multifunctional land use, focused on the development and protection of cultivated land [66], focused on the evaluation of construction land remediation potential [67], or explored the construction of landscape ecological patterns [16]. Some studies have considered multiple attributes of land, such as its natural, socio-economic, and ecological aspects, when constructing a comprehensive evaluation index system. However, methods such as the weighted index summation [67], artificial neural network (ANN) [27], and cellular automaton (CA) [68] that have primarily been used focus on the vertical process of land evaluation, neglecting the horizontal process. However, the MCR model is more effective in reflecting the horizontal process of land expansion. The underlying principle is that the expansion and compression relationship exhibited by PLES during spatial competition is influenced by the suitability of the spatial unit. Each spatial unit has varying degrees of suitability for land resource utilization, leading to different resistances encountered during the expansion process. The lower the resistance, the higher the suitability. In comparison to other methods, the MCR model not only enables a hierarchical analysis of the intensity of a single PLEF function but also illustrates the optimal spatial layout of PLES following a horizontal competition process.

There are also some limitations to this study. (1) The evaluation index system developed in this study has some limitations and subjectivity. Specifically, obtaining relevant basic data for Chongqing City was challenging, and the accuracy and precision of various data types vary, posing difficulties in data collection and processing. Consequently, the selection of 18 indicators is relatively constrained. Moreover, the weights of each evaluation index were primarily determined using the AHP method, which involved subjective ratings from experts and introduced a certain degree of subjectivity. (2) The study examines the optimal spatial arrangement of PLES but does not adequately consider the complex relationships among PLEF functions. Although the MCR model integrates and evaluates the PLEF of land use to determine an optimal solution for resource utilization among these three aspects, the study overlooks the intricate relationships and balance among production, livelihood, and ecological functions. Clarifying these complex relationships would enhance spatial planning outcomes, foster organic coordination between the regional economy, society, and ecology, and promote sustainable and environmentally friendly regional development.

6. Conclusions

Firstly, as a comprehensive social engineering endeavor, the versatility of CLC can solve the practical dilemma of the coordinated development of the PLES. However, due to the various constraints imposed by limited resources, economic development, and ecological protection, it is necessary to conduct suitability evaluations and implement CLC through zoning. This study employed the MCR model to simulate the competitive process among PLES and categorized 1031 townships in Chongqing into seven types of CLC areas. The research findings indicate that the zoning method that employs the MCR model and PLES theory provides a more accurate understanding of the multifunctionality of land use. The CLC zoning method that integrates PLES theory and the MCR model can not only conduct intensity analysis of a single function in PLEF but also illustrate the best way to use land multifunctionally after the horizontal competition process. This method helps clarify the man–land contradiction between industrial development, livable life, and ecological protection and promotes regional sustainable development.

Secondly, CLC should align with the development direction of townships and effectively safeguard the leading functional advantages of townships through diverse engineering measures. In the northeast and southeast of Chongqing, CLC should prioritize the implementation of projects aimed at natural resource protection and ecological restoration to safeguard regional ecological functions. The core task of CLC in this region is to investigate approaches for transforming ecological resources into ecological assets. In the western and northern regions of Chongqing, CLC should engage in systematic planning, establish more detailed functional zoning, and enhance resource utilization efficiency. The core task of CLC in this region is to fully coordinate the human–land conflicts between the PLES.

Thirdly, further explorations are needed in the following aspects for future research: (1) Conduct an extensive collection of relevant opinions and suggestions and enhance the scientific and rational optimization of the evaluation index system. (2) Considering the introduction of coupling coordination degree, geographic detectors, and other models to explore the synergistic relationship between PLEF and the interactive influence of different factors on the suitability of PLEF will help refine the practical measures of CLC. (3) Summarizing experiences from successful cases in various functional areas will facilitate the transformation of the comprehensive land improvement strategy into a more practical implementation pathway.