Evolving Urban Expansion Patterns and Multi-Scenario Simulation Analysis from a Composite Perspective of “Social–Economic–Ecological”: A Case Study of the Hilly and Gully Regions of Northern Loess Plateau in Shaanxi Province

Abstract

Over recent decades, the hilly and gully regions of the northern Loess Plateau in Shaanxi province have grappled with severe soil erosion and a precarious ecological milieu. Shaped by urbanization policies, this locale has encountered a gamut of issues, including an imbalance in human–environment dynamics and the degradation of ecological integrity. Consequently, the comprehension of how urban expansion impacts the optimization of regional landscape configurations, the alignment of human–environment interactions in the Loess Plateau’s hilly and gully domains, and the mitigation of urban ecological challenges assumes paramount importance. Leveraging data from land use remote sensing monitoring, alongside inputs from natural geography and socio-economic spheres, and employing methodologies such as landscape pattern indices, we conduct an exhaustive analysis of Zichang City’s urban fabric from 1980 to 2020. Furthermore, employing the CLUE-S model, we undertake multifaceted scenario simulations to forecast urban expansion in Zichang City through to 2035. Our findings delineate two distinct phases in Zichang City’s urban expansion trajectory over the past four decades. From 1980 to 2000, urban construction land in Zichang City experienced a phase of methodical and steady growth, augmenting by 64.98 hectares, alongside a marginal decrease in the landscape shape index (LSI) by 0.02 and a commensurate increase in the aggregation index (AI) by 1.17. Conversely, from 2000 to 2020, urban construction land in Zichang City witnessed an epoch of rapid and haphazard expansion, doubling in expanse, marked by a notable escalation in LSI (2.45) and a corresponding descent in the AI (2.85). The precision of CLUE-S model simulations for Zichang City’s land use alterations registers at 0.88, fulfilling the exigent demand for further urban expansion and land use change prognostication. Under the aegis of the natural development scenario, the augmentation of urban construction land in Zichang City primarily encroaches upon grassland, farmland, and woodland, effectuating an increase of 159.81 hectares. Conversely, under the ambit of urbanization development, urban construction land contends predominantly with farmland, grassland, and woodland, heralding an augmentation of 520.42 hectares. Lastly, under the mantle of ecological protection, urban construction land expansion predominantly encroaches upon grassland, farmland, and woodland, resulting in an augmentation of 4.27 hectares. Through a nuanced analysis of the spatiotemporal evolution of urban expansion and scenario-based simulations, this study endeavors to furnish multi-faceted, scenario-driven, and policy-centric insights for regional planning, urban spatial delineation, and regional ecological safeguarding.

1. Introduction

Land, as an indispensable natural asset underpinning human societal and economic endeavors, assumes a paramount role in fostering social and economic sustainability and realizing the imperatives outlined in Sustainable Development Goals (SDGs). Particularly pertinent in the pursuit of SDG 11 (advancing inclusive, resilient, and sustainable urban settlements) and SDG 15 (promoting the sustainable use and conservation of terrestrial ecosystems), judicious land employment emerges as an essential precondition [1,2]. However, amidst the global tide of urbanization, challenges have surfaced, including the unchecked pace of urban land expansion, rampant spatial sprawl, and discordant spatial arrangements [3]. Notably, despite cities encompassing a mere 3% of the globe’s landmass, they accommodate a staggering 55% of the global populace, exacerbating the palpable tension between human habitation and environmental integrity [4]. Projections suggest a twofold increase in global urban areas by 2095 [5]. Furthermore, aside from the socio-environmental disequilibrium induced by urban sprawl, the unrelenting urban sprawl encroaches incessantly upon urban ecological habitats, aquatic bodies, and protected natural reserves, progressively encumbering and infringing upon these vital resources [6]. Thus, elucidating the spatiotemporal dynamics of urban expansion and envisaging the forthcoming urban landscape transitions assumes critical significance.

The United Nations’ “New Urban Agenda” underscores the ongoing global trend of rural-to-urban migration, with urban populations burgeoning at an unprecedented pace [7]. This swift demographic surge and concurrent urban land expansion have engendered a myriad of challenges, encompassing social inequities, developmental disparities, and ecological degradation [8,9]. Consequently, the features and driving forces behind urban land expansion have assumed centrality among global researchers and political decision-makers, emerging as pivotal avenues for delving into the intricate interplay between human endeavors and their environmental ramifications, and illuminating significant socio-economic developmental issues alongside their associated environmental effects [10]. Current investigations into urban land expansion predominantly concentrate on the scrutiny of spatiotemporal evolution characteristics [11,12,13], exploration of driving mechanisms [14,15,16], and evaluation of the social, economic, climatic, and ecological ramifications stemming from urban spatial expansion [17,18,19,20]. Nonetheless, prevailing studies largely adopt short-term research perspectives, devoid of high-temporal-resolution analyses tracking urban expansion dynamics [21]. Methodologically, extant research often resorts to singular methodologies for either qualitative or quantitative analyses, yielding outcomes characterized by pronounced singularities and an absence of comprehensive analyses integrating diverse methodologies [22]. Looking forward, extant research predominantly scrutinizes historical facets of urban expansion, lacking simulations of future urban expansion trajectories under diverse policy contexts, thereby falling short of fulfilling the exigencies for urban expansion forecasting analyses [23]. Therefore, it is equally imperative to incorporate various influential factors driving urban sprawl when simulating future urban expansion trajectories, building upon the examination of historical urban expansion dynamics.

Simulation models for land use change play a pivotal role in spatial planning and carry significant implications for forecasting future urban land layouts [24]. Cellular automata (CA) are widely recognized as an acceptable method for simulating large-scale land use changes [25,26]. For instance, studies have employed cellular automata to simulate urban land use changes in Toronto, Canada, thus introducing a novel tool for more refined simulations of land use alterations [27]. Additionally, the PLUS model, developed on the foundation of the CA model and embedding Markov chains, enables the prediction of land use quantity demands, thereby partially mitigating the shortcomings of the CA model. For example, research has utilized socio-hydrogeological methods and the PLUS model to simulate land use changes in the future Angas Bremer Specified Wells Area [28]. However, further deliberations are necessary to ascertain the suitability of these models for simulating land use changes in small-scale regions. The CLUE-S model emerges as an advantageous tool for simulating land use changes in small-scale regions [29]. This model, an improvement upon the CLUE model, has been refined to overcome limitations regarding the number of land use types and other factors. In comparison to CA, PLUS, and FLUS models, the CLUE-S model demonstrates greater efficacy in simulating land use changes at small scales [30]. Concurrently, the integration of natural geography, transportation accessibility, socio-economic dynamics, and policy influences within the CLUE-S model presents a robust approach to capturing the intricate nuances of future land use changes within multifaceted contexts. Consequently, the application of the CLUE-S model to forecast urban land use dynamics holds paramount significance, particularly within county-level domains and regions characterized by intricate topographies. Nonetheless, as an essential prerequisite for simulating urban expansion, there exists an exigent demand for a land use change simulation model capable of delineating urban construction land as a discrete land class, devoid of the constraints on land typology.

Historical data on urban land use spatial dynamics form the bedrock for uncovering the evolutionary traits of urban development. In data selection, scholars have opted for Ipswich City in Queensland, Australia, leveraging vector data to simulate the dynamics of land use transformation amidst urban expansion, thereby enriching the understanding of urban planners [31]. Additionally, researchers have harnessed Landsat data to effectively simulate the urban landscape of Lagos in Nigeria by 2030 [32]. However, the utilization of urban land as a standalone land category, as employed in the aforementioned studies, warrants further discourse. The Comprehensive National Land Use and Cover Change (CNLUCC) dataset offers heightened precision in simulating land use changes across multiple temporal stages, while also settling the debate regarding urban land’s classification, thus refining simulation accuracy [33]. Furthermore, CNLUCC exhibits comprehensive, dynamic, objective, and efficient attributes in examining ongoing land use transformations, thereby presenting distinct advantages in analyzing the spatiotemporal evolution of urban construction land and simulating urban land dynamics [34].

The Loess Plateau is not only the cradle of Chinese civilization but also a pivotal region for urbanization development in China [35], exhibiting a rural–urban development process characterized by “self-organization” and “self-renewal” [36]. While it boasts numerous distinctive features, it also confronts a plethora of challenges, necessitating the urgent adoption of scientific and efficient planning and policy guidance [37]. As a key battleground for new urbanization initiatives in western China, the hilly and gully areas lack a clear urban expansion model [38]. The prevailing urban and rural planning schemes alongside policy interventions have markedly disrupted the regional environment and urban construction endeavors [39]. In some valley areas, urbanization has proceeded rapidly, with urban land excessively expanding outward, leading to the emergence of high-rise residential areas in certain shallow mountain regions through extensive excavation and high slope cutting [40]. This monotonous and disorderly urban expansion exacerbates the aging and vacancy of traditional settlements, thereby accentuating the conflicts between people and land in urban development [41]. Hence, in the urban construction of the Loess Plateau’s hilly and gully areas, direct application of rural–urban planning experiences from plain areas poses significant challenges. Rather, it is imperative to integrate local urban expansion characteristics and future development forecasts, guided by the principle of harmonious coexistence between humans and the environment. This necessitates exploration and effective utilization of urban spatial potential within gully areas, thereby endeavoring to establish a mode of orderly urban expansion.

In recent years, Zichang City’s development planning for hills and canyon landscapes has undergone significant transformations, influenced by multiple factors. With urbanization rapidly advancing, urban expansion has exerted notable pressures on the natural scenery. Some development projects have overlooked environmental concerns, leading to issues such as soil erosion and vegetation degradation. Concurrently, climate change has introduced profound effects on hills and canyon landscapes, with diminishing rainfall and escalating extreme weather events exacerbating ecological vulnerabilities. To confront these challenges, Zichang City has implemented a series of measures. Notably, urban expansion planning and management have been reinforced to ensure coherence between urban growth and environmental preservation. Through strategies like delineating ecological redlines and enacting comprehensive land use plans, destructive development activities within hill and canyon regions are rigorously curtailed. Moreover, efforts in ecological restoration have been intensified, progressively rehabilitating compromised ecosystems through initiatives like reforestation and soil conservation. Additionally, bolstered environmental monitoring and early-warning mechanisms facilitate the timely detection and mitigation of environmental issues. In practical implementations, Zichang City has effectively executed several emblematic projects. For instance, ecological governance initiatives in designated canyon areas have successfully mitigated soil erosion and enhanced local ecological integrity through measures such as silt dam construction and afforestation. Furthermore, amidst urban expansion, deliberate efforts have been made to preserve and leverage the natural beauty of hills and canyons, with the creation of parks and green spaces providing aesthetically pleasing recreational havens for residents. Despite the protective measures safeguarding Zichang City’s ecological treasures and advancing sustainable urban development, it is essential to acknowledge the iterative nature of urban planning, necessitating continuous refinement and adaptation. To ensure a harmonious balance between economic progress and environmental conservation in the future, Zichang City must delve deeper into historical trends and effectively anticipate future trajectories, thereby devising more scientifically sound and pragmatic strategies and methodologies.

Building upon this premise, the aims of this study are delineated as follows: (1) to scrutinize the spatiotemporal pattern evolution of Zichang City spanning from 1980 to 2020; (2) to discern the driving forces underpinning urban expansion within Zichang City; (3) to prognosticate and simulate the urban transformation trajectories of Zichang City up to the year 2035. Through a focused inquiry into Zichang City, a more nuanced comprehension of the regularities and distinct characteristics inherent in urban development within the hilly and gully regions of the Loess Plateau can be gleaned, thus furnishing a robust scientific foundation and actionable policy recommendations for forthcoming urban planning and development endeavors.

2. Research Area and Data Source

2.1. Overview of the Study Area

Zichang City (109°11′58″ E–110°01′22″ E, 36°59′30″ N–37°30′00″ N) is situated in the heart of the Loess Plateau, flanked by the Hengshan District to the north, and bordered by Zizhou County and Qingjian County to the east. To the south lie Yanxian County and Yan’an City, while Ansai District and Jingbian County neighbor it to the west. Encompassing three streets and eight towns, the city spans a total area of 2405 km² (see Figure 1). Zichang City epitomizes the undulating topography of the Loess Plateau, with elevations ranging from 930 to 1562 m. Characterized by rolling hills and meandering gullies, hills and valleys cover approximately 94.6% of the total area. Zichang City experiences a warm temperate semi-arid continental monsoon climate, characterized by low temperatures and significant temperature fluctuations. With an annual average temperature of 9.1 °C and average annual precipitation of 514.7 mm, the city is traversed by three major tributaries, namely, the Qingjian River, Wuding River, and Yan River, with numerous surface streams and modest flow rates. As of the end of 2022, Zichang City had a permanent population of 215,300 people and achieved a regional gross domestic product of CNY 16.584 billion [42].

2.2. Data Sources

The study data are bifurcated: natural geographic data and socio-economic data (

Table 1. Description of data sources and applications.

Category	Data	Time	Resolution	Source
Physical geographic data	Land use data	1980–2020	30 m	China Resources and Environmental Science and Data Center [43]
	DEM	2005	30 m	China Resources and Environmental Science and Data Center [44]
	Water area	2005	-	China Resources and Environmental Science and Data Center [45]
Socioeconomic data	Population density	2005	1000 m	China Resources and Environmental Science and Data Center [46]
	GDP	2005	1000 m	China Resources and Environmental Science and Data Center [47]
	Railway	2005	-	China Resources and Environmental Science and Data Center [48]
	Highway	2005	-	NASA [49]
	Nighttime light data	2005	1000 m	Global Change Research Data Publishing & Repository [50]

). Natural geographic data encompasses land use datasets, digital elevation models (DEM), and water body data. Socio-economic data encompasses population density, GDP, railway, highway, and nighttime light data. Details regarding the temporal coverage, resolution, and sources of the data are delineated below.

3. Research Methodology

Building upon land use data, we delineated urban construction land and employed land use transition matrices alongside spatial autocorrelation indices to ascertain the spatial distribution and evolutionary dynamics of urban construction land in Zichang City from 1980 to 2020. Moreover, tailored to diverse scenarios, we integrated the Markov Chain approach and utilized the CLUE-S model to simulate the variations in urban construction land across Zichang City under different developmental trajectories.

3.1. Land Use Change and Urban Expansion

3.1.1. Land Transfer Matrix

The land transfer matrix serves as a precise tool for delineating the origins, destinations, transferred-out, and transferred-in areas of various land-type conversions. This study incorporates the land use transfer matrix to scrutinize the dynamic changes in land use within Zichang City from 1980 to 2020. Adopting a 20-year interval, it delves into the dynamic characteristics of transfer structures and directions between different land classes in Zichang City during its initial and final stages. Its conventional expression format is elucidated as follows [51]:

$$A={\left(A_{ij}\right)}_{n\times n}=\left[\begin{array}{ccc}{A}_{11}& \cdots & A_{1n}\\ ⋮& \ddots & ⋮\\ A_{n1}& \cdots & A_{nn}\end{array}\right]$$

In this formulation, A represents the respective areas of different land use types; n stands for the total number of land use types; and i and j denote the land use types at the commencement and conclusion of the study period, respectively. A_ij signifies the area transitioned from land type i to land type j during the initial and final phases of investigation. Leveraging land use data from both periods, a spatial overlay analysis was conducted using ArcGIS 10.8 software to compute the land use transfer matrix, facilitating the analysis of the dynamic evolutionary processes across various land use types.

3.1.2. Landscape Pattern Indices

Urban expansion directly precipitates alterations in urban landscape patterns. Therefore, we scrutinize spatial land changes by integrating landscape pattern indices. These indices are comprehensively evaluated across five key dimensions, encompassing density, land use composition, scale, shape, and aggregation. The objective is to gauge and delineate the landscape pattern of Zichang City at both patch-type and landscape levels. Specifically, we meticulously select five landscape indices—patch number (NP), patch area (CA), largest patch index (LPI), shape index (LSI), and aggregation index (AI)—each imbued with profound ecological significance. Through these indices, we conduct a quantitative analysis of land use changes in Zichang City, probing aspects such as landscape fragmentation and diversity. The computation formulas and implications of the landscape indices employed in this study are elucidated in

Table 2. Spatial autocorrelation indices and their meanings.

Primary Indicator	Secondary Indicator	Description	Formula	Indicates the Formula
Density index	Patch number (NP) [52]	Total number of a specific patch types within the landscape.	$\mathrm{N}\mathrm{P}={\mathrm{n}}_{\mathrm{i}}$	In the formula, ni represents the number of patches of a particular patch type within the landscape, measured in “units”.
Land use index	Patch area (CA) [53]	Represents the scale of a specific patch type.	$\mathrm{C}\mathrm{A}={\displaystyle \sum _{\mathrm{j}=1}^{\mathrm{n}}}{\mathrm{a}}_{\mathrm{i}\mathrm{j}}\times \frac{1}{1000}$	Where aij represents the area of patch ij, with CA ≥ 0, measured in square hectares (hm2).
Scale merit	Largest patch index (LPI) [54]	Represents the proportion of the landscape area occupied by the largest patch within the region.	$\mathrm{L}\mathrm{P}\mathrm{I}=\frac{\mathrm{a}}{\mathrm{C}\mathrm{A}}$	a represents the area of the largest patch within a certain patch type, measured in square hectares (hm2); CA represents the total area of patches of a certain type within the landscape.
Shape index	Landscape shape index (LSI) [55]	Characterizes the irregularity or complexity of a specific patch. A higher value indicates greater irregularity and elongation of the corresponding patch shape.	$\mathrm{L}\mathrm{S}\mathrm{I}=\frac{0.25\sum _{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{c}}_{\mathrm{i}}}{\sqrt{\sum _{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{a}}_{\mathrm{i}}}}$	Where ci denotes the perimeter of the i-th patch, measured in meters (m), and ai represents the area of the i-th patch, measured in square hectares (hm2).
Convergence and dispersion index	Patch aggregation index (AI) [56]	Represents the connectivity between patches, where a higher value indicates greater connectivity and aggregation within the patches.	$\mathrm{A}\mathrm{I}=\left[{\displaystyle \sum _{\mathrm{i}=1}^{\mathrm{m}}}\left({\mathrm{g}}_{\mathrm{i}\mathrm{i}}/\mathrm{m}\mathrm{a}\mathrm{x}{\mathrm{g}}_{\mathrm{i}\mathrm{i}}\right){\mathrm{P}}_{\mathrm{i}}\right]\times 100$	gii represents the number of similar adjacent patches for the corresponding landscape type.

.

3.2. Selection and Verification of Driving Factors

3.2.1. Selection of Driving Factors

Natural, geographic, social, and economic factors exert distinct influences on urban expansion dynamics. To quantitatively characterize these influences, we draw upon previous research and select a total of nine driving factors for the evolution of urban expansion patterns, including elevation, slope, aspect, distance to water bodies, distance to highways, distance to railways, GDP, population density, and nighttime light data [57,58,59]. Leveraging ArcGIS 10.8 software, we extracted slope and aspect from DEM data, while all distances were computed as Euclidean distances. Additionally, we transformed the driving factors into ASCII files to serve as input variables for subsequent simulations of land use changes (Figure 2).

3.2.2. Verification of Driving Factors

Utilizing the inherent convert tool within the CLUE-S model, we proceeded to convert the ASCII-formatted data into a format amenable to statistical analysis software such as SPSS. Subsequently, we conducted binary logistic regression analysis using the functionality provided by SPSS 22 software, adhering to the formula as outlined [60]:

$$\log \left(\frac{{\mathrm{P}}_{\mathrm{i}}}{1-{\mathrm{P}}_{\mathrm{i}}}\right)={\beta }_0+{\beta }_1{\mathrm{X}}_1+{\beta }_2{\mathrm{X}}_2+\dots \dots +{\beta }_{\mathrm{n}}{\mathrm{X}}_{\mathrm{n}}$$

In the equation, P_i signifies the suitability when the grid cell corresponds to the ith land use type, while X represents the value of the driving factor in that specific grid cell. The stepwise regression procedure facilitates the elimination of driving factors with minimal correlation to the ith land use type from the regression equation, effectively setting the corresponding β coefficient of the driving factor to 0. Given the receiver operating characteristic (ROC) method’s several advantages, including its resilience to sample imbalance, we employ the ROC method to evaluate the regression results’ goodness-of-fit [61]. ROC values range between 0.5 and 1, with higher values indicating better fit and thus stronger explanatory power of the driving factors for the grid cell’s land use type. Typically, ROC > 0.7 is considered to demonstrate considerable explanatory power. Hence, in this study, we select driving factors with ROC > 0.7.

3.3. Model Principles and Scenario Design

3.3.1. Principle of the CLUE-S Model

The CLUE-S model comprises a non-spatial analysis module and a spatial allocation module. The non-spatial analysis module is employed to compute the demand quantities of various land types in the target year of the study area, achieved through the utilization of the Markov model. Meanwhile, the spatial allocation module, predicated on the input parameters of land demand, iteratively allocates land use types to grid cells based on the spatial distribution characteristics of driving factors. This process enables the spatiotemporal simulation of different land types across various years. The spatial allocation mechanism, being the focal point of the entire CLUE-S model, is determined by the overall allocation probabilities, as articulated mechanistically [62]:

$$T_i=P_{i,u}+I_u+E_u$$

In the equation, T_i denotes the aggregate probability of each grid’s suitability for land use types, P_i,u signifies the spatial probability derived from the binary logistic regression equation, I_u represents the iterative variable of land types, and E_u stands for the parameters established in accordance with transformation rules.

3.3.2. Model Accuracy Validation

To ascertain the accuracy of CLUE-S model outcomes, prior to formal simulation, we initiated the simulation of Zichang City’s land use in 2020 using the 2005 land use map of Zichang City as the starting point. Subsequently, we compared the simulated results with the actual results (the authentic land use map of Zichang City in 2020). If they were congruent or exhibited a high degree of resemblance, it signified favorable simulation efficacy; conversely, discrepancies indicated otherwise. For evaluating similarity, we employed the Kappa coefficient to assess the spatial distribution consistency between the two images. The computational formula is as follows [63]:

$$Kappa=\frac{P_o-P_e}{P_p-P_e}$$

In the formula provided, p_o represents the ratio of identical pixel counts between the observed and simulated images to the total pixel count, signifying the overall accuracy. Meanwhile, p_o denotes the anticipated probability of consistency under the distribution of observed image data. Typically, Kappa values range from 0 to 1, where 0 indicates extremely low consistency between the observed and simulated images, while 1 indicates a high level of consistency.

3.3.3. Scenario Design

(1)

Natural Development Scenario

The natural development scenario assumes that land use change will not be influenced by human plans and policies, but will evolve solely based on the historical conditions of land use conversion. The research posits that historical growth patterns will persist in the coming decades; hence, no restrictive conditions are imposed in the simulation experiment.

(2)

The Scenario of New Urbanization

The new urbanization scenario places greater emphasis on economic advancement, thus imposing no restrictions on urban expansion. Furthermore, urban sprawl primarily encroaches upon arable land, grassland, forest land, and undeveloped land. Hence, drawing from the land use transfer matrix spanning 2005 to 2020 and the actual conditions in Zichang City, we augment the probabilities of conversion from arable land to construction land, grassland to construction land, and undeveloped land to construction land. The transition probabilities between other land categories remain unaltered.

(3)

Ecological Conservation Scenario

The ecological protection scenario underscores the collaborative endeavors and the preservation of the ecological milieu, accentuating the safeguarding of forests, grasslands, and arable lands. Synthesizing the land use dynamics in Zichang City, we augment the likelihood of arable land transitioning to forests and grasslands, and amplify the probability of dormant land converting to forests, grasslands, and arable lands. Furthermore, we curtail the likelihood of arable land converting to built-up areas and diminish the probability of forests converting to arable lands, grasslands, and built-up areas. Additionally, we mitigate the probability of grasslands converting to arable lands and built-up areas. The probabilities associated with the conversion among other land classifications remain unchanged.

4. Results

4.1. Land Use Characteristics of Zichang City

The proportional distribution of various land use types within Zichang City from 1980 to 2020 elucidates the structural attributes of land resources in the region (Figure 3,

Table A1. Land use change matrix of Zichang City from 1980 to 2000.

Land Types	Cropland	Forest Land	Grassland	Rural Settlement	Urban Land	Water Area	Area in 2000
Cropland	111,173.00	244.53	148.68	27.27	57.69	2.97	111,654.14
Forest land	81.90	20,766.30	0.36	0	7.29	16.47	20,872.32
Grassland	50.22	3632.58	102,679.00	10.44	0	29.79	106,402.03
Rural settlement	0.09	0	0	153.36	0	0	153.45
Urban land	0	0	0	0	104.76	0	104.76
Water area	0	0	20.97	0	0	237.78	258.75
Area in 1980	111,305.21	24,643.41	102,849.01	191.07	169.74	287.01	239,445.45

and

Table A2. Land use change matrix of Zichang City from 2000 to 2020.

Land Types	Cropland	Forest Land	Grassland	Rural Settlement	Urban Land	Water Area	Area in 2020
Cropland	85,854.80	16,872.10	8467.38	49.41	54.81	7.02	111,305.52
Forest land	413.19	23,872.80	342.00	4.05	7.11	4.32	24,643.47
Grassland	2425.77	4803.75	95,460.20	12.78	116.28	29.88	102,848.66
Rural settlement	8.10	1.26	5.40	176.31	0	0	191.07
Urban land	0.36	0.81	1.08	0	167.49	0	169.74
Water area	2.25	5.58	15.39	0	0	263.79	287.01
Area in 2000	88,704.47	45,556.30	104,291.45	242.55	345.69	305.01	239,445.47

). Over this temporal span, grassland has consistently dominated the land use landscape, maintaining an average coverage of approximately 43.65% of the total land area. Notably, the transition dynamics reveal significant trends: from 1980 to 2000, grassland primarily transitioned into forest land, while the subsequent two decades, 2000 to 2020, witnessed its conversion primarily into forest land and arable land, alongside concurrent transitions of arable land to grassland. Furthermore, arable land and forest land emerged as pivotal constituents undergoing notable transitions. Specifically, their average proportions over the three temporal points (1980, 2000, and 2020) hovered around 43.39% and 12.68%, respectively. During the period from 1980 to 2000, arable land exhibited marginal fluctuations, while forest land demonstrated encroachment upon grassland. Subsequently, from 2000 to 2020, a substantial portion of arable land transitioned into forest land and grassland, with a concurrent phenomenon of forest land encroachment on grassland.

Throughout the span of 40 years, the urban construction land area in Zichang City has experienced exponential growth, with respective urban construction land areas in 1980 (104.76 ha), 2000 (169.74 ha), and 2020 (345.69 ha) constituting 0.04%, 0.07%, and 0.14% of the total area of Zichang City (Figure 3, Table A1 and Table A2). In the initial two decades, arable land and forest land predominantly contributed to the expansion of urban construction land area, while in the subsequent two decades, grassland emerged as the primary source of expansion. Likewise, the transformation patterns of rural settlements mirrored those of urban construction land, depicting an increasing trend mainly sourced from arable land and grassland. Notably, the water area witnessed minimal growth over the 40-year period, with grassland, forest land, and arable land being its primary contributors.

4.2. Spatial–Temporal Evolution Pattern of Urban Expansion

The urban construction land in Zichang City experienced notable expansion from 1980 to 2020 (Figure 4). In 1980, Zichang’s urban area was situated at the junction of Wayaopu and Xiuyan Streets, to the east and west, respectively. Between 1980 and 2000, urban construction land expanded towards the west and south from its original location. From 2000 to 2020, Zichang’s urban construction land witnessed significant expansion, further extending to the north and south from its existing boundaries. Moreover, there were new additions of urban construction land in the southern part of Luanjiaping Street, as well as the northwestern and southeastern parts of Yujiaping Street.

Between 1980 and 2020, the fragmentation degree of urban construction land in Zichang City experienced a phase of decline followed by an ascent (

Table 3. Landscape pattern index of Zichang City from 1980 to 2020.

Primary Indicator	Secondary Indicator	1980	2000	2020
Density index	NP	3.00	3.00	10.00
Land use index	CA (ha)	104.76	169.74	345.69
Scale merit	LPI (%)	61.00	71.63	39.91
Shape index	LSI	2.64	2.62	5.07
Convergence and dispersion index	AI	95.00	96.17	93.32

). From 1980 to 2000, the number of patches (NP) in Zichang City remained stable, while both the patch area (CA) and the proportion of the largest patch index (LPI) to the landscape area expanded, indicative of the urban construction land’s expansion on its existing footprint. During this period, Zichang City’s landscape shape index (LSI) diminished, while the aggregation index (AI) increased, suggesting a gradual regularization of the urban construction land’s shape and a simultaneous enhancement of its aggregation. From 2000 to 2020, Zichang City’s CA increased concomitantly with NP, denoting an expansion of existing construction land alongside the development of new construction areas (Figure 4). Over this timeframe, Zichang City witnessed a steep decline in LPI, a significant increase in LSI, and a simultaneous decrease in AI, indicating that while urban construction land became more fragmented, its shape also became more irregular, and its degree of aggregation decreased.

4.3. Land Use Change Simulation and Future Multi-Scenario Prediction

4.3.1. Accuracy Verification

We validated the simulated land use results for Zichang City in 2020 against the actual land use data for the same year, yielding a Kappa coefficient of 0.88. This indicates that the simulation results satisfactorily meet the requirements for further simulation and prediction of urban expansion and land use change in Zichang City. It also suggests that the selected driving factors possess strong explanatory power for the changes in land use in Zichang City, thus enabling the simulation and prediction of future probability distributions of land use. Moreover, upon comparing the simulated land use results for Zichang City in 2020 with the actual land use patterns, it was observed that the simulated distribution of various land use types generally aligned well with reality, with differences mainly localized in specific areas. For instance, discrepancies between the current situation and the simulation were noted in certain regions, such as the western part of Xiuyan Street, the western part of Luanjiaping Street, and the central part of Yangjiayuanzi Town (Figure 5).

4.3.2. Multi-Scenario Simulation and Prediction

In the multi-scenario simulation and prediction, we projected the land use conditions in Zichang City for the year 2035 under various scenarios, and utilized land use transition matrices to calculate the area conversions of different land types from 2020 to 2035.

Under the scenario of natural development, the urban construction land, grassland, and woodland areas in Zichang City experienced increments of 159.81, 4852.7, and 1202.8 hectares, respectively (

Table 4. Land use change matrix (ha) from 2020 to 2035 under natural development scenario.

Land Types	Grassland	Urban Land	Cropland	Forest Land	Rural Settlement	Water Area	Area in 2020
Grassland	87,499.50	49.12	13,523.60	2947.17	28.52	27.81	104,075.72
Urban land	117.93	180.46	42.97	4.33	0	0	345.69
Cropland	18,275.40	260.24	65,615.60	4279.41	83.99	18.99	88,533.63
Forest land	2978.22	15.68	3051.21	39,416.20	8.39	17.79	45,487.49
Rural settlement	29.40	0	25.50	14.57	173.08	0	242.55
Water area	27.95	0	14.79	28.61	0	232.01	303.36
Area in 2035	108,928.40	505.50	82,273.67	46,690.29	293.98	296.60	238,988.44

). Additionally, reductions were observed in arable land, rural residential areas, and water bodies, decreasing by 6259.96, 9.38, and 6.76 hectares, respectively. Spatially, the expansion of urban construction land primarily encroached upon grassland, arable land, and woodland (260.24, 49.12, and 15.68 hectares, respectively). The expansion of urban land occurred predominantly in the Wabao and Xiuyan streets, with minor expansions occurring in the southern river valley areas of Zichang City (Figure 6).

In the urbanization development scenario, urban construction land, grassland, forest, and rural settlements expanded by 520.42, 4683.23, 1201.76, and 49.53 hectares, respectively. Arable land and water bodies decreased by 6448.68 and 6.36 hectares, respectively (

Table 5. Land use change matrix from 2020 to 2035 under urbanization development scenario.

Land Types	Grassland	Urban Land	Cropland	Forest Land	Rural Settlement	Water Area	Area in 2020
Grassland	87,473.00	112.81	13,486.50	2949.81	28.32	25.34	104,075.78
Urban land	117.43	181.06	42.87	4.33	0	0	345.69
Cropland	18,144.50	533.81	65,473.60	4277.70	82.19	21.88	88,533.68
Forest land	2967.66	35.80	3044.48	39,413.30	8.39	17.79	45,487.42
Rural settlement	28.47	2.63	24.07	14.30	173.08	0	242.55
Water area	27.95	0	13.66	29.74	0	232.01	303.36
Area in 2035	108,759.01	866.11	82,085.18	46,689.18	291.98	297.02	238,988.48

). Spatially, urban construction land primarily competed with arable land, grassland, and forest, with urban expansion occupying areas of 533.81, 112.81, and 35.80 hectares, respectively. Urban construction land expansion primarily occurred in the areas of Wayaobao Street, Luanjia Ping Street northeast, Anding Town northwest, and the river valley area of Zichang City (Figure 7). Notably, the phenomenon of urban expansion in the river valley area was more pronounced compared to the natural development scenario.

In the ecological protection scenario, the expansion of urban construction land, grassland, forest land, and rural residential areas amounted to 4.27, 11,152.33, 2009.37, and 49.43 hectares, respectively. Remarkably, under this scenario, urban expansion exhibits a reduced magnitude compared to both the natural development and urbanization scenarios. Additionally, there is a notable decrease in arable land and water area by 13,211.52 and 3.88 hectares, respectively (

Table 6. Land use change matrix under the ecological protection scenario from 2020 to 2035.

Land Types	Grassland	Urban Land	Cropland	Forest Land	Rural Settlement	Water Area	Area in 2020
Grassland	88,671.10	25.06	12,245.00	3080.25	28.90	25.41	104,075.72
Urban land	122.49	180.85	37.25	5.10	0	0	345.69
Cropland	23,056.40	140.17	60,324.90	4911.13	78.10	22.99	88,533.69
Forest land	3315.25	3.84	2692.32	39,449.30	7.67	19.07	45,487.45
Rural settlement	33.92	0.04	10.43	20.85	177.31	0	242.55
Water area	28.89	0	12.27	30.19	0	232.01	303.36
Area in 2035	115,228.05	349.96	75,322.17	47,496.82	291.98	299.48	238,988.46

). Spatially, urban construction land primarily competes with arable land, grassland, and forest land. Specifically, the area occupied by urban expansion in these three land types amounts to 533.81, 112.81, and 35.80 hectares, respectively. Urban expansion predominantly unfolds in the Wayaobao street. Notably, the pace of urban expansion is relatively subdued (Figure 8).

5. Discussion

5.1. Analysis of the Driving Forces Affecting the Evolution of Urban Pattern

5.1.1. Impact of Physical Geographical Factors on Urban Expansion

Zhang City’s natural geographical setting presents inherent challenges, characterized by rugged mountains, deep valleys, and severe soil erosion, factors that inherently impede urban development [42]. Nestled at the eastern terminus of the Hengshan Mountains within the hilly and gullied expanse of the Loess Plateau in northern Shaanxi, the city’s primary ridge delineates the watershed between the Xiuyan River and Jianyuchacha River. The northern branch ridge demarcates the boundary between the Dali River and Huaining River (referred to as the Jianyuchacha River within the city), while the southern branch ridge separates the upper reaches of the Yan River and Xiuyan River. Sloping from west to east, the watershed between Yingbangou and Gaotaigou extends southward, traversing the eastern frontier of Lijiacha Township before intersecting with the eastern boundaries of Anding Town and Siwan Township. Elevational disparities are notable, with the western reaches ranging from approximately 1400 m to 1562 m, contrasting with the eastern terrain spanning from about 930 to 1300 m. Notably, the Duncangudu precinct in Lijiacha Township boasts the highest elevation at 1562 m, while the riverbank locale of Majiabian Village registers the lowest point at 930 m [64]. As a result, urban construction land predominantly clusters around water bodies and the lower-altitude eastern expanses. Furthermore, the city’s landscape encompasses 5.60% of the total area as river valley terraces, punctuated by scattered small river valley basins, features that significantly influence urban genesis and the distribution dynamics of urban construction land.

5.1.2. Influence of Social Factors on Urban Expansion

Population factors play a predominant role among social factors, serving as the primary impetus driving urban land expansion [65]. Within the context of social development, all societal activities are rooted in human endeavors, and the progress of society significantly impacts the structure of land utilization. Consequently, population factors hold a paramount position within the realm of social factors. Since the establishment of the People’s Republic of China, Zichang City has witnessed a rapid surge in population. In 1949, the population stood at 68,800, which escalated to 177,300 by 1985 and further surged to 257,300 by the close of 2007. Over the course of the past 58 years, the population has burgeoned by a factor of 2.74. As of the end of 2022, the permanent resident population in Zichang City reached 215,300 [42]. The swift population growth inevitably results in an increased demand for urban construction land. Consequently, sans consideration of other influencing factors, population growth precipitates the expansion of residential areas, rural settlements, and cultivated land areas, thereby rendering grassland, woodland, and unused land as the principal sources for expansion for both.

5.1.3. Impact of Economic Factors on Urban Expansion

Economic factors constitute the cornerstone for the expansion of urban construction land, exerting influence over the trajectory of land use change and the efficacy of land development [66]. Thus, urban expansion hinges on the impetus provided by economic growth. Since the dawn of reform and opening-up, Zichang County has witnessed a remarkable surge in economic prowess. Its GDP surged from CNY 19.96 million in 1978 to CNY 3.395 billion in 2007, marking a staggering increase of over 170 times, with an impressive average annual growth rate of 15.4%. Notably, during the “Tenth Five-Year Plan” period, the GDP boasted an average annual growth rate of 16.4%. Concurrently, per capita GDP soared from CNY 126 in 1978 to CNY 136,020 in 2007, representing a remarkable 104-fold increase [42]. The vigorous economic development of Zichang City not only propels further urban development and expansion but also spurs residents’ enthusiasm for constructing and purchasing homes. The ongoing trend of urban development and construction, coupled with the gradual assimilation of urban villages into the existing urban fabric, constitutes a pivotal factor driving the expansion of urban construction land. Moreover, since the 1990s, the Zichang City government has formulated the economic development strategy of “prioritizing industry, fostering high-quality and efficient agriculture, and nurturing the tertiary industry”, thereby reshaping the economic landscape and catalyzing progress across various sectors. Initiatives such as the introduction of construction projects from Shandong, the establishment of 13 enterprises, and the relaxation of land approval policies have fueled economic growth in Zichang City. Consequently, since the turn of the millennium, alongside the rapid economic ascent of Zichang City, the urban area has experienced an equally swift expansion.

In recent years, with Yanchuan City designated as the sub-central city of Shaanxi province and Zichang City undergoing a concerted effort to optimize its industrial structure, urban expansion in Zichang City has been further propelled by a confluence of external and internal factors. Externally, the designation of Yanchuan City as Shaanxi province’s sub-central city has exerted a constructive influence on Zichang City’s urban expansion dynamics. The ample resources and robust economic prowess of Yanchuan City provide a solid foundation for Zichang City, bolstered further by its comprehensive infrastructure, industrial development, and favorable policies. This radiating effect from Yanchuan City has catalyzed Zichang City’s rapid development, infusing renewed vitality into its economic and social fabric. Internally, Zichang City has prioritized the refinement of its industrial landscape in recent years. Emblematic of this effort is the establishment of energy and chemical industry parks, complemented by initiatives focusing on the integrated utilization of coal, salt, and gas, alongside the development of sophisticated chemical recycling and agricultural processing hubs. Simultaneously, leveraging its rich cultural and touristic assets, Zichang City has fostered the growth of its tertiary sector, spearheaded by red cultural tourism, thereby accelerating the pace of tourism infrastructure development. Positioned as a livable city primarily emphasizing tourism, commerce, and residential functions within the Yellow Earth Plateau, the Zichang district strategically harnesses its surrounding industrial zones to enhance its residential amenities, thus attracting a burgeoning industrial workforce. Moreover, capitalizing on its diverse cultural heritage, Zichang City fosters the growth of commercial and service sectors alongside cultural tourism, thereby laying the groundwork for population aggregation and augmenting urban functionality, infrastructure quality, and overall urban–rural integration across the municipality. These proactive measures underscore the intrinsic drivers fueling Zichang City’s urban expansion trajectory.

5.1.4. Influence of Policy Factors on Urban Expansion

Zichang City has a longstanding history of grappling with severe soil erosion and a delicate ecological balance, factors that have significantly impeded the region’s socioeconomic progress. In response, following the initiation of the reform and opening-up policies, both the central government and local authorities have rolled out a series of strategic measures aimed at mitigating soil erosion and other natural calamities, particularly at the watershed level [64]. The year 1998 marked a pivotal moment as Zichang City was earmarked as a focal county for national ecological and environmental construction endeavors. Furthermore, propelled by the enactment of the Western Development Strategy and the introduction of the Grain for Green Program in 1999, Zichang City earned distinction as a pioneering demonstration county for the nationwide Grain for Green initiative in 2000 [42]. Under the resolute influence of these policy dynamics, the expansion of urban precincts within Zichang City has been judiciously restrained, predominantly encroaching upon arable lands. Moreover, the implementation of the Grain for Green Program has precipitated the conversion of select arable lands into verdant pastures and lush forested expanses, while certain grasslands have undergone a metamorphosis into forested domains. Notwithstanding the dynamic land transformations spurred by these policies, there has been no marked proliferation of forested or grassy territories. Instead, a harmonious equilibrium has been maintained among arable lands, forested expanses, and grassy terrains across Zichang City. Thus, from 1980 to 2000, Zichang City navigated a delicate balance between advancing urbanization and safeguarding ecological integrity.

However, since the 1990s, Zichang City has grappled with inadequate urban infrastructure and a disproportionately small per capita area, leading to the gradual emergence of urban dilapidation [64]. Consequently, since the onset of the 21st century, Zichang City has intensified its efforts in urban revitalization and renewal, significantly propelling urban expansion. For instance, the city has vigorously implemented policies aimed at rejuvenating old urban areas, involving the demolition of dilapidated structures in the old city center and the development of new areas such as Qijiawan Farmer Street, Changxing Street, and Guang’an Street. Additionally, new residential complexes like Ximenping and Qijiawan, along with commercial thoroughfares like Yingbin Road, have been erected, with over 120 mixed-use buildings towering above. By the end of 2020, the urban area had expanded from 104.76 hectares in 1980 to 345.69 hectares [42]. Furthermore, Zichang City has consistently pursued municipal welfare policies, continuously investing in essential infrastructure, county hospitals, schools, and other supporting facilities. This steadfast commitment has also played a pivotal role in fueling the rapid expansion of urban construction land in Zichang City since 2000.

5.2. Analysis of Urban Pattern Evolution under Different Scenarios

In the scenario of natural development, Zichang City’s land use characteristics and urban construction land expansion follow the developmental patterns observed from 2005 to 2020. With population growth and socioeconomic advancement, the demand for housing purchases continues to rise among residents, thereby expanding residential area footprints. Consequently, urban construction land exhibits a continual trend of expansion. Moreover, as living standards improve, residents increasingly pursue larger residential units, leading to the enlargement of residential areas. Simultaneously, the addition or expansion of cultural and recreational facilities, commercial zones, municipal infrastructure, and urban parks serves as another significant factor driving urban construction land expansion.

In the context of urbanization, the scale of urban construction land surpasses that under the natural development scenario. Within the urbanization model, Zichang City prioritizes economic growth and urbanization advancement, making urban construction land expansion the direct manifestation of urbanization. Additionally, according to the “Zichang City Land Spatial Plan 2020–2035”, Zichang City is designated as the northern sub-center of Yan’an City. Economically, Zichang City aims to further establish Yan’an’s new development pattern, foster new growth engines, promote high-quality economic development, and become the economic sub-center of northern Yan’an [42]. Culturally, Zichang City seeks to enhance its urban cultural brand, integrate with Yan’an culture, and collaborate to develop key national red tourism areas, thereby boosting the cultural tourism industry’s growth. In terms of technology, Zichang City aims to establish innovation and entrepreneurship service platforms, facilitate deep integration between innovation chains and industrial chains, and create a highland for innovation and entrepreneurship in the neighboring Yan’an-Yulin region. Regarding urban construction, Zichang City plans to further construct high-level public service facilities and infrastructure, create high-quality living environments, build a park city, and enhance residents’ sense of happiness and well-being. These policies serve as significant drivers of urban construction land expansion.

Under the ecological protection scenario, the urban construction land area in Zichang City is smaller compared to that under the natural protection scenario. In this context, Zichang City emphasizes the relationship between ecological conservation and economic development. According to the Zichang City Land Spatial Plan, Zichang City is committed to creating an overall ecological security pattern of “one screen, two zones, four corridors, and multiple points” [28]. The “one screen” refers to the sandstorm protection screen at the southern foot of Baiyu Mountain. The “two zones” include the Qingshui–Huaining River water conservation zone and the loess hilly gully soil erosion control zone. The “four corridors” encompass the Xiuyan River, Jianyuchacha River, Nanhe River, and Yongping River ecological corridors. The “multiple points” include ecological protection focuses such as the Zhongshan Chuan Reservoir, Hongshimao Reservoir, Wujia Wan Reservoir, Weijiacha Reservoir, and Yanjia Gou Reservoir. Furthermore, Zichang City emphasizes the conservation and utilization of natural resources, especially forest and grassland resources. Adhering to the principle of the “overall stabilization of the ecological protection red line”, Zichang City ensures that the adjustment of the ecological protection red line delineation scheme is optimized based on regulations while ensuring no significant impact on ecological functions. These policies significantly constrain the disorderly and sprawling expansion of urban construction land in Zichang City [56] under the ecological protection scenario, resulting in less urban construction land expansion.

5.3. Comparison with Other Studies

This study employs the CLUE-S model to conduct multi-scenario simulations and predictions for Zichang City. The advantage of this model lies in its comprehensive consideration of both natural geographical elements and socio-economic development factors, thereby achieving higher simulation accuracy and generating more realistic land use patterns. However, the urban expansion of Zichang City is influenced and constrained by various factors, including terrain, ecology, socio-economics, and local policies. Among these, local regional policies play a particularly crucial role in shaping the speed and pattern of urban spatial expansion. Although the CLUE-S model considers key influencing factors such as elevation, slope, aspect, GDP, population, and transportation, it has limitations in the selection of influencing factors due to the lack of consideration for natural conditions like climate, precipitation, and soil [67,68].

Nevertheless, building upon previous research on urban expansion, this study introduces landscape pattern indices to comprehensively analyze urban scale, form, and shape. By integrating Zichang City’s territorial spatial planning policies, this study conducts multi-scenario simulations and predictions of future urban land use, aiming to provide planners with a more scientific, comprehensive perspective. Overall, while this study has made progress in considering influencing factors and model accuracy, it still needs to further consider the impacts of more natural condition factors in future research. Integration with local policies and planning is also necessary to enhance the accuracy and reliability of the model, thereby providing better scientific foundations for urban planning and decision-making.

5.4. Policy Implications

In the context of Zichang City’s distinctive landscape characterized by the hills and gullies of the Loess Plateau, it is imperative to recognize its profound ecological significance. Consequently, as the municipality progresses towards a novel phase of urbanization, it becomes paramount to meticulously navigate the delicate interplay between urban expansion and ecological preservation [69]. Moreover, Zichang City grapples with inherent challenges stemming from its resource limitations, rugged topography, sparse vegetative cover, meager forest density, pervasive soil erosion, and recurrent natural calamities. Hence, charting the course for Zichang City’s future entails a nuanced approach that transcends mere economic growth, placing equal emphasis on harmonizing economic advancement with the imperative of ecological conservation. Therefore, envisaging scenarios for urban evolution should be rooted in prudence, refraining from indiscriminate expansion of urban infrastructure, while strategies for ecological safeguarding should not exclusively prioritize the enlargement of arable lands, forests, grasslands, and aquatic habitats.

In the forthcoming urbanization trajectory of Zichang City, the optimization of construction land utilization hinges upon a meticulous blend of stringent control over land increments, activation of existing stock, and the relentless pursuit of qualitative enhancements [70]. This entails rigorously adhering to prescribed urban development boundaries and construction land parameters to streamline development activities while revitalizing dormant land resources through strategic re-development initiatives. Moreover, fostering the rejuvenation of dilapidated urban precincts stands paramount, focusing on upgrading infrastructural inadequacies, ameliorating living standards, and aligning urban functionality with contemporary imperatives. Concurrently, endeavors to steer unsuitable industries away from urban confines and galvanize the metamorphosis of outdated urban clusters constitute pivotal measures for enhancing urban resilience and sustainability [71].

In the domain of ecological conservation, Zichang City’s trajectory is underscored by a steadfast commitment to the ethos of a harmonious coexistence between humanity and nature. In this vein, concerted efforts are mandated to execute transformative endeavors such as erosion control, ecosystem preservation in watershed areas, green corridor establishment, and ecological rehabilitation of historically degraded mining sites [72]. Augmenting the ecological fabric of urban landscapes, bolstering the environmental vitality of agricultural domains, and strategically allocating resources towards ecological restoration endeavors aimed at fortifying soil and water conservation, nurturing biodiversity, and safeguarding ecological equilibrium are pivotal imperatives. Notably, such initiatives are indispensable in delineating and fortifying the natural ecological thresholds that encapsulate Zichang City’s ecological integrity [73].

In charting the trajectory of future development, the imperative of aligning urban expansion within the broader framework of a “social–economic–ecological” composite system cannot be overstated. Thus, the delineation of urban development boundaries, stringent safeguards for ecological precincts, prudent management of arable lands and forests, and proactive pursuit of comprehensive ecological revitalization projects such as soil and water conservation and vegetative regeneration in resource exploitation zones remain paramount. Additionally, synergizing incentives for ecological conservation with initiatives such as ecological migration programs to catalyze ecological renaissance, establishment of ecological sanctuaries, judicious urban planning, and the realization of sustainable urban development underscore the ethos of Zichang City’s evolution towards ecological equilibrium and societal prosperity [74].

In light of Zichang’s distinctive geographical and ecological features, the urban development of the city encounters a myriad of challenges. Achieving systematic progression in this regional urban setting necessitates a holistic integration of socio-economic and environmental exigencies, while striving for equilibrium between the two. Primarily, addressing the constraints imposed by Zichang’s topographical intricacies demands meticulous scientific delineation and judicious exploitation of land assets. Techniques such as topographic sculpting, ravine infilling, and elevation normalization serve to repurpose latent land resources into viable construction plots, thereby augmenting the urban development canvas. Concurrently, upholding an ecological primacy ethos is paramount to ensuring that expansion endeavors remain non-invasive to the surrounding ecosystem, thereby averting manifestations of soil erosion and allied concerns. Secondarily, concerted efforts must be directed towards the ecological rejuvenation and stewardship of Zichang. In light of its ecological fragility, an intensified approach to afforestation initiatives, coupled with a nuanced selection of arboreal species and enhanced afforestation survivability rates, is imperative. Additionally, bolstering soil and water conservation endeavors, with a particular emphasis on the fortification of silt dam infrastructures, serves as a linchpin in consolidating governance achievements and fostering ecological amelioration. On the policy front, heightened governmental fiscal bolstering, coupled with a synergistic amalgamation of departmental resources, is indispensable in fostering a cohesive front. Policy prescriptions should incentivize the active engagement of social capital in ecological stewardship endeavors and urban expansion initiatives, thereby fostering mutually beneficial outcomes. Furthermore, the facilitation and standardization of farmer land transference initiatives serve to optimize the allocation of agricultural production resources and operational elements. In navigating the labyrinth of real-world challenges, due emphasis must be accorded to technological innovation and human capital cultivation. By leveraging cutting-edge technological apparatuses and methodologies, efficiencies and efficacies within the realms of urban construction and ecological governance can be significantly augmented. Concurrently, the grooming of a cadre of technically adept and administratively savvy professionals acts as an intellectual bulwark in fortifying Zichang’s urban expansion aspirations. In summation, the realization of an orchestrated developmental trajectory and urban expansion paradigm in Zichang necessitates a nuanced calibration of multifaceted parameters. Through the prism of scientific planning, ecological stewardship, policy prescriptions, technological innovations, and human capital enrichment endeavors, the gradual resolution of real-world predicaments is envisaged, thus ensuring a harmonious amalgamation of socio-economic imperatives and environmental requisites.

6. Conclusions

During the period from 1980 to 2020, Zichang City experienced a continual expansion of its urban footprint, witnessing an increase in urban construction land area by approximately 240.93 hectares. Specifically, from 1980 to 2000, the urban construction land area expanded by 64.98 hectares, demonstrating a relatively stable growth trend. However, from 2000 to 2020, the urban construction land area experienced a rapid and exponential surge, expanding by 175.95 hectares, signifying a markedly accelerated pace of growth. Throughout this timeframe, the fragmentation level of urban construction land exhibited a pattern of initial decline followed by an upward trajectory, with the year 2000 marking a pivotal juncture as urban construction land transitioned from orderly to disorderly development.

In anticipation of future developmental trajectories, three scenarios were envisioned: natural development, urbanization, and ecological conservation. Among these, the urbanization scenario depicted the most extensive urban expansion area, reaching 520.42 hectares, followed by the natural development scenario at 159.81 hectares, and the ecological conservation scenario with the smallest urban expansion area of only 4.27 hectares. Tailored policies and measures should be formulated based on the simulated results of different scenarios. Under the urbanization scenario, there is an urgent imperative to bolster land use control, regulate urban expansion, and mitigate the perils of resource depletion and environmental degradation stemming from excessive development. In the natural development scenario, efforts should concentrate on maintaining a steady growth trajectory of urban construction land while prioritizing enhancements in land use efficiency and the quality of urban development. Conversely, under the ecological conservation scenario, stringent controls on urban expansion are imperative, with priority given to the protection and restoration of ecological environments, fostering synergistic development between ecology and urbanization. By harnessing scientifically informed simulations and forecasts of urban and regional land changes, pivotal insights can be gleaned to inform the planning and development of Zichang City’s future. This comprehensive approach aims to achieve coordinated progress in land utilization, economic growth, and ecological preservation, thereby advancing the city’s trajectory towards sustainable development.