Research on the Development of Deserticulture and Desertification Land Use Benefits Evaluation in Ordos City

Abstract

The regional economy of desertification area plays a pivotal role in the land economy. Therefore, the rational development of deserticulture is of paramount significance to the economic, social, and ecological benefits of sand areas in western China. In this paper, we constructed a comprehensive evaluation index system for the development of deserticulture and the benefits of desertification land use. The entropy method was used to calculate the weight of each index, which was then used to evaluate the level of development in Ordos City from 2010 to 2017. Additionally, we analyzed the coupling relationship between these two subsystems. The results indicate a gradual increase in the input, output, and environmental evaluation value of deserticulture development, as well as the economic, social, and ecological benefits of desertification land use from 2010 to 2017 in Ordos City. Additionally, there has been an overall improvement in the comprehensive evaluation value of both systems. The level of coupling and coordinated development between deserticulture development and desertification land use benefits has been further enhanced, with a significant increase in the degree of subsystem coordination. Initially, there was serious internal and external developmental discoordination in the system, which gradually improved to an overall state of barely coordinated.

1. Introduction

With unique resource advantages and broad development space, priority should be given to economic development and ecological environment construction in the process of developing the deserticulture in sandy areas due to the relatively fragile ecological environment. With the increasingly severe global desertification situation, there are more studies on desertification, desert agriculture, desert photovoltaic and desert aquaculture abroad, but there are few overall discussions on “deserticulture”; the concept of deserticulture has not been clearly put forward [1,2,3]. The development and utilization of the desert mainly rely on the water, soil, light, and heat resources in the desert area, combined with the achievements of modern biological science, water conservancy engineering, and computing automatic control technology to develop knowledge-intensive industries [4,5]. As early as the 18th century, researchers began to try to use desert resources. In 1794, the United States promulgated land laws, which authorized the sale of state-owned desertification land to individuals, so that the development of the entire western desert on the basis of a land market economy; at the end of the 19th century, the United States Congress tried to encourage the immigration desert policy, exchange desert economic property rights for desert ecological construction, and encourage the development of “environmental control agriculture” [6]; in 1959, Israel, which has always been known for its lack of water resources, passed legislation, which clearly stipulates that the state shall have full control over water resources, and successfully created “marginal water resources” through the combination of science and technology and policy regulation, and developed knowledge-intensive agriculture [7]; in the 1990s, Australia developed a “desert knowledge economy”, combining desertification control and wealth [8].

Since Qian Xuesen first proposed the concept of “Deserticulture” in 1984 [9], Chinese researchers have expanded and extended its definition and application [10], deepening our understanding of both theory and practice. Deserticulture, encompassing both agricultural and non-agricultural sectors, refers to the utilization of desertified or potentially desertified land in arid and semi-arid regions. It capitalizes on the vast land resources and abundant solar radiation available in sandy areas. With ecological improvement as its foundation, natural resources as its industrial base, scientific and technological advancements as its support, and sustainable development as its core objective, the deserticulture aims to foster the unified development of economic, ecological, and social benefits within knowledge-intensive sectors. Additionally, drawing on advanced concepts of ecological restoration to drive the development of green industries, a series of comprehensive projects have been implemented in China’s northern sandy regions to combat desertification [11]. While achieving the ecological benefits of desertification prevention, there has been a coordinated effort to also realize economic and social benefits, gradually transforming from pure ecological desertification prevention to an approach that integrates ecological and economic considerations. This strengthens the relationship between desertification prevention efforts and the development of deserticulture [12]. The development of deserticulture involves various aspects, such as resource and environmental conditions, regional spatial layout strategy, technology research and development, enterprise market management, among others [13,14]. However, there is limited research on evaluating the relationship between the level of deserticulture development and land use benefits in areas affected by desertification.

The assessment of deserticulture development serves as a crucial indicator for gauging the regional deserticulture’s level of progress, with the aim of analyzing current conditions and trends in core driving factors that influence its growth. Land use benefits evaluation is a primary approach to reflect the regional land utilization level, which can scientifically and accurately assess social, economic, and ecological benefits in order to explore the extent of regional land use [15]. The coupling relationship refers to the interdependence between things that act on each other. Under the coordination of economic, social, and ecological benefits, stable land in sandy areas provides an input–output environment for deserticulture. Meanwhile, the stable development of the deserticulture can also enhance the comprehensive benefits of desertification land use. Therefore, in terms of perspective, the two are considered to have a coupling relationship, and a coupling correlation analysis is conducted [16,17].

The establishment of an evaluation system for the development of the deserticulture and land utilization benefits serves as a valuable tool to monitor and assess the efficient utilization of land resources by the deserticulture. It enables the identification of existing issues and potential areas for improvement, preventing excessive exploitation and environmental degradation. By ensuring sustainable practices within the deserticulture, it optimizes land utilization structure, enhances land utilization efficiency, and maximizes the effective utilization of resources. This, in turn, promotes the sustainable development of the deserticulture. Through the evaluation of the interrelationship between the development of the deserticulture and land utilization benefits, an analysis of their coupled and coordinated dynamics can provide governments, businesses, and stakeholders with scientific evidence and valuable insights. It supports decision-making processes by suggesting rational management and planning measures, reducing investment risks, and enhancing the scientific accuracy of decisions. Moreover, it offers guidance for industrial technological upgrades and innovation, elevating the competitiveness of deserticulture enterprises and increasing the value-add of deserticulture commodities. In summary, the establishment of an evaluation system for the deserticulture’s development and land utilization benefits not only facilitates effective monitoring and assessment but also offers a scientific foundation for decision-making, promoting sustainable practices, and driving the deserticulture toward enhanced competitiveness and increased product value.

This study focuses on the analysis of the economic, social, and ecological advantages associated with the development of desertified land and sand industries in Ordos City. Its aim is to offer unbiased evidence and support for evaluating the benefits derived from the utilization of desertified land through the implementation of deserticulture practices. The ultimate goal is to foster a coordinated and sustainable approach toward comprehensive land utilization [18]. In the investigation of the economic, social, and ecological aspects, this study delves into the multifaceted benefits arising from the development of desertified land. By exploring the potential of deserticulture, it sheds light on the economic opportunities that can be harnessed, such as the generation of income, employment, and market expansion. Furthermore, it examines the social dimensions, including the improvement of local livelihoods, the promotion of cultural heritage, and the enhancement of community well-being. At the same time, the study evaluates the ecological benefits associated with deserticulture, such as land restoration, biodiversity conservation, and the mitigation of desertification. The findings of this research underscore the importance of adopting a comprehensive approach toward land utilization, one that incorporates economic, social, and ecological considerations. By effectively harnessing the potential of desertified land through sustainable practices, Ordos City can unlock various benefits, creating a positive and harmonious relationship between economic development, social progress, and ecological preservation. These findings provide valuable insights for policymakers, stakeholders, and researchers, facilitating informed decision-making and guiding the formulation of strategies for sustainable development.

In summary, this study not only highlights the advantages of developing desertified land and sand industries in Ordos City but also emphasizes the need for a balanced and integrated approach that addresses economic, social, and ecological aspects. By utilizing deserticulture as a means of comprehensive land utilization, the region can realize its potential for economic growth, social well-being, and environmental conservation, contributing to a sustainable and prosperous future.

2. Materials and Methods

2.1. Study Area

As is shown in Figure 1, Ordos City is situated within the central region of the Ordos Plateau, encompassed by multiple Yellow River bays on its western, northern, and eastern perimeters. The total land area of Ordos City is 8.68 million hectares, with the sand area encompassing both the Mu Us Desert and Hobq Desert, constituting nearly half of the entire region. The topography exhibits a high elevation at its center, with lower elevations to the north and south, while the west boasts higher terrain than that of the east; altitudes range from 800 to around 1500 m. The western portion of this territory comprises a barren high plain whereas the eastern section features hilly terrain replete with loess deposits. It is bounded by the east–west uplift erosion zone of the Ordos Plateau, with the northern part being the Hobq Desert distributed along the southern bank of the Yellow River, and the southern part being the main body of the Mu Us sandy land [19]. This area belongs to a typical temperate continental climate, which transits from an arid desert climate to a semi-arid grassland climate from west to east. The region is distinguished by intense solar radiation, abundant solar and thermal resources, a brief frost-free period, aridity, and scant precipitation. Annual sunshine duration reaches 3009 h with an annual sunshine percentage of 67.8%, while the average annual total solar radiation amounts to 142 kcal/cm². The mean annual temperature stands at 6.6 °C with an annual temperature range of 33.3 °C; the active accumulated temperature ranges from 2800 °C to 3120 °C, and the frost-free period lasts for approximately 150 days [20]. The average annual precipitation ranges from 192 to around 400 mm, increasing in an eastward direction. Prevailing northwest winds blow through the city at an average speed of 3.0 ms⁻¹ to 4.3 ms⁻¹ over time, with a historical maximum wind speed of 28.7 ms⁻¹ recorded within the city limits. The zonal soils found in this region run from southeast to northwest and include chestnut soil, brown calcium soil, gray calcium soil, and gray desert soil; non-zonal soils consist of sandy soil, coarse bone soil, saline soil, and swampy terrain. The vegetation in Ordos City is predominantly xerophytic and sandy shrubs, with a landscape that transitions from steppe to desert grassland and finally to steppe desert as one travels from southeast to northwest. The city covers an area of 86,881.6 square kilometers and is divided into nine districts. As of 2020, the permanent population was 2.1536 million, while the total regional GDP reached RMB 353.366 billion. The added value structure of the three industries accounted for 3.8%, 56.8%, and 39.4%, respectively [21].

With the promulgation of national and local environmental protection policies, as well as the implementation of key engineering and technical measures for desertification control, Ordos City has gradually established a pattern of continuous promotion of national greening, sustained growth in total forest and grass resources, ongoing improvement in habitat conditions, and persistent strengthening of forest and grass industry management. This provides stable assurances and ample opportunities for the realization of “ecological industrialization” and “industrial ecology”, as well as the coordinated development of desertification control and poverty alleviation. Over the past 30 years, guided by deserticulture theory and supported by relevant policies, Ordos City has integrated high-tech achievements to enhance light and heat resource utilization in sandy areas. As a result, it has established a primary deserticulture that primarily focuses on water-saving facility agriculture, forest and grass economy, livestock breeding, and algae cultivation. The secondary deserticulture was established to focus on the advanced processing of raw materials from the primary deserticulture, as well as the intermediate processed products generated by this sector. Lastly, a tertiary deserticulture was developed with an emphasis on providing ecotourism services.

2.2. Methods

2.2.1. Evaluation Index System

This study is based on the development and characteristics of the deserticulture and desertification land use in Ordos City, with reference to comprehensive evaluation of land use benefits, an evaluation index system for the applicability of ecological industry technology in sandy areas, as well as a comprehensive evaluation of China’s ecological civilization. The study of deserticulture management models [22], the national forestry competitiveness evaluation index system [23], and the evaluation index systems for sustainable land use and industrial development at home and abroad [24,25] was conducted. A comprehensive evaluation index system was established for assessing the development level of the deserticulture and the utilization benefits of desertification land. The system was based on input, output, environmental, and economic benefits, social benefits, and ecological benefits perspectives. Each evaluation index was comprised of 12 indicators that were classified as positive or negative (+/−). Positive indicators referred to the indicators in an indicator system that represented a positive effect or benefit, where a higher value of the indicator indicated a better evaluation. By contrast, negative indicators, also known as inverse indicators, represented a weakening effect or a desirable outcome where a lower value of the indicator was considered better in the evaluation within the indicator system, as demonstrated in

Table 1. Evaluation index system for the development level of deserticulture.

Target Layer (O)	Criterion Layer (P)	Indicator Layer (Q)	Unit	Indicator Property
Deserticulture Development (O)	Deserticulture Investment (P1)	Deserticulture total assets (Q1)	100 million yuan	+
		Ratio of deserticulture output value to GDP (Q2)	%	+
		Total output value of deserticulture enterprises (Q3)	10,000 yuan	+
		Enterprise’s funds for purchasing raw materials (Q4)	10,000 yuan	+
	Output of Deserticulture (P2)	Annual per capita income increases in deserticulture/disposable income of farmers (Q5)	%	+
		Enterprise sales revenue (Q6)	10,000 yuan	+
		Number of farmers and herdsmen driven by the enterprise annually (Q7)	person	+
		Enterprise driven by per capita income increase (Q8)	yuan	+
	Deserticulture Development Environment (P3)	Fixed investment in agriculture, Forestry, animal husbandry, and fisheries (Q9)	100 million yuan	+
		Total retail sales of social consumer goods (Q10)	100 million yuan	+
		Ending balance of various loans from financial institutions (Q11)	100 million yuan	+
		Tourism revenue (Q12)	100 million yuan	+

“+” represents a positive indicator.

and

Table 2. Index system for evaluating the benefits of desertification land use.

Target Layer (A)	Criterion Layer (B)	Indicator Layer (C)	Unit	Indicator Property
Desertification land use Benefit (A)	Economic Benefit (B1)	GDP per unit area (C1)	10,000 yuan/km2	+
		Public finance budget revenue per unit area (C2)	10,000 yuan/km2	+
		Per capita disposable income of rural residents (C3)	yuan	+
		Total output value of agriculture, forestry, animal husbandry, fishing, and service industries (C4)	100 million yuan	+
	Social benefits (B2)	Urban–rural income gap index (C5)	%	−
		Total area of raw material forest (C6)	10,000 km2	+
		Highway network density (C7)	km/100 km2	+
		Engel’s coefficient (C8)	%	−
	Ecological benefits (B3)	Shrub area (C9)	10,000 km2	+
		Nature reserve area/total Area (C10)	%	+
		Forest coverage rate (C11)	%	+
		Number of days per year exceeding the onset of sandstorms (C12)	day	−

“+” represents a positive indicator. “−” represents a negative indicator.

[26].

(1)

Deserticulture Investment Layer (P1):

Deserticulture investment refers to the financial investment by the government and enterprises to promote the development of the regional deserticulture. Taking into account the specific situation and data availability in Ordos City, 4 indicators, including namely total assets of the deserticulture, deserticulture output/GDP, total output of deserticulture enterprises, and funds allocated by enterprises for raw material acquisition, were selected as the indicators for the deserticulture input layer.

Deserticulture total assets (Q1): This indicator includes fixed assets and current assets, reflecting the corresponding material foundation and financial reserves owned and controlled by the deserticulture. A higher value indicates a more solid financial foundation for deserticulture development in the region and a higher evaluation value for deserticulture investment.

Ratio of deserticulture output value to GDP (Q2): This indicator reflects the level of attention given by the government and enterprises to the development of the deserticulture in the region and the proportion of the deserticulture in the national economy. A higher value indicates a higher level of attention to deserticulture development in the study area and a higher evaluation value for deserticulture investment. The calculation formula is deserticulture output/GDP × 100%.

Total output value of deserticulture enterprises (Q3): This indicator reflects the productivity, economic vitality, and adequacy of funds available for the next round of investment in deserticulture enterprises. A larger value indicates higher production enthusiasm of deserticulture enterprises in the region and a more efficient fund operation system.

Enterprise’s funds for purchasing raw materials (Q4): This indicator reflects the purchasing power of enterprises for relevant raw materials in the regional deserticulture development. It is the most direct investment in deserticulture development. A larger value indicates higher investment in deserticulture development.

(2)

Output of Deserticulture (P2):

Deserticulture output primarily refers to the economic and social benefits generated, representing the tangible results of deserticulture development. The following four indicators are selected as the deserticulture output indicators:

Annual per capita income increases in deserticulture/disposable income of farmers (Q5): This indicator reflects the contribution of deserticulture income to farmers’ overall income. A higher value indicates a greater proportion of income derived from the deserticulture, demonstrating the significant role of deserticulture development in improving farmers’ livelihoods. The calculation formula is (annual per capita income from the deserticulture/disposable income of farmers) × 100%.

Enterprise sales revenue (Q6): This indicator reflects the contribution of deserticulture income to farmers’ overall income. A higher value indicates a greater proportion of income derived from the deserticulture, demonstrating the significant role of deserticulture development in improving farmers’ livelihoods. The calculation formula is (annual per capita income from the deserticulture/disposable income of farmers) × 100%.

Number of farmers and herdsmen driven by the enterprise annually (Q7): This indicator reflects the population of farmers and herdsmen engaged in deserticulture activities under the guidance and influence of enterprises. A higher value indicates a greater number of individuals benefitting from employment opportunities provided by the deserticulture. It demonstrates the positive impact of the deserticulture on employment and economic development in the region.

Enterprise driven by per capita income increase (Q8): This indicator measures the growth in individual income resulting from the leadership and support of deserticulture enterprises. A higher value indicates a more significant improvement in income levels due to the positive effects of deserticulture development.

(3)

Deserticulture Development Environment (P3):

Deserticulture development environment refers to the sum of several factors that significantly influence the progress of deserticulture development. The following four indicators are selected as the deserticulture input indicators:

Fixed investment in agriculture, forestry, animal husbandry, and fisheries (Q9): This indicator reflects the level of government financial investment in production and construction projects, as well as related equipment and machinery, in various industries, including the deserticulture.

Total retail sales of social consumer goods (Q10): This indicator reflects the level of consumption of various products, including deserticulture products, by the entire society. A larger value indicates a better sales environment for deserticulture products and higher income levels for deserticulture enterprises, thereby creating a more favorable development environment for the deserticulture in the region.

Ending balance of various loans from financial institutions (Q11): This indicator reflects the quality of the regional loan financing environment and the scale of financial capital. A higher value indicates stronger support from financial institutions for deserticulture development, a more favorable credit structure, and a better development environment for the deserticulture.

Tourism revenue (Q12): This indicator reflects the richness of tourism resources, including desert tourism, the enthusiasm of the population, and the ability to transform tourism resources into actual income in the region. A higher value indicates greater popularity of desert tourism in the area, indicating a better development environment for the tertiary deserticulture.

(4)

Economic Benefits (B1):

Land use economic benefits refer to the value of effective products and services obtained from the input of land per unit area. By studying the economic benefits of land use, they can provide a basis for optimizing the layout and rational utilization of land resources and achieve sustainable land resource utilization. The following four indicators are selected as the indicators for land use economic benefits:

GDP per unit area (C1): This indicator reflects the value of goods and services produced per unit area in the region. A higher value indicates a higher level of economic development and economic efficiency in the area. The formula for calculation is Gross domestic product (GDP)/Administrative area land area.

Public finance budget revenue per unit area (C2): This indicator reflects the quality of the economic operation mechanism per unit area in the region. A higher value indicates higher economic efficiency of land use in the area. The formula for calculation is Annual public budget revenue/Administrative area land area.

Per capita disposable income of rural residents (C3): This indicator reflects the living standards of rural residents in the region. A higher value indicates higher income for farmers and higher land use efficiency.

Total output value of agriculture, forestry, animal husbandry, fishing, and service industries (C4): This indicator reflects the size of the primary and tertiary industries in the region and is an important indicator of regional economic level. A higher value indicates higher economic efficiency of land use in the area.

(5)

Social benefits (B2):

The social benefits of land use primarily refer to the impact on society after land utilization. In modern society, the role of humans in social development is increasingly significant. Therefore, when selecting indicators, factors related to human influence are given priority. Four indicators are chosen as the social benefits of a land use indicator layer.

Urban–rural income gap index (C5): This indicator reflects the disparity in income between urban and rural areas in the region. A higher value indicates a larger urban–rural income gap and lower social benefits of land use in the area. The calculation formula is Urban residents’ disposable income/Farmers’ and herdsmen’s net income × 100%.

Total area of raw material forest (C6): Raw material forests, as important sources of raw materials for the deserticulture, can be planted and managed by the government, enterprises, and individuals. They have certain economic value and play a role in stimulating the enthusiasm of relevant collectives and individuals to engage in the deserticulture. They can also create employment opportunities. A larger value indicates better social benefits of land use in the area.

Highway network density (C7): This indicator reflects the level of transportation accessibility and road carrying capacity in the region. A higher value indicates a higher level of transportation development and convenience for people’s travel, resulting in higher social benefits. The calculation formula is total road mileage in the region/Administrative area land area.

Engel’s coefficient (C8): This indicator refers to the percentage of household expenditures on food in total household expenditures and is an important indicator of household affluence. A higher value indicates lower social benefits of land use in the area.

(6)

Ecological benefits (B3):

Ecological benefits of land use refer to the impact of human activities on the ecological environment during the process of land utilization. The following indicators are selected as the ecological benefits of land use:

Shrub area (C9): This indicator reflects the abundance of shrub resources and the extent of greening achieved in the region.

Nature reserve area/total area (C10): This indicator reflects the government’s emphasis on natural environmental protection in the region. A higher value indicates better ecological benefits of land use in the area. The calculation formula is Natural protected area/Total land area × 100%.

Forest coverage rate (C11): This indicator refers to the percentage of forest area to the total land area in the region, which reflects the forest coverage within the region. It is an important indicator of ecological benefits in an area. A higher value indicates a more stable ecological system and better ecological benefits of land use.

Number of days per year exceeding the onset of sandstorms (C12): This indicator refers to the number of days in the region where wind speed exceeds the threshold for sandstorms, resulting in dust storms and sandstorms. It is an important indicator of the ecological environment and air quality in the area.

2.2.2. Evaluation Model

(1)

Data normalization processing:

Max–Min normalization is a common data normalization method. Its purpose is to scale the value of a numerical variable to a specific range, typically between 0 and 1 [27]. Using the Max–Min normalization to process data, the formula is as follows:

$$b_j=\frac{x_{ij}-\min \left(x_j\right)}{\max (x_j)-\min (x_j)}$$

(1)

$$b_j=\frac{\max (x_j)-x_{ij}}{\max (x_j)-\min (x_j)}$$

(2)

where Formula (1) represents the positive index formula, and Formula (2) represents the negative index formula. Here, b_i denotes the standardized index data, x_ij refers to the original value of j-th indicator in i-th year, while max(x_j) and min(x_j) denote the maximum and minimum values of j-th index.

(2)

Determination of evaluation indicator weights:

The entropy method is an objective weighting method for determining indicator weights by analyzing the information entropy of indicators and their relative changes through intervention in the entire system. The greater the relative change in an indicator, the higher its weight. Due to its practicality and high research value, the entropy method for determining weights has been widely applied in various fields [28,29].

Therefore, this article utilizes the entropy method to assess the development level of the deserticulture and benefits derived from desertification land use [30]. The proportion of index value p_ij in the i-th year for j-th item is then calculated:

$$p_{ij}=\frac{b_{ij}}{{\displaystyle \sum _{i=1}^m{b}_{ij}}}, i=1,2\cdots ,m; j=1,2\cdots n,(0\le p_{ij}\le 1);$$

(3)

To calculate the entropy value e_j of the j-th index:

$$e_j=-k_i{\displaystyle \sum _{i=1}^m\left[p_{ij}\ln \left(p_{ij}\right)\right]}, i=1,2\cdots ,m; j=1,2\cdots ,n;$$

(4)

In Formula (4), $k_i=\frac{1}{\ln (m)}$, $0\le k_i, 0\le e_j\le 1$, $m=8, k=\frac{1}{\ln 8}\approx 0.481$;

To calculate the difference coefficient g_i of the j-th index:

$$g_j=1-e_j, j=1,2\cdots ,n;$$

(5)

To calculate the weight of each index with the difference factor w_j:

$$w_j=\frac{g_j}{{\displaystyle \sum _{j=1}^n{g}_j}}, j=1,2\cdots ,n$$

(6)

where w_j represents the weight of each indicator layer, and g_j is the difference coefficient of each indicator layer [31].

(3)

Measurement model of evaluation results:

$$D_i(\omega )={\displaystyle \sum _{j=1}^n{b}_{ij}}\times W_j, i=1,2,\cdots ,m; j=1,2,\cdots ,n$$

(7)

In the formula, D_i(w) represents the comprehensive evaluation value, W_j denotes the weight of the j-th indicator, b_ij stands for the standard value of the indicator, and n refers to the number of indicators.

(4)

Research model of coupling relationship:

$$C=2{\left\{\frac{U(o)\times U(a)}{{\left[U(o)+U(a)\right]}^2}\right\}}^{\frac{1}{2}}$$

(8)

The function U(o) represents the level of development in deserticulture, which is a comprehensive evaluation value obtained through an index system for evaluating the level of development in deserticulture. The function U(a) represents land use benefits, which is a comprehensive evaluation value obtained through an index system for evaluating the benefits of using desertified land. The degree of coupling C ∈ [0, 1].

$$D=\sqrt{C\cdot T}$$

(9)

$$T=\alpha \cdot U\left(o\right)+\beta \cdot U\left(a\right)$$

(10)

In the formula, T represents the comprehensive coordinated scheduling of deserticulture development and desertification land use benefits; α and β are undetermined functions with a sum equal to 1. Therefore, in this article, both α and β are set to 0.5; D represents the coupling coordination degree, with a value ranging from 0 to 1 used to determine the strength of coupling coordination [32]. By measuring the relative proximity of the evaluation object to the optimal development model and conducting classification and sorting, this article categorizes the coupling coordination degree into three types of coordinated development with ten levels of evaluation (

Table 3. Classification and evaluation criteria for coupling coordination degree levels.

Coupling Coordination Degree Range	Evaluation Level	Coordination Development Type
0.90~1.00	High-Quality Coordination	Coordinated Developing Type
0.80~0.89	Good Coordination
0.70~0.79	Intermediate Coordination
0.60~0.69	Primary Coordination
0.50~0.59	Barely Coordinated	Transition Type
0.40~0.49	Near Dysfunction
0.30~0.39	Mild Dysfunction	Dysfunction Type
0.20~0.29	Moderate Dysfunction
0.10~0.19	Severe Dysfunction
0.00~0.09	Extreme Dysfunction

) [33]. The calculated coordination degrees exhibit both relatively high and low levels of coordination, and the classification of coordination evaluation levels and coordinated development types are only applicable within the scope of this research period [34].

3. Results and Discussion

3.1. Deserticulture Development and Land Use Benefits Evaluation

Based on the indicators of Ordos City from 2010 to 2017, we have utilized Formulas (1)–(7) to calculate the evaluation values for both the development level of the deserticulture (Figure 2) and the comprehensive benefits of land use (Figure 3).

3.1.1. Evaluation of Deserticulture Development

From 2010 to 2017, the input, output, environment, and comprehensive assessment value of deserticulture development in Ordos City exhibited an overall upward trend (Figure 2), indicating a certain degree of promotion and improvement in the level of deserticulture development.

In 2017, the evaluation value of investment in deserticulture development was approximately 0.119, marking a growth of 38.250 times compared to 2010. This significant increase can be attributed to the marginal upward trends observed in both the total assets of the deserticulture (Q1) and the deserticulture output/GDP (Q2). Meanwhile, the funds used by enterprises for purchasing raw materials (Q4) experienced a slight decline. Notably, the investment in deserticulture development fluctuated during the same period due to a combination of upward and downward movements in the funds allocated for Q4 between 2010 and 2015, as well as between 2016 and 2017. However, the overall trend remained upward. In 2017, the evaluation value of deserticulture output reached 0.328, an increase of 1.723 times compared to 2010, with an average annual growth rate of 21.532 percentage points. Although there was a minor decline in annual per capita income increases in deserticulture/disposable income of farmers (Q5), and the number of farmers and herdsmen driven by the enterprise annually (Q7) and the sales revenue of enterprises (Q6) experienced a slight upward trend. This can be attributed to the notable increase in per capita income growth facilitated by enterprises (Q8), indicating an increase in income generation despite the reduction in the number of farmers and herders employed. As depicted in Figure 2, the evaluation values of investment and output in the deserticulture in Ordos City fluctuated significantly from 2010 to 2015. It was not until 2016 and 2017 that consecutive years of output exceeding investment were observed, indicating a certain degree of stable development in the deserticulture. However, it is likely that the industry is still in the exploration and experimental phase, with ample room for improving investment-output efficiency. The evaluation value of the environmental impact of deserticulture development in 2017 was 0.343, a growth of 12.418 times compared to 2010, with an average annual increase of 155.219 percentage points. This growth can be attributed to the rapid increase in total retail sales of social consumer goods (Q10), the ending balance of various loans from financial institutions (Q11), and tourism revenue (Q12) from 2010 to 2017, despite a noticeable decline in fixed investment in agriculture, forestry, animal husbandry, and fisheries (Q9) in 2011 and 2017. These trends indicate an overall improvement in the financial and consumer environment for deserticulture development in Ordos City.

As shown in the figure, the comprehensive evaluation value of deserticulture development in Ordos City increased from 0.149 to 0.789 between 2010 and 2017, demonstrating a fluctuating upward trend with an average annual growth rate of 61.36%. This reflects an overall improvement in the level of deserticulture development in Ordos City, despite some fluctuations. The deserticulture development had achieved a certain degree of stable development, but it was still in the stage of exploration and practice, and there was a large space for the development of input–output benefits. In terms of the components of the evaluation value, the weights of investment in deserticulture development, deserticulture output, and deserticulture environmental impact were 0.221, 0.391, and 0.388, respectively. These weights indicate that the intensity of investment in deserticulture development has a relatively smaller impact compared to the development output and environmental factors.

3.1.2. Land Use Benefits Evaluation

From 2010 to 2017, the overall evaluation values of the economic, social, ecological, and comprehensive benefits derived from desertification land use in Ordos City exhibited an upward trend (Figure 3). During the period of 2010 to 2017, the development of deserticulture in Ordos City exhibited an overall upward trend in economic, social, and ecological benefits derived from the utilization of desertified land. The linear regression analysis yielded slope values of 0.0645, 0.0298, and 0.0158 for economic, social, and ecological benefits, respectively, indicating that the growth rates followed the order of economic benefits > social benefits > ecological benefits. Furthermore, the R-squared values obtained from the linear regression analysis were 0.7806, 0.5562, and 0.6176 for economic, ecological, and social benefits, respectively, suggesting that the stability of the development exhibited the pattern of economic benefits > ecological benefits > social benefits. These findings underscore the prominence of economic benefits in driving the development of deserticulture, followed by the importance of social and ecological benefits. The high R-squared values indicate the robustness and reliability of the observed trends, emphasizing the significance of sustainable development practices in balancing economic growth with social well-being and ecological preservation. From 2010 to 2017, the evaluation value of land use economic benefits was inferior to the two benefits in 2010 but surpassed social and ecological benefit evaluation values in all subsequent years. This suggests that land use economic benefits serve as a crucial driver for enhancing comprehensive regional desertification management outcomes. Between 2010 and 2017, the shrub area in Ordos City increased from 25.41 million mu (16,940 km²) in 2010 to 30.27 million mu (20,180 km²) in 2017. Similarly, the forest coverage rose from 23.01% in 2010 to 26.72% in 2017, with an average annual growth rate of 2.49%. Furthermore, the number of days with sandstorms exceeding the threshold decreased from 235 days in 2010 to 150 days in 2017. The influence of wind and sand flow on the ecological benefits of the land is negative. To protect the land’s ecosystem and mitigate the impact of wind and sand flow, corresponding measures, such as vegetation restoration, soil conservation, and sandstorm control, need to be implemented to promote sustainable land utilization and improve the ecological environment. The increase in shrub area and forest coverage enhances soil stability, preserves water sources, and provides habitats for flora and fauna. The reduction in the number of days with sandstorms lowers the frequency and intensity of dust storms, thereby reducing soil erosion and degradation, preserving soil integrity and fertility, and benefiting crop growth and ecosystem stability. The evaluation values of ecological benefits, except for being higher than social benefits in 2012 and 2013, are lower than economic and social benefits evaluation values in other years, indicating that economic and social benefits are more easily realized in the short term, while the improvement of ecological benefits requires more time and sustained efforts. There may be other factors or issues limiting the achievement of ecological benefits, such as insufficient or ineffective ecological restoration measures. Although the improvements in shrub area, forest coverage, and the reduction in the number of days with sandstorms have positive effects on the ecological environment, there is still room for further improvement to enhance the ecological benefits of desertified land. Identifying factors that may influence the evaluation results and taking corresponding measures for improvement are necessary.

Except for 2010, the evaluation values of land use comprehensive benefits in other years are higher than the evaluation values of deserticulture development. Notably, the comprehensive benefits evaluation values of land use in 2014 and 2015 significantly exceed those of deserticulture development, indicating a relatively high degree of land use intensification. In 2016 and 2017, the development level of deserticulture and land use benefits reached a high level of development. During this period, the input, output, and development environment of deserticulture are becoming increasingly rational and perfect, while the land use benefits have also made relatively significant progress. However, reform and innovation are needed at this stage to explore new development models and routes.

3.2. Evaluation and Analysis of the Coupling Relationship between Deserticulture Development and Land Use Benefit

3.2.1. Coupling Relationship between Deserticulture Development and Land Use Benefits

From 2010 to 2017, the coupling degree between deserticulture development level and land use comprehensive benefits in Ordos City was greater than 0.89 (Figure 4), indicating that there has always been a strong coupling relationship between deserticulture development and land use benefits, and there is a strong correlation between the two evaluation systems. The coupling coordination degree between deserticulture development and land use benefits in Ordos City exhibited an overall upward trend from 2010 to 2017, experiencing a mild dysfunction stage in 2010 and then transitioning to a low-level coupling coordination stage from 2011 to 2013. Subsequently, it continued to improve in 2014, entering a good coordination stage. In 2015, the coordination level experienced a 2.2% decrease to an intermediate level; from 2016 to 2017, the coupling degree between them was approximately 0.94 and 0.91, respectively, leading to an overall increase in the coupling relationship quality toward the high-quality coordination stage. The development of both remained relatively consistent, resulting in an overall resonance coupling level that has advanced into a benign state. The correlation between the development of deserticulture and land use benefits in Ordos City has reached a high level from 2010 to 2017, with a tendency toward strong coupling. Based on the stabilization of correlation, there has been an increase in the overall fluctuation of the coupling coordination degree value from the initial state of “uncoordinated coupling” to increasingly coordinated changes in the coupling degree and scheduling. This indicates a further improvement in the level of coupling coordination development between both parties, with their developmental steps becoming more unified and interactions more coordinated.

3.2.2. Coupling Coordination Degree between Deserticulture Development and Land Use Benefits Subsystem

The coupling types between various subsystems of deserticulture development and land use benefits consist of an inter-system subsystem interaction coupling and an intra-system subsystem interaction coupling. P1, P2, and P3, respectively, represent the input, output, and environment levels of deserticulture development. B1, B2, and B3, respectively, denote the economic, social, and ecological benefits of land use. Pairwise coupling refers to the interaction coupling relationship between two subsystems. For example, P1B1 denotes the coupling coordination between the input of deserticulture development and economic benefits of land use in subsystem interaction coupling, and P1P2 represents the coupling coordination between the input and output of deserticulture development within the system’s subsystems interaction couplings. The coupling coordination relationship between deserticulture development and land use benefits across subsystems was analyzed (Figure 5) [35].

As shown in Figure 5 and

Table 4. The coupling coordination degree and coordinated development stage of deserticulture development and land use benefit.

Year	U(o)	U(a)	Coupling Degree	Coupling Coordination Degree	Coordination Development Type
2010	0.1491	0.1297	0.9976	0.3738	Mild Dysfunction
2011	0.1894	0.4275	0.9225	0.5718	Barely Coordinated
2012	0.3619	0.3661	0.9999	0.6033	Primary Coordination
2013	0.2416	0.5370	0.9252	0.64193	Primary Coordination
2014	0.3594	0.8473	0.9146	0.8013	Good Coordination
2015	0.3212	0.8247	0.8983	0.7836	Good Coordination
2016	0.8474	0.9165	0.9992	0.9395	High-Quality Coordination
2017	0.7894	0.8603	0.9991	0.9086	High-Quality Coordination

, the coupling coordination degree between subsystems exhibited fluctuations and local as well as overall increases from 2010 to 2017. However, the coupling coordination stage between the two subsystems remained below intermediate coordination, with a maximum value of 0.66 for P2B1 in 2016. The overall coupling coordination degree of subsystems can be further subdivided into four stages: (1) In 2010, the overall coupling degree of subsystems was extremely low with a high degree of dispersion, resulting in significant inconsistencies between the internal and external development of subsystems. (2) From 2011 to 2013, the coupling coordination degree increased to a slight disharmony. The highest convergence level was observed in 2011, indicating a high response sensitivity and a low coupling with high cohesion between the two systems. In 2012, the subsystem coupling coordination degree showed similar mean and median values, suggesting small development dispersion. The values in 2013 were concentrated in the median and lower quartile range of each coupling coordination value, which lowers its coordination median value. (3) The subsystem coupling coordination degree was on the near dysfunction level during 2014~2015, with a maximum difference of 0.406 appearing in 2015 (the extremes were 0.199 for P1P1 and 0.605 for P3B1). This indicates that the performance of some subsystems’ internal coupling coordination was extremely poor during this period. However, the values of B1B3, P3B1, and B1B2 all exceed 0.5, indicating that the coupling coordination among the three subsystems has reached a higher level of development characterized by reluctant and primary coordination levels. (4) From 2016 to 2017, the discreteness of the coupling coordination degree among subsystems gradually converged. With the exception of a low value in P1B3, the overall coupling coordination degree remained at a stage of barely coordinated and began to transition into a new phase of development.

From the development trend of each subsystem coupling body, it can be observed in Figure 5 that all subsystem coupling bodies (P1B1, P2B1, P3B1, B1B2, B1B3) comprising land use economic benefits (B1) have the lowest starting value of coordination degree and the greatest development span of coupling coordination degree with an average maximum span of 0.63. The average annual dispersion amplitude of its coordination degree is the smallest, approximately 0.075, while the other subsystems’ coupling body has a dispersion amplitude of about 0.20. This indicates that during the interactive coupling between desert agriculture development and land use benefits. The sensitivity coefficient of land use economic benefits to other indicators is relatively high, and the promotion of convergence development between the two becomes timelier with the progress of economic benefits. For all subsystems (P1B2, P2B2, P3B2, B1B2, B2B3) that constitute the social benefits of land use (B2), the initial coordination degree is highest. However, the range of coupling coordination degree is smallest at approximately 0.328. This indicates that B2 has the most stable development speed when moving toward an optimal coupling mode and exhibits a slower response to other subsystems. At the outset, augmenting investment in social benefits may not significantly impact the development of coupling systems. However, when other factors approach perfection and the overall optimization speed of coupling degree slows down, it is advisable to consider increasing investment in social benefits of land use to further cultivate a coordinated relationship between deserticulture development and land use benefits [36].

4. Conclusions

From 2010 to 2017, the deserticulture in Ordos City has exhibited a positive trend in investment, output, and environmental performance. Although the input–output ratio of the deserticulture is relatively high, its input intensity remains insufficient. During this period, the contribution value of deserticulture development investment to the overall evaluation and growth of deserticulture development is smaller than the contribution value of deserticulture development output and environmental level. The overall land use benefits tend to rise, the economic benefit growth rate being the fastest and most stable, serving as a crucial driving force for promoting comprehensive land use benefits in Ordos. Meanwhile, the ecological benefits have the lowest but relatively stable growth rate. The coupling relationship between deserticulture development and land use benefits remains relatively stable, exhibiting a strong correlation. The coupling degree and coupling coordination trend are becoming increasingly collaborative, with the overall subsystems’ coupling coordination degree maintaining an upward trend. The evaluation level of coordination degree gradually improves from relatively severe dysfunction to a relatively barely dysfunction level as a whole.

The overall development of the deserticulture in Ordos has gradually achieved the goal of integrating economic, ecological, and social benefits. There is a relatively good coupling relationship between the deserticulture development level in Ordos and the land use benefits level. The findings demonstrate that the development of deserticulture has contributed to the overall evaluation and growth of land use benefits in Ordos City. Therefore, it can be inferred that the primary constraint on the current coupling coordination degree of deserticulture benefits is the benefits development level of each subsystem, rather than the coupling relationship. Due to the short development time of the deserticulture, its industry chain is relatively brief and lacks close connections between chains. The initial investment is small, and output benefits are not immediately apparent, which limits the further development of deserticulture. Strengthening risk resistance, enhancing the visibility of product geographical indications, and increasing market sales proportion are currently the most effective measures to augment the total value of deserticulture benefits and enhance coupling coordination.

In terms of economic benefits, the development of the deserticulture industry typically leads to increased employment opportunities, enhanced production value, and overall economic growth. This aligns with findings from other countries, highlighting the significant implications of deserticulture development for boosting regional economic development and improving residents’ income status [37].

Regarding social benefits, the advancement of deserticulture contributes to improved social welfare and an enhanced standard of living for the population. By generating more job opportunities and providing social security, the deserticulture industry offers increased benefits to society and enhances the quality of life for residents. Similar studies conducted in other countries also emphasize the positive impact of deserticulture on social welfare [38,39].

Furthermore, ecological benefits play a crucial role in deserticulture research. Numerous studies from various countries demonstrate that deserticulture development can enhance land quality, protect the ecological environment, and promote biodiversity conservation. By implementing appropriate land management practices and environmental conservation measures, the deserticulture industry significantly contributes to achieving sustainable development goals [40,41].

Enhancing land utilization benefits is crucial for facilitating the development of the deserticulture, as it heavily relies on land resources. Efficient land utilization plays a pivotal role by providing abundant resources and support for the deserticulture. For instance, the availability of high-quality land and ample water resources enables the cultivation of high-yield sand-based agriculture and aquaculture projects. Conversely, inadequate land utilization benefits, scarcity of resources, and harsh environmental conditions can constrain the growth of the deserticulture. Thus, optimizing land utilization benefits becomes imperative, ensuring a favorable environment for the deserticulture to thrive. It is essential to achieve sustainable development and employ scientifically sound management practices to minimize adverse effects on land resources and maximize positive impacts on land utilization benefits. Additionally, aligning government land utilization policies and strategies with the development of the deserticulture will foster a harmonious relationship, enabling a beneficial cycle of mutual reinforcement between the deserticulture and land utilization benefits. The establishment of an evaluation system for the development of the deserticulture and land utilization benefits holds paramount significance in fostering sustainable development, enhancing land utilization efficiency, driving industrial innovation and upgrading, and facilitating informed decision-making. This system aids in harmonizing the intricate relationship between economic progress and ecological preservation while propelling the deserticulture toward a path of sustainability and optimal efficiency.

This study acknowledged the limitation of a narrow data scope, which may affect the generalizability of the findings. To overcome this limitation, future research can consider expanding the data scope by including a larger sample size and incorporating data from multiple regions or countries. This would provide a more representative and diverse dataset for analysis, leading to more robust and generalizable conclusions.