Rural Landscape Change: The Driving Forces of Land Use Transformation from 1980 to 2020 in Southern Henan, China

Abstract

Rapid urbanization has had an important impact on the pattern and function of rural land use. To better understand the key drivers of the landscape pattern evolution in southern Henan in China from 1980 to 2020, we used techniques of GIS(Geographic Information System) technology and the geodetector model in the research area of landscape pattern evolution characteristics. The research results show that the land use transformation in the rural areas of southern Henan has been characterized by the conversion of production land to living land and ecological land, with the highest conversion rate and continuous growth of construction land, a decreasing trend of cropland, and continuous and stable growth of land for forest and water body in the past 40 years. Land use conversion in the rural areas of southern Henan is mainly concentrated in the northern, central, and southern areas, and the spatial conversion has shifted from mountainous areas to the plains. The center of gravity of forest, cropland, and water body has most obviously shifted, and human interference and ecological environment destruction are the main influencing factors. The overall landscape pattern in the rural areas of southern Henan has increased in fragmentation and landscape heterogeneity, evenness has decreased, irregular patches have increased, and landscape connectivity has decreased. The combined effect of the six dimensions of elevation, slope, night lighting, average annual precipitation, average annual temperature, and population density in the rural areas of southern Henan has led to the transformation of land use and changes in landscape pattern. Physical geographic factors are the main drivers of rural landscape pattern changes in southern Henan, while population density changes and urbanization are secondary drivers. The results of the study have important guiding significance for the further optimization of rural landscape patterns and the sustainable development of rural areas.

1. Introduction

The concept of land use transition was first proposed by the British scholar Grainger [1], who believed that land use transition is a dynamic process with a time series of changes in regional land use patterns in response to socio-economic development changes. The basic characteristics of land transition are land use change and intensification [2], and the rapid land use transition caused by urbanization has a great impact on the ecological environment [3,4,5]. The Chinese scholar Long Hualou introduced the concept of “land use transition” to China in 2002 as a new way of integrated land use and cover change research [6]. A large number of scholars have followed to conduct a series of studies on land use transformation in terms of theory and hypothesis [7], characteristics and laws [8,9], and development prediction [10,11,12,13], and a systematic theoretical framework has been formed. With the rapid development and continuous transformation of the social economy, especially with regard to the strategy of ecological civilization construction, land use transformation research has mostly focused on the relationship between urban function and rural revitalization, and has been in the last decade [12,14,15]. Landscape pattern is one of the core elements in the field of landscape ecology, and change in pattern is a prominent sign of land use transformation [16,17,18]. Landscape pattern refers to the composition and configuration of different ecosystems or land cover types in time and space, and it is the result of the action of ecological processes on different scales [15,19]. The quantitative analysis of landscape pattern is the basis for studying the interrelationship between pattern and process. The size, shape, and arrangement of landscape patches reflect, to a certain extent, the way and intensity of human activities, and influence the ecological processes and forms of material cycling, energy flow, and information transfer in them [20]. Changes in land use transformation affect the development pattern of towns and cities. By exploring the characteristics of regional land use transformation, the evolution of a region’s landscape pattern can be analyzed, which is of great significance to the development of regional ecological security [21].

Land system science is committed to monitoring land change, explaining driving factors and feedback mechanisms, and understanding human–environment interactions occurring on land. Relevant theoretical achievements are still scarce [22,23,24,25]. Research on land use transition is an important component of current land system science research. The explanation and prediction of land use transition depend on the reference of relevant academic theories and the theoretical construction of land use research [26]. At present, the research on the evolution of landscape pattern under the transformation of land use mainly focuses on the impact of rapid urbanization on regional landscape pattern. The research on the spatial evolution of land use and landscape pattern mostly focuses on large-scale regions, while the research on small-scale regions such as local rural areas is lesser; in particular, the focus on the evolution of rural landscape pattern reflected by the main grain-producing areas is low, and the research on the evolution of rural landscape pattern in the context of land use transformation is lacking.

The southern area of Henan province is located in the transition zone from a subtropical humid monsoon climate to a warm temperate semi-humid monsoon climate. It is the main grain production base of Henan province and is rich in resources, but is also an important ecological zone for carbon fixation and oxygen release, and water conservation and soil conservation in the central plains of China. It also has a high incidence of natural disasters such as soil erosion, and the ecological environment is relatively fragile, which inevitably makes the conflict between socio-economic development and ecological environmental protection more acute. With the rapid development of urbanization, the increase in regional population and over-exploitation of land have led to increased ecological and environmental pressure in southern Henan, and some rural areas have serious problems such as soil erosion, frequent natural disasters, and degradation of ecosystem service values. However, at present, few scholars have conducted qualitative and quantitative research on the dynamic evolution and optimization strategy of landscape pattern in the rural areas of southern Henan from the perspective of landscape ecology, especially on the landscape pattern in the rural areas of southern Henan based on the background of land use transformation.

In view of this, this study takes the rural areas in southern Henan province as the research target area, and based on the perspective of land use transformation, uses remote sensing (RS), the geographic information system (GIS), and other technologies, means, and geographic detector models, selects the period from 1980 to 2020 as the research period, and discusses the spatial–temporal evolution characteristics and driving forces of the landscape pattern under the background of land use transformation in the study area over the past 40 years. It is expected to provide a scientific basis for land use planning and management in the study area, so as to improve the value of ecosystem services in the study area and improve human well-being in rural areas.

2. Overview of the Study Area

The southern part of Henan province is at the junction of the three provinces of Hubei, Henan, and Anhui and between the northern foot of Dabie Mountain and the upper reaches of Huai River. It has three prefecture-level cities named Nanyang, Zhumadian, and Xinyang, and three directly governed counties (cities) named Dengzhou, Gushi, and Xincai, with a total area of about 58,000 km² and a total population of 27 million (Figure 1). The study focuses on the evolution of rural landscape patterns and rural development patterns in southern Henan, so the urbanized area of the study area was excluded.

The southern part of Henan has a very advantageous geographical location because it is at the intersection of the Wuhan economic circle, Wanjiang urban belt, and the Central Plains economic zone. It has four distinct seasons and a remarkable monsoon climate, and is a typical transition zone from the subtropical to warm temperate zone. The overall topography is high in the south and low in the north, with complex topography and landforms (Figure 2). The altitude is between 22 and 2128 m, and the mountains, valleys, and hills are evenly distributed (Figure 3). The climate type is relatively complex, with an average annual temperature of about 14–16 ℃ and annual precipitation of 800–1100 mm. The soil types include brown loam, dark brown loam, alpine meadow soil, and brown soil, which are conducive to the growth of plants and crops. The vegetation types include coniferous forest (evergreen coniferous forest, deciduous coniferous forest), broad-leaved forest (evergreen broad-leaved forest, deciduous broad-leaved forest, mixed evergreen deciduous broad-leaved forest), mixed coniferous forest, bamboo forest, thicket and scrub, meadow, swamp vegetation, and aquatic vegetation. In southern Henan, the crops are mainly rice, wheat, and corn, and it is an important grain and oil production base in the province. Under the combined influence of a transitional climate from north to south, and a mountainous climate with unique natural geographical conditions, droughts and floods occur in southern Henan, posing a great threat to local economic construction, agricultural and industrial production, and social development.

3. Materials and Methods

3.1. Data Sources and Processing

Remote sensing images were obtained from the Geospatial Data Cloud (http://www.gscloud.cn/) (accessed on 12 August 2022) and the website of the United States Geological Survey (https://earthexplorer.usgs.gov/) (accessed on 18 June 2022), and five periods of remote sensing image data were selected from 1980, 1990, 2000, 2010, and 2020. All of the images have the time phase of June to September, and the cloudiness of the images is less than 1%. The high spatial resolution remote sensing images used for accuracy verification were obtained from BIGEMAP map downloader (BIGEMAP GIS Office v1.0) (http://www.bigemap.com/) (accessed on 20 August 2022). Other data sources for socio-economic, population, topography, climate, and location factors are shown in

Table 1. Main data sources.

Data Type	Data/Factors	Year	Resolution	Source
Remote sensing image data	Landsat MSS	1980	70 m	https://earthexplorer.usgs.gov (accessed on 18 June 2022)
	Landsat ETM +	1990, 2000	30 m	https://earthexplorer.usgs.gov (accessed on 12 June 2022)
	Landsat ETM	2010	30 m	https://earthexplorer.usgs.gov (accessed on 12 June 2022)
	Landsat OLI-TIRS	2020	30 m	https://earthexplorer.usgs.gov (accessed on 12 June 2022)
Socio-economic factors	Population density (X1)	2019	1 km	http://www.resdc.cn (accessed on 18 June 2022)
	GDP (X2)	2019	1 km	http://www.resdc.cn (accessed on 18 June 2022)
	Night lighting (X3)	2020	500 m	http://www.noaa.gov/ (accessed on 16 June 2022)
Topographical factors	Elevation (X4)	-	30 m	http://www.gscloud.cn (accessed on 12 August 2022)
	Slope (X5)	-	30 m	Calculated from DEM (accessed on 12 August 2022)
Climate factors	Average annual temperature (X6)	-	1 km	http://www.resdc.cn (accessed on 17 August 2022)
	Average annual precipitation (X7)	-	1 km	http://www.resdc.cn (accessed on 17 August 2022)
Location factors	Distance from major railroads (X8)	2015	-	https://www.webmap.cn/(accessed on 21 August 2022)
	Distance from major roads (X9)	2015	-	https://www.webmap.cn/ (accessed on 21 August 2022)
	Distance to third-order stream and above (X10)	2015	-	https://www.webmap.cn/ (accessed on 21 August 2022)

.

First, we used ENVI5.3 (https://envi.geoscene.cn/) (accessed on 10 May 2022) software to pre-process the remote sensing images of 1980, 1990, 2000, 2010, and 2020 for the study area with atmospheric correction and radiometric calibration in FLASH module. By analyzing and comparing the color differences in each band combination, we combined the historical images and field research results of the study area to determine each land use type corresponding to each band combination. Then, the maximum likelihood method was used for feature classification, and then the land use classification results for 1980, 1990, 2000, 2010, and 2020 were obtained. Finally, thirty randomly selected calibration samples were taken for each land use type, and an error matrix was established to evaluate the classification accuracy. The classification accuracy of the five time periods reached more than 85%, and the kappa coefficients all exceeded 0.8, and thus the classification results could be used in the study. Finally, raster processing, fusion, and map output were performed in ArcGIS10.6, and the final land use classification maps for each of the five phases were obtained (Figure 4 and

Table 2. Multi-period land use/land cover remote sensing monitoring data classification system in the rural areas of southern Henan.

Serial Number	Land Use Type	Meaning
1	Cropland	Refers to the land used for crop cultivation, including mature cultivated land, newly opened wasteland, recreational agricultural land, rotation land, grass field rotation crop land, fruit forest, and economic forest, as well as beach and seashore cultivated for more than three years.
2	Forest	Refers to forest land for growing trees and shrubs.
3	Grassland	Refers to all kinds of grassland dominated by growing herbs and coverage above 5%, including shrub grassland and sparse forest grassland in pastoral areas with canopy density below 10%.
4	Water body	Refers to natural land waters, including water conservancy facilities.
5	Construction land	Refers to industrial, mining, and transportation land in rural areas, but does not include residential areas.
6	Unused land	Refers to the types of land that are difficult to use or have not yet been developed in rural areas.

).

According to the “Land Use Status Classification Standard (GB21010-2017)” and field research, the land use of rural areas in southern Henan was divided into six categories: forest, cropland, grassland, water body, construction land, and unused land (Table 2). Meanwhile, based on the classification system of “Production–living–ecological” [27,28], each land use type was also classified into three life spaces from the perspective of the dominant function of land use, in which cropland was considered as production space, construction land as living space, and ecological space included forest, water body, and unused land (

Table 3. “Production–living–ecological” land use classification in the rural areas of southern Henan.

Space Types	Land Use Types	Functional Interpretation
Production space	Cropland, grassland	Used in production and business activities, producing economic benefits
Living space	Construction land	Used for daily communication activities, providing life services
Ecological space	Forest, water body, unused land	Space for species to survive and multiply, providing natural resources

).

3.2. Single Land Use Dynamic Attitude Model

The dynamic degree model of land use can characterize the transfer of different land use types within a certain period of time, and identify the hot spots of land use change in the study area [29]. The specific calculation formula is as follows.

$$K=\frac{U_{b-U_a}}{Ua}\times \frac{1}{T}\times 100\%$$

(1)

In Equation (1), K denotes the attitude of a land use type during the study period; Ua and Ub, respectively, denote the number of a land use type at the beginning and end of the study period; T denotes the length of the study period; and when the period of T is set to years, K denotes the annual rate of change in a land use type.

3.3. Land Use Transfer Matrix

The land use transfer matrix is a mathematical model used to portray the structural characteristics of regional land use change and the direction of change for each land use type, and is a method for quantitative analysis of system state and state transfer [21,29]. The mathematical form of the transfer matrix is as follows.

$$S=\left[\begin{array}{c}{S}_{11}{S}_{12}{S}_{13} \cdots S_{1n}\\ S_{21}{S}_{22}{S}_{23} \cdots S_{2n}\\ S_{31}{S}_{32}{S}_{33} \cdots S_{3n}\\ ⋮\\ S_{n1}{S}_{n2}{S}_{n3} \cdots S_{nn}\end{array}\right]$$

(2)

In Equation (2), S is the land area; S_ij indicates the area of land transferred from land use type i to type j at the beginning and end of the study period; and n is the number of land use types.

3.4. Landscape Center of Gravity Shift Model

The evolution process of landscape types can be characterized by the transfer model of landscape center of gravity to reflect the transfer trend of different landscape types [21,30]. The center of gravity model equation is as follows.

$$Y_t={{\displaystyle \sum }}_{i=0}^n\left(C_{ti}\times Y_{ti}\right)/{{\displaystyle \sum }}_{i=1}^n{C}_{ti}$$

(3)

$$X_t={{\displaystyle \sum }}_{i=1}^n\left(C_{ti}\times X_{ti}\right)/{{\displaystyle \sum }}_{i=1}^n{C}_{ti}$$

(4)

In Equations (3) and (4), X_t and Y_t, respectively, denote the latitude and longitude coordinates of the center of gravity of a landscape type in year t; X_ti and Y_ti, respectively, denote the latitude and longitude coordinates of the center of gravity of the ith patch of the landscape type in year t; and C_ti denotes the area of the ith patch of the landscape type in year t.

3.5. Landscape Index Selection

Landscape indices can quantitatively express the correlation between landscape patterns and ecological processes [19]. Using Fragstats 4.2 software, the evolutionary characteristics of landscape patterns are separately analyzed from type level and landscape level: (1) type level indices include number of patches (NPs), class area (CA), aggregation index (AI), and landscape shape index (LSI); and (2) landscape level indices include contagion index (CONTAG), landscape division (DIVISION), Shannon diversity index (SHDI), Shannon evenness index (SHEI), and aggregation index (AI). The ecological significance of different landscape indexes mainly refers to the literature published by Wu [19].

3.6. Driver Factors Selection

This study selects the driving factors that affect the evolution of land use and landscape pattern in the rural areas of southern Henan according to the following criteria: (1) the factors are quantifiable and independent of each other; (2) the driving factors include socio-economic factors, terrain factors, climate factors, and location factors; (3) each driver is available and easy to obtain. In this study, a total of 10 driving factors were selected according to the actual situation of the study area and the relevant literature. Among them, socio-economic factors included population density, GDP, and nighttime lighting, topographic factors included elevation and slope, climatic factors included annual average rainfall and annual average temperature, and location factors included distance from major railways, distance from major highways, and distance from water systems above Class III.

3.7. Geographic Probes

The geographic detector is a metrological model used to detect the driving force behind the spatial differentiation mechanism. Factor detection and interactive detection can well reveal the impact factors and their degree of effect that affect the landscape evolution, but it is worth noting that the independent variable X involved in the geographic detector model must be a discrete type variable [31,32]. Accordingly, this paper disaggregated the continuously varying independent variable factors into nine categories based on the natural breakpoint method, and subsequently used the $q$ statistics to determine the strength of each driver X in explaining the spatial variation in landscape type Y during the time period 1980–2020. The value of q was within [0,1], and the larger its value indicates the stronger the explanatory strength of the driver X for the spatial change Y in the landscape type that occurred; the formula is as follows.

$$q=1-\frac{1}{N{\mathsf{\sigma }}^2}{\displaystyle \sum }_{\mathrm{h}=1}^{\mathrm{L}}{N}_{\mathrm{h}}{\mathsf{\sigma }}_{\mathrm{h}}^2$$

(5)

In Equation (5), $\mathrm{L}$ denotes the stratification or classification of the driving factor X; $N_h$ and $N$, respectively, denote the layer $\mathrm{h}$ and the number of cells in the whole area; and ${\mathsf{\sigma }}_{\mathrm{h}}^2$ and ${\mathsf{\sigma }}^2$, respectively, denote the variance of the layer $\mathrm{h}$ and the variance of the Y-values of the whole region.

3.8. Logistic Regression Model

The logistic regression model now has been widely used in the driving force analysis of landscape pattern evolution, and has been recognized by most scholars [33]. This study used the logistic regression model to explore the impact of each driving factor on the change in each landscape type. The continuous value of each driving factor was taken as the independent variable X. For each type of landscape, the grid value of the changed and unchanged landscape was reset to 1 and 0, respectively. The change in a certain landscape type was taken as the dependent variable. The relevant sample data were input into the SPSS 28.0.1 (https://www.ibm.com/cn-zh/products/spss-statistics) (accessed on 16 June 2022) software for logistic regression analysis. When p < 0.05, the model was significant. The ROC (receiver operator characteristic curve)value was used to test the prediction effect of the model, and its value range was within [0,1]. The closer the ROC value was to 1, the better the prediction effect of the model was. Generally, when p < 0.05, its variables have statistical significance. Therefore, this paper selected the relevant factors that have a significant impact on the evolution of landscape pattern (p < 0.05) to carry out driving force analysis.

4. Results and Analysis

4.1. Analysis of Land Use Characteristics in the Rural Areas of Southern Henan

(1)

Analysis of the quantitative structure of land use

Located in the transition zone between the Central Plains and the northern and southern regions of China, southern Henan is a combination of an ecological function area, food production area, and tourism area, and its land uses mainly consist of forest, cropland, grassland, water body, and construction land (Figure 2).

Due to the influence of topographic factors, the location of different types of land is clearly distributed: cropland accounts for more than 60% of the total land area in southern Henan, mainly concentrated in the northeast region; forest accounts for more than 20% of the total land area, mainly concentrated in the northwest and southwest regions; construction land accounts for about 8% of the total land area, with a relatively fragmented distribution; and water body, mainly consisting of reservoirs, lakes, and rivers, accounts for about 3% of the total land area. Construction land includes land for rural residents, land for market towns, land for transportation and water body conservancy facilities, and land for roads. The land use category of other includes barren land, sandy land, and bare land.

Table 4. Area of land use types in the rural areas of southern Henan from 1980 to 2020.

Land Use Type	1980		1990		2000		2010		2020
	Area	Proportion	Area	Proportion	Area	Proportion	Area	Proportion	Area	Proportion
	km²	%	km²	%	km²	%	km²	%	km²	%
Cropland	37,462.56	64.65	37,468.08	64.66	37,700.80	65.06	36,962.07	63.79	36,410.15	62.83
Forest	12,101.55	20.88	12,094.37	20.87	12,166.53	21	12,574.97	21.7	12,393.78	21.39
Grassland	2705.27	4.67	2720.71	4.7	2329.9	4.02	2395.71	4.13	2501.69	4.31
Water body	1637.67	2.83	1604.64	2.77	1587.38	2.74	1778.76	3.07	1928.87	3.33
Construction land	4041.67	6.97	4060.87	7	4162.1	7.18	4232.05	7.3	4712.59	8.13
Unused land	0.1	0	0.1	0	0.1	0	1.13	0	4.11	0.01

summarizes the area of land use for each of the five time periods. From 1980 to 2020, the area of cropland always maintained the maximum value, of which the area of cropland in 1990 was the largest, 37,468.08 km², indicating that the landscape of cropland is the dominant landscape type in the rural areas of southern Henan, reflecting the landscape characteristics of the main grain-producing areas. The area of forest is only second to that of cultivated land. In the past 40 years, the area of forest in the study area has continuously increased from 12,101.55 km² in 1980 to 12,393.78 km² in 2020, indicating that the study area not only has high forest coverage, but also has effectively protected the forest, meaning it can continuously and effectively play the ecological service function of forest, thus better promoting regional ecological security. The proportion of construction land area ranks third and shows an increasing trend year by year, with a cumulative increase of 670.92 km² over the past 40 years, indicating that the study area is still in the rapid development stage of social economy and urbanization. As an important type of landscape, the grassland area reached 2501.69 km² in 2020, which is also the main distribution area of animal husbandry in the study area. The area of the water area is relatively small, with a cumulative increase of 291.2 km² in 40 years. The reasons may come from two aspects: first, the construction of water conservancy facilities has increased the area of the water area; another aspect may be related to the shooting time of remote sensing data. For example, the remote sensing data taken in the month with the largest precipitation may make the value of the water area larger. The area of unused land is the smallest, and its area has increased in the past 10 years, which may be related to the rapid development of social economy and urbanization processes.

(2)

Analysis of land use type dynamic attitudes

The dynamic attitude of land use can reflect the drastic degree of land use type change in the region, and a higher absolute value indicates a more active land type change and a more unstable spatial pattern. The results of land use type dynamics calculated by Equation (1) (

Table 5. Land use change rate over the decade in the study area from 1980 to 2020.

Land Use Type	1980–1990	1990–2000	2000–2010	2010–2020
Cropland	0.00%	0.06%	−0.20%	−0.15%
Forest	−0.01%	0.06%	0.34%	−0.14%
Grassland	0.06%	−1.44%	0.28%	0.44%
Water body	−0.20%	−0.11%	1.21%	0.84%
Construction land	0.05%	0.25%	0.17%	1.14%
Unused land	0.00%	−0.27%	106.20%	26.36%

) show that from 1980 to 1990, the absolute value of single dynamics of water body in the rural areas of southern Henan was the highest at 0.2%, and the lowest rate of change was in cropland and unused land, indicating that the area of cropland was more stable, which is consistent with the characteristics of rural areas of southern Henan making it the main agricultural production area. Between 1990 and 2000, the rate of change in grassland was the highest, and between 2000 and 2010, the rate of change in unused land was the highest, reaching 106.20%. The change rates of unused land and construction land were higher from 2010 to 2020, at 26.36% and 1.14%, respectively, which is related to the continuous promotion in China of the beautiful countryside and rural revitalization in the region. The above data show that the cropland and forest began to show a gradual decrease trend, grassland, construction land, and water body showed a continuous increase trend, and the area of unused land also showed an increase trend. Along with the continuous decrease in production land and ecological land, living land in the rural areas of southern Henan has been increasing.

4.2. Analysis of Land Use Transformation in the Rural Areas of Southern Henan

(1)

Analysis of land use type transfer

The basic characteristics of the overall land use changes in the study area were explored by analyzing the structural quantity of land use and land dynamic attitude. The detailed change trends in each land use type in the region were derived by analyzing the transformation between the land use types. The results of the transfer matrix calculated by using Equation (2) (

Table 6. Land use transfer matrix of the study area from 1980 to 2020 (km²).

		2020
		Cropland	Construction Land	Forest	Water Body	Unused Land	Total
1980	Grassland	206.11	45.12	279.53	20.97	0.00	2705.27
	Cropland	34,823.14	1458.91	735.21	315.52	0.30	37,462.55
	Construction land	872.47	3154.44	7.47	6.03	0.00	4041.67
	Forest	442.76	48.81	11,358.68	45.56	3.71	12,101.55
	Water body	64.62	5.26	11.90	1540.59	0.00	1637.67
	Unused land	0.00	0.00	0.00	0.00	0.10	0.10
	Total	36,409.11	4712.54	12,392.78	1928.68	4.11	57,948.80

) show that the land use types in southern Henan changed more significantly from 1980 to 2020, and the change trend is the continuous transformation of production land and ecological land to living land, mainly from cropland, grassland, and forest to construction land, water body, and unused land. Among them, 1458.91 km² of cropland was transferred to construction land and 315.52 km² of cropland was transferred to water body, with transfer rates of 3.89% and 0.84%, respectively; for grassland, 206.11 km², 45.12 km², and 20.97 km² was transferred to cropland, construction land, and water body, at transfer rates of 7.62%, 1.67%, and 0.78%, respectively; and for forest, 442.76 km², 48.81 km², and 45.36 km² was transferred to cropland, construction land, and water body, at transfer rates of 3.65%, 0.40%, and 0.37%, respectively. The above analysis results show that the economic production methods in the study area have changed over 40 years. With the implementation of projects for poverty alleviation, beautification of the countryside, and rural revitalization, the rural areas of southern Henan have vigorously developed chestnut and other industries, and some traditional farming in southern Henan is changing to the cultivation of special products, while some ecological land is gradually being encroached upon due to urbanization.

In 40 years, the most significant change was to cropland, as the area decreased by 1.82%, and the sown area of food crops has gradually reduced, from 37,462.56 km² in 1980 to 36,410.15 km² in 2020. Cropland has mainly transformed to forest, construction land, and water body. Since 1978, China began to carry out the policy of internal reform and opening to the outside world, and the internal reform started from China’s rural areas. Especially after farmers met their needs for food and clothing, farmers have occupied cropland indiscriminately and used it to build new houses, resulting in a large number of residential areas and unused land. Since 2010, the rural areas in southern Henan have been promoting the construction of new rural areas, which has gradually transformed cropland into construction land. The area of forest has increased continuously by 0.51% over 40 years, while part of the original forest has been converted into cropland and water body, and conversion to construction land has also been occurring. During the 40 years of the study period, the second venture of forestry was carried out in southern Henan, and economic forests such as oil palm, chestnut, tea-oil tree, and tea tree were vigorously developed. Under the construction of key projects such as returning cropland to forest and water-body-containing forest construction, the area of forest continued to increase and the forest coverage rate rose continuously. Forest land has increased from 12,101.55 km² in 1980 to 12,393.78 km² in 2020. Over the 40 years, construction land has continued to increase by 1.16%, while the original construction land has mainly been converted to cropland and a small amount of land has been converted to forest and water body. The main reason for this is that since 2000, the legal obligation of “balance of cropland occupation and replenishment” in the new Land Management Law has been implemented in southern Henan, and the system of “occupying one and replenishing one” has been implemented for cropland occupied by township land use and village construction. Since 2000, southern Henan has gradually started the construction of new rural areas, formulated a master plan for the construction of new rural areas, and vigorously constructed rural towns.

(2)

Analysis of spatial transfer of land use

Driven by urbanization, industrialization, and social economy, land use in the rural areas of southern Henan has undergone large changes in the number and structure of types from 1980 to 2020, while the spatial changes in land use type shifts are also more obvious. In this study, we used ArcGIS10.6 (https://support.esri.com/zh-cn/) (accessed on 20 August 2022) to analyze the spatial transformation of land use classification in five periods, and obtained land use transformation maps for 1980–1990, 1990–2000, 2000–2010, 2010–2020, and 1980–2020 (Figure 5, Figure 6, Figure 7, Figure 8 and Figure 9).

From 1980 to 2020, land use conversion was mainly concentrated in the north, central region, and south of the study area. From 1980 to 1990, the spatial conversion of land use was concentrated in the central and southeastern areas, mainly regarding the conversion of watershed to cropland and grassland. As shown in Figure 7, the west side of Zhumadian city is the main area for the conversion of water body to grassland, and the northeast side of Xinyang city is the main area for the conversion of water body to cropland. From 1990 to 2000, the spatial conversion of land use was still concentrated in the central area, the west side of Zhumadian city (Figure 6), mainly for the conversion of grassland to cropland and forest, the conversion of cropland to construction land, forest, and water body, and the conversion of forest to cropland. From 2000 to 2010, land use conversion was mainly the conversion of cropland to construction land, forest, and water body, the conversion of construction land to cropland, and the conversion of forest to cropland. As shown in Figure 9, the conversion of cropland to construction land was more concentrated in the southern part of Xinyang city. From 2010 to 2020, the conversion of cropland and forest to construction land was obvious everywhere, and the conversion of forest to grassland was mainly concentrated in the central area of Nanyang (Figure 9).

In general, the spatial conversion of land use migrated from mountainous areas to the plain areas (Figure 7). The main reason for this is that there is a large difference in elevation across the region, and the plain areas, which are relatively open and have abundant water body resources, are suitable for people to live in. Especially in recent years, the continuous promotion of new rural construction and urbanization has led to the continuous conversion of forest and cropland to construction land, and reforestation and ecological restoration actions have helped maintain forest, but the trend of the decreasing grassland area has not yet been alleviated.

4.3. Evolutionary Changes in the Landscape Pattern

4.3.1. Analysis of Landscape Focus Shift

Using the mean center tool in ArcMap10.6 and combining Equations (3) and (4), the migration direction (Figure 10) and migration distance (

Table 7. Changes in center of gravity of various landscape types in the rural areas of southern Henan from 1980 to 2020.

		Cropland	Forest	Grassland	Water Body	Construction Land
1980–1990	Migration direction	South to East	North to West	North to West	North to West	South to West
	Migration distance (km)	1.1	0.81	1.96	0.35	0.1
1990–2000	Migration direction	South to East	North to West	North to West	North to East	South to East
	Migration distance (km)	3.03	11.6	1.39	2.08	0.36
2000–2010	Migration direction	South to East	South to West	North to West	South to East	North to West
	Migration distance (km)	16.97	11.76	0.28	7.06	2.2
2010–2020	Migration direction	North to West	North to West	North to West	North to West	North to West
	Migration distance (km)	6.02	38.62	0.58	3.25	1.98

) were calculated for each land use type in the study area in 1980, 1990, 2000, 2010, and 2020. From 1980 to 2020, the center of gravity of forest in the study area shifted significantly, with a shift of 61.45 km to the west-northwest. The center of gravity of cropland shifted 21.02 km to the east–south direction from 1980 to 2010, and 6.02 km to the north–west direction from 2010 to 2020. The center of gravity of water body shifted 0.35 km to the west–north direction from 1980 to 1990, and 2.08 km to the east–north direction from 1990 to 2000. From 2000 to 2010, the center of gravity of water body shifted 7.06 km to the east–south direction, and from 2010 to 2020, it shifted 3.25 km to the west–north direction. The center of gravity of grassland and construction land shifted 4.11 km and 3.9 km, respectively, during the 40 years, with relatively slow changes. The ecological spatial center of gravity has shifted due to the continuous expansion of rural construction land, the continuous disturbance of human activities, and the destruction of the ecological environment in southern Henan since the reform and opening up, which may have led to the exploitation of grassland and soil erosion.

4.3.2. Landscape Pattern Change Characteristics at the Type Level

From the changes in different landscape types (Figure 11), the class area (CA) of cropland has decreased year by year from 1980 to 2020, but cropland is still the dominant landscape. Its number of patches (NPs) does not change much, the landscape shape index (LSI) gradually increases, and the aggregation index (AI) significantly decreases. This indicates that the modernization, urban expansion, and changes in the structure of agricultural development in the study area have had a certain impact on cropland. During the study period, the CA of forest increased in general, NPs and AI decreased slightly, and LSI showed an increasing trend. In addition to cropland, forest is also one of the dominant landscapes in rural areas in southern Henan. In the past 40 years, the fragmentation degree of forest landscape has gradually decreased, but the decline rate has been relatively slow. This is related to the long-term development of closed mountains, afforestation, and tree planting in southern Henan, which play an important role in supporting ecological security maintenance, biodiversity conservation, water and soil conservation, water conservation, and ecological environment improvement in southern Henan. The CA and NPs of construction land are both decreasing first and then increasing, and AI is showing a continuous growth trend. Especially in the past 20 years, the types of construction land have continued to increase, and its fragmentation and aggregation are also gradually increasing. The expansion of construction land has caused a certain impact on the ecological environment of southern Henan. It can be seen from the change trend in CA, NPs, and LPI in the water area that the water area was comprehensively affected by various factors such as hydrological changes and human activity interference from 1990 to 2010, resulting in an increase in fragmentation, but patches in large areas of water area were relatively concentrated. The NPs, LSI, and CA of grassland are gradually increasing, while AI is generally decreasing, indicating that the area and fragmentation of grassland are increasing with the acceleration of rural construction in this area. The CA and LSI of the unused land in the study area showed an overall increase trend, AI showed an overall decrease trend, and NPs and CA tended to be zero, indicating that the CA and LSI of the unused land patches continued to rise, and the degree of fragmentation continued to increase, becoming a landscape type with very little advantages in the rural areas of southern Henan.

4.3.3. Landscape Pattern Change Characteristics at the Landscape Level

In the past 40 years, the characteristics and changes in landscape pattern index in the rural areas of southern Henan province have been obvious (

Table 8. Characteristics of landscape level index in the rural areas of southern Henan from 1980 to 2020.

Years	Landscape Shape Index (LSI)	Contagion Index (CONTAG)	Landscape Division (DIVISION)	Shannon Diversity Index (SHDI)	Shannon Evenness Index (SHEI)	Aggregation Index (AI)
1980	126.9028	66.7403	0.939	1.0387	0.5797	96.9219
1990	127.3063	66.7426	0.9376	1.0382	0.5794	96.9118
2000	129.0336	67.0957	0.9387	1.0243	0.5717	96.8697
2010	133.2275	66.2891	0.9339	1.0483	0.5851	96.7658
2020	139.5073	65.3389	0.9385	1.0755	0.6003	96.6081

and Figure 11). The landscape shape index (LSI) continued to increase from 1980 to 2020, and each landscape type gradually dispersed and increased its dispersion. The contagion index (CONTAG) first increases and then decreases, indicating that the aggregation degree of each landscape type during 1980 to 2020 first increases and then decreases sharply. The aggregation index (AI) shows a continuous decreasing trend, and the degree of patchy connectivity keeps decreasing. The SHDI emphasizes the contribution of rare patch types to the information and can reflect the heterogeneity of the landscape. Between 1980 and 2020, both SHDI and SHEI in southern Henan first decreased and then increased, and the most significant changes were observed between 2010 and 2020, indicating that the landscape uniformity and heterogeneity have shown a gradual increase in recent years. Combined with the analysis of area changes above, because forest is the dominant landscape type in the rural areas of southern Henan, its area first increases and then decreases, which influences the change in SHEI in the area. The landscape division (DIVISION) changed most significantly between 2000 and 2010 and between 2010 and 2020, showing a sharp decrease and a sharp increase, respectively, with the lowest fragmentation of patch composition within the landscape in 2010.

In general, the overall landscape fragmentation has increased, the landscape connectivity has decreased, and the evenness has also increased heterogeneously, indicating that the development of urban and rural residential land, public facility land, industrial land, and transportation facilities has led to the fragmentation of each landscape type and thus the irregularity of patches (Figure 12).

4.4. Analysis of the Drivers of Landscape Pattern Change

4.4.1. Geographical Exploration Results and Analysis

From

Table 9. Factor detection values.

Factor Type	Driving Factor	q (Explanatory Power)	p (Significance)
Socio-economic factors	Population density (X1)	0.086	0.000
	GDP (X2)	0.084	0.000
	Night lighting (X3)	0.011	0.045
Topographical factors	Elevation (X4)	0.112	0.000
	Slope (X5)	0.135	0.000
Climate factors	Average annual temperature (X6)	0.088	0.000
	Average annual precipitation (X7)	0.063	0.000
Location factors	Distance from major railroads (X8)	0.026	0.000
	Distance from major roads (X9)	0.032	0.000
	Distance to third-order stream and above (X10)	0.004	0.453

and Figure 13, it can be seen that topographic factors such as slope (0.135) and elevation (0.112) have the greatest influence on landscape pattern change with an average contribution of 12.35%, followed by climatic factors with an average explanatory power of 7.55%. Location factors have the least influence on landscape pattern change with an average explanatory power of only 2.07%. Among socio-economic factors, population density, and GDP have the higher explanatory power, 8.6% and 8.4%, respectively, and the explanatory power of night lighting is much lower at 1.1%.

In the results of interaction detection, 15 groups of factors with explanatory power above 0.05 were selected for analysis, and the results showed (

Table 10. Q value of factor interaction and corresponding interaction relationship.

Driving Factor	q	Interaction
X1∩X2	0.133	Two-factor enhancement
X1∩X4	0.153	Two-factor enhancement
X1∩X5	0.172	Two-factor enhancement
X1∩X6	0.134	Two-factor enhancement
X1∩X7	0.138	Two-factor enhancement
X2∩X4	0.139	Two-factor enhancement
X2∩X5	0.160	Two-factor enhancement
X2∩X6	0.125	Two-factor enhancement
X2∩X7	0.126	Two-factor enhancement
X4∩X5	0.153	Two-factor enhancement
X4∩X6	0.121	Two-factor enhancement
X4∩X7	0.151	Two-factor enhancement
X5∩X6	0.153	Two-factor enhancement
X5∩X7	0.159	Two-factor enhancement
X6∩X7	0.129	Two-factor enhancement

) that the interaction between any two factors showed a two-factor enhancement, and there was no mutually independent or weakened relationship. That is, the interaction of any two factors had a greater impact on the landscape pattern change than a single factor, and the landscape pattern evolution was influenced by multiple factors acting together. As a result, the higher the interaction q value, the greater the degree of influence of the interaction between its corresponding two factors. The interaction between socio-economic factors and topographic factors is strong, with the highest q value being 0.172 for the interaction between population density and slope, followed by the strong interaction between topographic factors and climatic factors, with the q value of the interaction exceeding 0.15.

4.4.2. Analysis of Regression Results of Each Driver and Land Use Type

According to the ROC evaluation results, all models had ROC values > 0.7, indicating that the analysis of individual landscape type change drivers using logistic regression models was accurate and reliable. After removing the independent variables whose variable tests exceeded 0.05, the regression results of each driver and land use type are shown in

Table 11. Logistic regression analysis results.

Type of Land Use	Independent Variable	Regression Coefficient (β)	Standard Error (SE)	Statistics (Wald)	Significance (sig)	Incidence Rate (Exp)
Cropland	Night lighting (X3)	0.361	0.083	18.668	0.000	1.434
	Elevation (X4)	0.012	0.002	22.750	0.000	1.012
	Average annual temperature (X6)	1.057	0.452	5.460	0.019	2.878
	Average annual precipitation (X7)	0.002	0.001	6.998	0.008	1.002
	Constants	−24.553	7.622	10.377	0.001	0.000
Forest	Population density (X1)	−96.497	49.041	3.872	0.049	0.000
	Slope (X5)	0.112	0.055	4.213	0.040	1.119
	Average annual precipitation (X7)	0.004	0.002	3.927	0.048	1.004
	Constants	21.061	16.759	1.579	0.209	1.401

.

The significance test of the regression coefficients uses the Wald statistic, and if the Wald statistic of a driver is larger, it is considered that the influence of that driver on the land use type change is more significant. The regression coefficient β has positive and negative values, which indicate the direction of each driver X on the land use type change. As can be seen from the table, the dominant drivers of cropland change in the study area from 1980 to 2020 are elevation > night lighting > average annual precipitation > average annual temperature, in that order, and the transformation of cropland is positively correlated with these drivers, indicating that the probability of transforming cropland into other land use types increases with the increases in elevation, temperature, and precipitation and the enhancement of night lighting. The dominant drivers of forest change are slope > average annual precipitation > population density, in that order. Forest transformation is negatively correlated with population density, indicating that the probability of forest change is small in areas with high population density, and forest transformation is positively correlated with slope and average annual precipitation, indicating that the increase in slope and precipitation has a facilitating effect on the transformation of forest into other landscape types.

5. Discussion

5.1. Landscape Pattern Changes Caused by Land Use Transition

The land transformation caused by social and economic development and expansion of construction land leads to land use change and intensification [2], and also has an impact that cannot be ignored on the regional ecological environment [5]. At present, most scholars focus on the study of land use change [34], or explore the law of land use landscape pattern evolution and the characteristics of spatial–temporal heterogeneity [35], but the study of landscape pattern change caused by land use transformation has not been paid much attention. Based on this, this paper analyzes the landscape pattern change characteristics of the main landscape types in the rural areas of southern Henan, and the landscape pattern in the study area is changing with the transformation of land use, indicating that productivity agriculture and land abandonment can co-exist in the spatial difference pattern [36]. The change in land use in the rural areas of southern Henan in the past 40 years reflects the transformation of land use and the transformation of landscape pattern caused by it. Its fragmentation, dominance, landscape shape, and diversity can be reflected by the landscape pattern index. Driven by rapid urbanization and socio-economic development, the land use transformation in the rural areas of southern Henan has been frequent and complex in the past 40 years. In the past 40 years, with the development of unused land, the reduction in cultivated land and the continuous increase in construction land, the landscape pattern has changed greatly and the fragmentation, uniformity, and heterogeneity of the landscape have increased, while the overall connectivity of the landscape has decreased. The center of gravity of ecological space has also moved to the south as a whole. In particular, the area of forest landscape in the high-altitude rural areas of southern Henan has increased, the valley areas and the cultivated land at higher altitudes have been converted to farmland, the economic forest and forest landscape have gradually formed, and the urban and village landscape in the high-altitude areas has gradually shifted to the valley or gentle slope and flat dam areas, which has greatly improved the living environment and convenience of people’s lives.

Therefore, the landscape pattern transformation mode in rural areas in southern Henan mainly includes three types: (1) The pattern dominated by cultivated land landscape changes to the pattern of coexistence of multiple landscapes; this transformation mode mainly occurs in the valley area. The valley in southern Henan is less affected or restricted by the terrain, and the rapid development of urbanization and social economy makes its landscape shape gradually more complex, and the landscape diversity and heterogeneity continue to increase. Finally, the landscape pattern originally dominated by cultivated land types began to change to a landscape pattern with multiple land use types coexisting at the same time. (2) The pattern of coexistence of multiple landscapes is changing to the landscape pattern dominated by forest land; in mountainous and hilly areas with high altitude, this transformation pattern is mainly used. The main reason for this is that the degree of landscape fragmentation in mountainous and hilly areas is much smaller than that in valley areas, and the landscape diversity and heterogeneity are also low. (3) The cultivated land landscape is gradually changing to economic forest and forest landscape; since the implementation of returning farmland to forest in southern Henan is related to the adjustment of agricultural planting structure in the past 40 years, this transformation mode in southern Henan mainly focuses on the conversion of cultivated land landscape to forest land landscape, and the increase in forest land also contributes to the improvement in the ecological environment and the improvement in ecosystem service function, to a certain extent.

In the past 40 years, the transformation process of land use and landscape pattern in the rural areas of southern Henan has played an important role in the structural and functional transformation of the future agricultural ecosystem, helping to alleviate the pressure of farmland protection in southern Henan, promote the development of rural economy, improve the service function of rural ecosystem, improve human welfare, make rural ecological governance more effective, and promote sustainable improvement in the regional ecological environment. At present, the land function pattern of “ecological function dominant” and “ecological production function dominant” in the south of Henan province also shows that, like most areas in China, the transformation of cultivated land function, conversion of farmland to forest, afforestation, and other measures have continuously made the land space greener and achieved significant ecological benefits [37].

5.2. Analysis of the Driving Mechanism of the Gradient Evolution of the Landscape Pattern

The transformation of rural land use patterns is closely related to the socio-economic development stage of the region [38]. Generally, industrial structure adjustment and economic development have a direct impact on land use structure, which further leads to the evolution of the regional agricultural landscape pattern [39], just as the phenomenon of abandoned farmland in the world has caused the change in rural landscape [40]. The transformation process of land use type and the evolution process of landscape pattern are interrelated and inseparable, and both are affected by multiple factors such as natural environment, land use mode, and government decision making [41]. Changes in the distribution of landscape patterns in the study area are the result of a combination of multiple factors, including rural socio-economic–ecological systems and the external environment [21,42], and are generally driven by socio-economic, natural, and policy factors, mainly in the following areas (Figure 14).

(1)

Natural environmental factors: Natural environmental factors such as temperature and precipitation have a significant impact on crop planting and forest vegetation growth in the rural areas of southern Henan. Unstable natural environmental factors will affect the spatial distribution of farmland landscape types and forest landscape types, and ultimately affect the change in landscape pattern in the region.

(2)

Terrain factors: The terrain factors such as elevation and slope also play an important role in determining the distribution of cultivated land and farmland in the rural areas of southern Henan. This is mainly because the slope can directly affect the distribution of natural factors such as water, temperature, and light, thus affecting the flow of material and energy, the intensity and frequency of interference, and the occurrence of natural disasters in the region, thus changing the landscape pattern in the region.

(3)

Socio-economic factors: Socio-economic factors such as population density and night light are the main driving factors that affect the distribution of forest land and cultivated land, respectively. The increase in population and the rapid development of urbanization (night lights indicate the degree of urbanization) have promoted the improvement of various infrastructure in the rural areas of southern Henan, resulting in an increase in the demand for construction land, and part of forest land and farmland may be encroached on in large quantities.

(4)

The policy of returning farmland to forests and the development of economic forests: In recent years, the South of Henan province has vigorously implemented the policy of returning farmland to forests and, at the same time, it has given active policy support and guidance to the development of economic forests. In particular, the increasing demand for various types of seedlings has led to the rapid growth of the planting scale of economic forests in the south of Henan province, thus promoting the continuous transformation of cultivated land landscape to forest landscape.

(5)

Farmers’ livelihood transformation: With the rapid development of urbanization in China, a large number of agricultural labors in rural areas of southern Henan province continue to be exported, resulting in the abandonment of a large number of local arable land and the transformation of land use types such as grassland and forest land, and also resulting in the degradation of rural agricultural ecosystems and the decline of social economy in rural areas.

(6)

A rural land use model with win–win ecological and economic benefits: In recent years, most farmers in the rural areas of southern Henan have gradually transformed to have non-agricultural livelihoods, which mainly comes from the rural young and middle-aged labor force going out to work, eventually leading to a significant change in the agricultural production mode. In particular, economic forests such as melon and fruit picking gardens, oil plant plantations, and medicinal plant plantations continue to increase, and a large number of cultivated land is transformed into forest land. While increasing economic benefits, it is also conducive to local water and soil conservation, water conservation, biodiversity conservation, leisure tourism development, and an improvement in the human ecological environment, so as to achieve the goal of win–win ecological and economic benefits.

(7)

The comprehensive implementation of the “rural revitalization” strategy: The comprehensive implementation of China’s “rural revitalization” strategy, especially the massive construction of rural infrastructure and the change in agricultural production mode, on the one hand, has increased farmers’ incomes, improved rural living environment, and improved human well-being; on the other hand, it has also triggered the continuous change in land use mode.

5.3. Relevance of Land Use and Landscape Pattern Transformation in the Study Area

Exploring the transformation of the rural landscape pattern and its driving factors in southern Henan helps clarify the landscape pattern dynamics and land use transformation paths in typical rural areas of China, and provides a scientific basis for the future development of rural agriculture [21,43]. The evolution of the landscape pattern in the study area reflects the transformation of rural cropland from the traditional single function and crude operation to a modern agricultural society with diversified functions and spatial intensification. The transformation of cropland use in the study area tends to shift from cropland to forest and economic forest, and always aims at ensuring ecological benefits. In the process of land remediation, both food and economic crops can be planted to improve the quality of cropland, reduce soil erosion, increase farmers’ incomes, improve farmers’ motivation to carry out land remediation, improve the ecological condition, and reduce soil erosion. The report of the 19th National Congress of the CPC(Communist Party of China) also clearly put forward the strategy of “rural revitalization” and the impact of land remediation on the human–land system in rural areas, emphasizing the revival of rural life and the restoration and planning of rural ecology on the basis of the previous emphasis on agricultural development, and promoting rural transformation and revitalization [44,45]. Therefore, the development of economic forests provides direction for the transformation of agriculture in the study area, improves the quality and utilization efficiency of rural land, and can guide the sustainable development of modern agriculture and optimization of landscape patterns in the study area.

This study on the landscape pattern of rural areas in southern Henan can enrich research of rural ecology and provide guidance for future land use and ecological security planning in southern Henan. Significantly, due to the scope and purpose of the study, the classification of the six land use types has a different focus, and this study focuses on grasping the overall conversion direction of each category from a macroscopic perspective, while the grasp of microscopic changes has certain limitations. In the future, high-resolution remote sensing image data can be used to further explore the change rules and driving forces of land types at the micro level on the basis of further refinement of land types. At the same time, this study still has the following two deficiencies, which need to be further improved in future research. First, the remote sensing image data sources and shooting time used in each year are different. Although the accuracy has met the basic requirements after verification, and the impact on the research results is also small, the error is still objective. Secondly, the two-dimensional landscape index is used in this study. It is suggested to further collect data and professional opinions in the future to more accurately reflect the evolution characteristics of the vertical landscape pattern in the study area.

6. Conclusions

This paper selects rural areas in southern Henan province as the research object, combines five high-definition image data, and uses the landscape pattern index, transfer matrix, and center of gravity transfer model to analyze the process of land use transformation, the basic law of landscape pattern evolution, and its driving factors in rural areas in southern Henan province.

From 1980 to 2020, the overall change in landscape types in rural areas in southern Henan was relatively obvious. The change characteristics can be summarized into three types: (1) stable type: the two types of unused land and grassland belong to this type, and the change range of both types has been relatively small in 40 years; (2) decreasing type: the cultivated land belongs to the typical declining type. Since 1980, the cultivated land has been continuously reduced and mainly transferred to the landscape types, such as construction land, forest land, and water area; (3) incremental type: from 1980 to 2020, the area of forest land, construction land, water area, and other landscape types in southern Henan showed an overall increasing trend.

From 1980 to 2020, influenced by the urbanization level, elevation, slope, population density, and precipitation, the landscape pattern in rural areas in southern Henan changed significantly, and the “production” landscape pattern gradually changed to the “ecological economy+ecological adjustment” landscape pattern, which also reflects the importance of China’s ecological environment and the implementation effect of relevant specific measures. The focus of landscape transformation is mainly reflected in cultivated land, construction land, and forest land. The cultivated land landscape is mainly transformed into forest land landscape and artificial landscape, and the main driving factors for the transformation of cultivated land include elevation, temperature, precipitation, and night light. The change in forest land is closely related to slope, annual average precipitation, and population density.

Social and economic development and agricultural policies play an important role in promoting the transformation of land use and the evolution of rural landscape pattern. As an important transitional zone in the north-south region of China, the expansion of urban land and social production activities in the rural areas of southern Henan province have brought about a greater negative impact on the regional ecological environment, especially regarding the reduction in the area of forest land and other important ecosystems, reducing the supply capacity of ecosystem services in the region.