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Article

Land Use/Land Cover Changes in Baicheng District, China during the Period 1954–2020 and Their Driving Forces

by
Bin Peng
1,2,
Jiuchun Yang
1,*,
Yixue Li
2 and
Shuwen Zhang
1
1
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
2
College of Resources and Environment, Shandong Agricultural University, Taian 271018, China
*
Author to whom correspondence should be addressed.
Land 2023, 12(10), 1845; https://doi.org/10.3390/land12101845
Submission received: 15 August 2023 / Revised: 23 September 2023 / Accepted: 26 September 2023 / Published: 27 September 2023
(This article belongs to the Special Issue Assessment of Spatial and Temporal Landscape Patterns under Land Use Change)
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Abstract

:
Temporal and spatial variations in land use/land cover (LULC) and their driving factors are direct reflections of regional natural and anthropogenic impacts. To explore the pathways for green upgrading development in ecologically fragile areas, this study focused on Baicheng, located in the northern agropastoral transition zone, China. Based on the topographic map of 1954 and Landsat remote sensing images taken from 1976 to 2020, the spatial distribution of LULC data for the study area in 1954, 1976, 1988, 2000, 2010, and 2020 was obtained. The temporal and spatial characteristics of LULC changes and their driving factors under the combined influence of human activities and climate were analyzed using dynamic degree, flowchart, spatial analysis, and principal component analysis. The results indicate that (1) the dominant LULC type in Baicheng is cropland. By 2020, dry land accounted for over 41% of the total area, while the area of saline–alkaline land increased the most, and grassland decreased most drastically. (2) The dynamic degree of different LULC types ranked from highest to lowest as follows: paddy field > unused land and other types > woodland > saline–alkaline land. (3) LULC Changes in Baicheng were mainly influenced by human activities and economic development, especially regional gross domestic product and the sown area of crops. These research findings can provide a scientific basis for formulating sustainable development and protection strategies to ensure regional green upgrading development.

1. Introduction

Land use/land cover (LULC) changes are a direct reflection of the multiple interactions among natural environmental changes, socioeconomic development, and policies [1,2]. Over the past few decades, with the increase in population and the acceleration of urbanization, the transition from grassland, woodland, and marshland to cropland and construction land has sharply increased [3,4]. While these changes have significantly improved people’s quality of life, they have also led to various environmental problems such as soil erosion, water pollution, soil degradation, landscape fragmentation, and biodiversity loss, threatening global ecological security and sustainable development [5,6]. Especially in ecologically vulnerable areas, the combined effects of climate change and human activities are particularly prominent [7,8,9]. Against this backdrop, balancing ecological environment and human demands has always been a challenging issue [10]. Deeply revealing the changes in LULC and their driving mechanisms is fundamental to clarifying the relationship between regional socioeconomic development and ecological environment utilization and protection, which is crucial for exploring the pathways of regional green upgrading development.
The advancement of satellite Earth observation technology and the increase in the number of satellite images have offered extensive prospects for global LULC research. Since the launch of the first earth observation satellite in 1972, remote sensing technology has been widely used in monitoring and mapping temporal and spatial changes in LULC [11,12,13,14,15]. Over the past few decades, based on global multisource satellite data products, there has been a trend of increasing monitoring scales and continuously improving temporal and spatial resolutions, realizing LULC monitoring from regional to global scales [10,16,17], and from meter- to kilometer-level resolution, as well as regional and global land use monitoring [10,18]. For instance, Friedl et al. utilized MODIS data to map global LULC based on supervised classification methods [19]. Lunetta et al. used MODIS NDVI data and change detection techniques to automatically monitor the transition of agricultural land to nonagricultural cover types [20]. Hilker et al. employed fusion techniques on Landsat and MODIS data, effectively enhancing the temporal resolution of LULC change monitoring [21]. Gong et al. utilized Sentinel-1 synthetic aperture radar data to assess the annual maps of global impervious surface areas from 1985 to 2018 [22]. The aforementioned studies confirm the widespread application of remote sensing technology in the LULC domain. However, due to the lack of long-term remote sensing monitoring data, the temporal scope of these studies mainly traces back only to the years when remote sensing images became available. It is challenging to elucidate the complex transition process and its driving factors from periods with minimal influence from human activities and policies to the current era, where these impacts are significantly pronounced.
Since the 1990s, with the continuous intensification of human activities, the contradiction between economic development and the ecological environment has become increasingly prominent. LULC research has become a global research hotspot [23]. From the analysis of LULC spatial–temporal patterns [24,25,26] and explorations of LULC change driving mechanisms [27,28], the research has evolved to focus on the impact on ecosystem services [29,30], future LULC simulation studies [31,32,33,34], and more detailed analyses of human activities, policies, and other LULC driving mechanisms [35]. In terms of research scale, there have been numerous studies at global, continental, and transnational levels. For example, Foley et al. believed that the challenge facing global land use is how to balance human needs with the long-term ability of the biosphere to provide ecosystem services [10]. Zhao et al. found that rapid changes in land use in Asia over a short period have led to a series of negative environmental consequences [16]. Li et al.’s study indicated that the expansion of farmland and rapid urbanization in Central Asia has exacerbated LULC changes, significantly impacting ecosystem services [17]. Some studies focus on one or several types of land use to illustrate changes in specific areas. For instance, Li et al. used GIS and RS technology to comprehensively study the expansion of saline–alkaline wastelands in Da’an city, a typical salinization area in Northeast China [36]. Li et al., using Changchun Kuancheng as a case, employed a patch-scale field assessment system to analyze the dynamic changes in cultivated land at the urban–rural junction from 2004 to 2014 [37]. Bagan et al. evaluated the landscape features of the Horqin Desert, the changes in the area of protective forests from 1975 to 2007, and the influence of climatic factors on desert changes [14]. Other studies cover all types of land use, exploring the spatial pattern and temporal characteristics of LULC in Northeast China from a holistic perspective. For example, Pu et al. analyzed the land use change features in western Jilin over nearly 40 years [38]. Yang et al. integrated bitemporal change monitoring and temporal trajectory analysis methods to track the LULC change paths of each location in western Jilin [33]. Li et al. took the western part of Jilin province as the research area and analyzed the relationship between land use change and population dynamics from 1975 to 2010 [39]. The results showed that with the increase in population density, land use dynamics exhibited exponential growth, and the relative changes in land use of woodland, grassland, construction land, and wetlands were directly proportional to the changes in population density. However, past research generally considered short-term LULC changes, leading to certain uncertainties and challenges in understanding LULC changes, future development planning, and policy formulation.
LULC changes result from the combined effects of various driving factors, and different factors can lead to changes in LULC. Studying the relationship between LULC changes and influencing factors is crucial for addressing issues related to the land system [40]. Research indicates that natural elements and economic factors are the primary drivers of LULC changes [41]. Their impact can be analyzed from both macro and micro perspectives. At the macro scale, climate change and human activities are the main drivers of LULC changes, and they have cumulative effects. At the micro scale, the primary drivers include national policies, decisions and behaviors of land users, and interactions between different land use types [42]. The combination of these two has become a current research hotspot. Research methods have diversified. Earlier studies were primarily qualitative analyses; however, with the introduction of mathematical and statistical analysis methods, including principal component analysis (PCA), logistic regression models, and multiple regression models [23,40,41], these models can quantify the driving effects of LULC change drivers and have thus been widely applied.
The “beautiful China” concept refers to the implementation of national social, economic, and ecological construction in territories with different primary functions during a specific period. The aim is to achieve comprehensive sustainable development goals in terms of economic growth, environmental friendliness, and social progress [43]. The report of the 19th National Congress of the Communist Party of China explicitly stated that the construction of a “beautiful China” is an important practice to fulfill the “2030 Agenda for Sustainable Development” [44]. The construction process of a “beautiful China” represents a concrete form of the man–land system and is an essential means to achieving regional coordinated development. However, achieving this goal is not easy, especially in the northern agropastoral transition zone that lies in the transitional region from semi-humid to semiarid and arid climates. This region is highly sensitive to climate change and human activities, representing a classic area with prominent man–land contradictions and severe land degradation [33,45]. The long-standing extensive resource development model has caused increasing contradictions between economic and social development and ecological environment protection in this area [46]. The goal of a “beautiful China” is threatened, and the region has become one of the 14 contiguous poverty-stricken areas in the country, facing daunting tasks in poverty alleviation [47]. The land use and landscape patterns in the region are undergoing continuous and complex changes. The country has successively implemented major ecological projects such as the Three-North Shelter Forest Program in recent years, returning farmland to forests and grasslands, and controlling sand sources; ecological environment quality has been steadily improving. However, too much emphasis on ecological benefits during management while neglecting economic benefits has led to many measures not being sustainable in the long term, and their effects are not stable [48,49,50]. Therefore, there is an urgent need for continuous restoration technologies for degraded land based on regional resource-carrying thresholds and a green development model that considers regional economic coordinated development. Understanding the LULC change process and its driving factors since periods of minimal human interference in the region is essential for assessing regional resource-carrying thresholds and formulating green development approaches.
In recent years, research on LULC changes in the northern agropastoral transition zone has mainly focused on LULC changes and driving mechanisms throughout the region. Studies specifically using the agropastoral transition zone and “beautiful China” as entry points and based on RS and GIS for quantitative analysis of LULC changes in specific areas, are relatively rare. Particularly, there is a notable lack of intuitive and effective data analysis for long-time series LULC changes and their driving factors. Baicheng is a typical region in the northern agropastoral transition zone. It is an essential strategic node for the national implementation of the “Belt and Road Initiative” and the promotion of opening up to the north in Jilin Province. Baicheng is a crucial base for national commodity grain and livestock production, playing a vital role in ensuring national energy and industrial security. Therefore, this study selects Baicheng district as the research object. Based on the LULC data from 1954 to 2020, it clarifies the spatiotemporal changes of LULC in Baicheng over the past 70 years. Integrating key data on social development, economy, and policies, this research elucidates its driving factors in detail. This study aims to identify the challenges faced by ecologically vulnerable areas in achieving the “beautiful China” goal, formulate corresponding sustainable LULC and protection strategies, and provide a scientific basis to ensure the region’s green development and upgrade.

2. Study Area

In terms of natural geographical features and developmental history, Baicheng city can be regarded as a representative microcosm of western Jilin, China. Baicheng is situated in northwestern Jilin province, China (44°13′57″–46°18′ N, 121°38″–124°22′ E). The city has a total population of 2.032 million and covers an area of 26,000 km2. The current administrative divisions include Taobei district, Tongyu county, Zhenlai county, Taonan city, and Da’an city (Figure 1). The terrain consists of low mountains and hills in the northwest, extending to plains in the southeast. The city lies in a temperate continental monsoon climate, with a crop growing season from May to September, receiving a rainfall of 355.6 mm, which accounts for 88% of the annual precipitation, with the annual average being 399.9 mm. There are numerous river basins, occupying 26.7% of the province’s water area. The wind energy resources within the jurisdiction make Baicheng the area with the most potential for wind energy storage in Jilin province. The region also has abundant sunlight, indicating a high potential for both wind and solar energy development. Due to natural factors and human activities, issues like soil salinization, marshland, and grassland degradation are severe. However, with the implementation of ecological protection, restoration measures, policies, and strategies to increase food production, there has been an improvement in the irrational land use structure of Baicheng, as well as in the conditions of soil salinization, grassland degradation, land desertification, and wetland shrinkage. The city is actively exploring ways for green development and upgrading, aiming to achieve the goals of “beautiful China”.

3. Data Sources and Research Methods

3.1. Data Sources and Processing

3.1.1. Source of Land Use/Land Cover Data

Our research team previously utilized the 1:100,000 scale topographic maps published in 1954 and employed the historical land use reconstruction model (HLURM) for reconstruction, extending the earliest data acquisition of LULC back to 1954 [51,52].
Furthermore, our team extracted the LULC data from 1976 to 2020 via visual interpretation. These data serve as part of the national-scale 1:100,000 multitemporal LULC remote sensing monitoring database. The dataset has been made publicly available at the resource and environment science and data center (RESDC) (https://www.resdc.cn/ (accessed on 24 May 2021)), and has been extensively applied in various studies [11,13,51].

3.1.2. Acquisition of Driving Factor Data

Socioeconomic data are mainly derived from the “Compilation of 60 Years of Agricultural Development Data in Jilin” [53], “60 Years of Jilin” [54], and “Jilin Statistical Yearbook” [55], as well as information from the Jilin government website and the Baicheng government website. The data for average temperature and precipitation from 1954 to 2020 are sourced from the national meteorological science data center of the China meteorological data network (http://www.nmic.cn/ (accessed on 6 July 2021)).

3.2. Research Methods

Based on the preliminary research on LULC changes in the study area and the data acquired from the region, methods such as transition matrix, dynamic degree, and spatial analysis were employed. LULC changes were monitored at six time points: 1954, 1976, 1988, 2000, 2010, and 2020. Lastly, the driving factors behind the LULC changes were analyzed from both natural and socioeconomic perspectives using PCA. The research workflow is illustrated in Figure 2.

3.2.1. Preprocessing Methods

Due to the abundance of original LULC categories, most LULC types in Baicheng account for a relatively low proportion, making it challenging to reflect the trend changes of all LULC types. Hence, there is no necessity to conduct detailed analysis on every LULC type. In light of Baicheng city’s regional characteristics, this study categorizes LULC types into paddy field, cropland, woodland (including forested land, shrub land, sparse woodland, and other types of woodland), grassland (encompassing high, medium, and low coverage grasslands), waters (comprising rivers, lakes, ponds, and tidal flats), construction land (including urban areas, rural residential areas, and other construction lands), sandy lands, saline–alkaline land, marshland, and others (including bare soil and bare rocky gravel land). All LULC projection coordinate systems are unified to WGS84_Albers using ArcGIS10.2.

3.2.2. Descriptive Statistics

The descriptive statistical analysis was employed to assess the area and percentage of LULC in Baicheng across all periods. The change rate of LULC area was calculated to reveal the pattern and trend of LULC changes in Baicheng during all periods. The formula is as follows:
S i = A i A × 100 %
where S i represents the proportion of the area of the i -th LULC type within a certain period, A i denotes the area of the i -th LULC type within that period, and A is the total area of LULC.

3.2.3. Changes in Land Use/Land Cover Structure

The LULC type transition matrix is used to describe the mutual transformation relationship between LULC types in a certain research area, which can reflect the structure and source of LULC types. This transformation relationship can understand the change characteristics of each LULC type before and after the transition. The expression as follows:
A i j = A 11 A 12 ⋯ A 1 n A 21 A 22 ⋯ A 2 n ⋮ ⋮ ⋯ ⋮ A n 1 A n 2 ⋯ A n n
where A represents the area, i represents the LULC type at the beginning of the study, j represents the LULC type at the end of the study, and n is the number of LULC types.

3.2.4. Changes in the Quantity of Land Use/Land Cover

The speed of LULC change can be measured using the LULC dynamic degree model, which is divided into single LULC dynamic degree and comprehensive LULC dynamic degree.
1.
Single LULC dynamic degree
The single LULC dynamic degree is used to represent the change in the quantity of a certain land use type in a certain research area over a certain time range [41], and its formula is:
K = U b − U a U a × 1 F × 100 %
where K is the dynamic degree of a specific LULC type. U b is the area of a certain LULC type at the end of the study period. U a is the area of a certain LULC type at the beginning of the study period. F represents the annual change rate of a certain land use type in the study area.
2.
Comprehensive LULC dynamic degree
The comprehensive LULC dynamic degree is used to represent the change rate of all land use types in the research area [56], and its formula is:
L C = ∑ i = 1 n ∆ L U i − j 2 ∑ i = 1 n L U i × 1 F × 100 %
where L C represents the LULC dynamic degree of the study area. ∆ L U i − j is the absolute value of the area of the i -th land use type during the study period. L U i is the area of the i -th land use type at the beginning of the study period. F represents the annual interval and can be expressed as the annual change rate.
The LULC changes at the same location vary over different periods of time. In order to more intuitively represent the intensity of LULC changes each year, we created a grid of 3 km × 3 km and overlaid all the LULC data for each year, calculating the comprehensive land use dynamics within each grid to reflect the intensity of LULC changes at the same location during the research period.

3.2.5. Research Method for Land Use/Land Cover Change Driving Factors

This study adopts the PCA method to determine the primary driving factors of LULC change. Firstly, an indicator system for quantitatively analyzing the human and natural factors influencing LULC changes in Baicheng was constructed. Based on the data sources of this study, 12 indicators were selected, including total population (X1); regional gross domestic product (X2); value added of the primary industry (X3); value added of the secondary industry (X4); value added of the tertiary industry (X5); total output value of agriculture, forestry, animal husbandry, and fishery (X6); cultivated area of crops (X7); rural labor force (X8); livestock inventory at the end of the year (X9); sheep inventory at the end of the year (X10); average temperature (X11); and precipitation (X12). Then, using the dimension reduction algorithm of SPSS 24.0 software, the eigenvalues and contribution rates of each driving factor were calculated, and the principal component load matrix was generated. Following the criteria that the cumulative contribution rate is greater than 80% and the eigenvalue is greater than 1, the main factors influencing land use changes are determined. This is followed by an in-depth analysis of the processes influenced by each driving factor.

4. Results and Analysis

4.1. LULC Area Change Characteristics in Baicheng over the Past 70 Years

Over the past 70 years, dryland has been the predominant land use type in Baicheng, accounting for approximately 40% of the total area of the study region (Figure 3). The changes in LULC types mainly manifest in the increase in saline–alkaline land, paddy fields, and woodland, as well as the decrease in grassland, marshland, and dryland (Figure 4). Among them, the area of saline–alkaline land has shown fluctuating changes, with the most significant increase occurring between 1954 and 1976. This was primarily due to irrational irrigation and an imperfect drainage system leading to extensive secondary salinization. The areas of paddy fields and woodlands have noticeably increased, with their proportions rising from 0.01% and 0.34% in 1954 to 6.45% and 5.41% in 2020, respectively. This is primarily due to the increase in population leading to a rise in food supply demands, subsequently resulting in the establishment of windbreak forest systems and the process of reclaiming farmlands. Grassland area has significantly decreased, losing nearly 67% of its original extent. The ratio of grassland to arable land shifted from 1:1.2 in 1954 to 1:4.1 in 2020. Both marshland and dryland showed a fluctuating decline, decreasing by 7.24% and 2.09%, respectively.
The rate of change in land use area can be measured using the land use dynamic degree model. The dynamic degree of land use in Baicheng varies significantly in different periods (Table 1). From 1954 to 1976, grassland with medium coverage, marshland, and dryland showed a shrinking trend, while paddy fields, woodland, and saline–alkaline land showed a significant expansion trend. Among them, the change in paddy fields was the most dramatic, with a large growth rate, and the annual rate of change reached 764.11%. This was due to the increasing demand for arable land in the last century. Large-scale reclamation, retiring grasslands to cultivate land, and other behaviors caused the arable land area to increase sharply at the beginning of this study. This was also related to the small base of paddy fields and the large increase in area. From 1976 to 1988, the land use in Baicheng with the fastest annual change rate was grassland, with a significant reduction in area and an annual change rate of −1.65%. The next were sandy land and paddy fields, with positive growth, and annual change rates of 2.26% and 2.19%, respectively. From 1988 to 2000, the largest changes were in grassland and waters, with annual change rates of −1.48% and −0.79%, respectively, showing that the area of grassland continued to decrease, and the situation became more severe. From 2000 to 2010, the annual change rate of other lands grew the fastest, reaching 13.60%, followed by paddy fields and construction land. From 2010 to 2020, the largest change rates were in other lands, paddy fields, and construction land. In the process of land resource utilization, the area of other lands increased significantly, with an annual change rate of 95.41%, reaching the highest level ever. This is related to the current measures to develop solar and wind power in the western part of Jilin. The rapid development of regional socioeconomy and population is the reason for the continuous increase in construction land and paddy fields.
From the viewpoint of spatial distribution (Figure 5), the dynamic degree of LULC was larger in the whole area of Baicheng from 1954 to 1976. Regions with high LULC dynamic degree during this period included Xijiao street and Taohe town in Taobei district; Jiulongshan farm and Sifangtuozhi farm in Zhenlai county; Erlong township, Xiangyang street, Huhecheli township, and Yongmao township in Taonan city; Xianghai township, Tuanjie township, and Shihuadao township in Tongyu county; and Longzhao township in Da’an City. From 1976 to 1988, LULC dynamic degree slowed down overall, with agricultural activities as the primary focus. During this time, the most noticeable dynamic changes occurred in Qingshan town and Dongfeng township in Taobei district; Yongmao town, Jiaoliuhe township, and Datong township in Taonan city; Xinglongshan Town in Tongyu county; Sikeshu township and Lianhe township in Da’an city; and Datun township and Sifangtuozhi farm in Zhenlai county. From 1988 to 2000, LULC dynamic degree decreased further, with high dynamic degree areas including Datun township in Zhenlai county; Yongmao township, Jiaoliuhe township, and Datong township in Taonan city; and Sikeshu township in Da’an city. The high-value areas of LULC dynamic degree from 2000 to 2010 appeared in areas including Daobaozhen township in Taobei district, Yanjiang town in Zhenlai county, and Xinhuang fishery in Da’an city. From 2010 to 2020, regions with significant LULC dynamic degree were concentrated in Shunde township and Qingshan town in Taobei district; Datong township in Taonan city; Yongmao township, Jiaoliuhe township, Xinhua fishery farm in Da’an City; Honggangzi township; and Liangjiazi township, among others. This was primarily due to an increase in construction land.

4.2. LULC Type Transformation Characteristics of Baicheng over the Past 70 Years

From the land use type transformation map between 1954 and 2020 (Figure 6), it is evident that the most significant changes occurred in paddy fields, saline–alkaline land, woodlands, grasslands, and marshlands. The increase in paddy field area primarily originated from the reclamation of grasslands, croplands, and marshlands, with contribution rates of 37.35%, 35.10%, and 23.45%, respectively. The expansion of saline–alkaline land mainly resulted from secondary salinization of grasslands, marshlands, and croplands, with contribution rates of 45.22%, 25.30%, and 18.72% respectively. The rise in woodland area primarily came from farmland being returned to forests and afforestation of barren grasslands, with contribution rates of 52.44% and 39.98%, respectively. The decrease in grassland area was mainly due to its reclamation into cropland, secondary salinization, and its transformation into marshland, with transfer rates of 29.33%, 25.11%, and 9.74%, respectively. Marshland decreased from 398,500 hectares in 1954 to 212,000 hectares in 2020, mainly due to drying and subsequent transformation into saline–alkaline land.
From 1954 to 1976, the most significant change in Baicheng city’s land use was in grassland, followed by saline–alkaline land and marshland. Grasslands mainly transformed into dry lands, saline–alkaline lands, and marshlands, with conversion rates of 25.47%, 22.36%, and 10.14%, respectively. Saline–alkaline lands expanded significantly, primarily sourced from grasslands, marshlands, and dry lands, contributing 43.95%, 26.30%, and 17.86%, respectively. From 1976 to 1988, the most pronounced change was in saline–alkaline lands, followed by grasslands and marshlands. Salinization of grasslands remained the primary reason for the increase in saline–alkaline land area, accounting for 78.68% of the net increase. The net decrease in marshlands mainly transformed into dry lands, paddy fields, and saline–alkaline lands, with conversion rates of 5.85%, 5.18%, and 3.34%, respectively. From 1988 to 2000, the most significant change was in grasslands, with notable bidirectional conversions between grasslands and dry lands. The net reduction in grassland area was mainly due to its conversion into dry lands. Dry lands were primarily cultivated from grasslands, woodlands, and the conversion of paddy fields. The increase in saline–alkaline land area was mainly due to the destruction of water bodies and marshland ecosystems, as well as overcultivation of grasslands. From 2000 to 2010, the most significant changes were in water bodies, followed by paddy fields and dry lands. Water bodies primarily transformed into marshlands, dry lands, and saline–alkaline lands. The increase in paddy fields mainly resulted from the conversion of saline–alkaline lands and marshlands, with conversion rates of 3.46% and 2.14%, respectively. During this period, Baicheng city’s efforts to return cultivated land to forests and grasslands began to show results, with grassland areas increasing after previous declines. From 2010 to 2020, the area of paddy fields continued to increase, primarily due to the conversion from dry lands, saline–alkaline lands, and grasslands, contributing 25.27%, 16.86%, and 5.56%, respectively. In contrast, the area of saline–alkaline lands decreased, mainly transforming into paddy fields, marshlands, and grasslands, with conversion rates of 5.19%, 0.62%, and 0.49%. This change can be attributed to Baicheng’s recent efforts to promote ecological agriculture and tourism. Additionally, projects like river–lake connectivity and land reclamation have led to more “transform dried land into irrigated fields” conversions and rice farming projects on saline–alkaline lands.

5. Analysis of the Driving Factors for LULC Changes

Through PCA, it was discovered that both the first and second principal components have eigenvalues greater than 1, with a cumulative contribution rate reaching 83.2%. This suggests that these two components represent most of the information from the 12 factors selected for Baicheng (Table 2). The first principal component contributes 65.7% and is constituted by X2, X3, X4, X5, X6, and X7. This indicates that LULC changes in Baicheng are primarily driven by population and socioeconomic factors. The second principal component, with a contribution rate of 17.58%, is made up of X9, X10, and X11, suggesting that LULC changes in Baicheng are also influenced by agricultural, livestock, and climatic factors.
From the rotated principal component loading matrix (Table 3), it can be observed that the first principal component has a very strong positive correlation with variables such as the total output value of agriculture, forestry, animal husbandry, and fisheries (X6); the value added of the primary industry (X3); the regional gross domestic product (X2); and the value added of the tertiary industry (X5) with correlation coefficients of 0.989, 0.988, 0.969, and 0.957, respectively. The second principal component has a positive correlation with the year-end inventory of sheep (X10) with a correlation coefficient of 0.730 and a very strong negative correlation with precipitation (X12) with a correlation coefficient of −0.577.

5.1. Population Factor

The changes in population size and structure have led to changes in LULC types and intensities. The population change in Baicheng can be divided into three stages (Figure 7). From 1954 to 1978, there was a trend of rapid growth, with an increase of nearly 970,500 people in 24 years. From 1978 to 2010, the growth rate slowed down, and the rural labor force gradually increased. The increase in the total population exacerbated the conflict between humans and land. Firstly, it manifested in the ever-increasing demand for food. To address the food issue, a large area of grassland was reclaimed for dryland and paddy fields. Secondly, the demand for urban and rural housing, various public facilities, and transportation has grown, leading to an expansion in construction land use. This curtailed the growth rate of arable land and directly caused a decrease in arable land area. Starting from 2010, Baicheng’s total population and rural labor force began to decline. A large number of rural populations continuously gathered in towns and cities. The reduction in the rural labor force led to the phenomenon of farmland being abandoned, and the contradiction between urbanization and arable land protection became increasingly prominent.

5.2. Economic Factors

Economic factors are closely related to the local ecological environment and population size. The substantial loss of cropland, woodland, grassland, and marshland is largely due to rapid economic development, and the impact on the local ecological environment cannot be restored in a short time. From 1954 to 2020, the GDP of Baicheng surged from 310 million yuan to 49.15 billion yuan, almost 159 times that of 1954. The first, second, and third industries all showed an increasing trend (Figure 8). Among them, the development of the primary and secondary industries was relatively steady; after the “Revitalize the Northeast” strategy was proposed in 2004, it had a certain impact on land use dynamics. In the subsequent period, the development became more intense, with the secondary industry having the largest share among the three major industries, reaching a peak of 48.76%, followed by the tertiary industry, and the added value of the primary industry had the slowest growth trend. In recent years, the country has proposed “carbon neutrality”, advocating energy conservation and emission reduction, focusing on the development of the tourism industry and new clean energy. The construction lands for photovoltaic power generation and livestock farming have expanded significantly.

5.3. Farm Animal Factors

Animal husbandry is one of the main industries in Baicheng. The number of livestock and the mode of animal husbandry production affect changes in LULC, especially grassland types. Research has found that the Leymus chinensis grass communities in the Songnen plain are gradually being replaced by communities of Atriplex canescens and halophytic plants like Suaeda salsa [57]. Grazing, especially overgrazing, not only damages grassland vegetation but also causes soil quality degradation, leading to a series of ecological and environmental problems, thereby indirectly causing soil desertification and saline–alkaline land. Looking at the changes in the number of large livestock and sheep in Baicheng from 1954 to 2020 (Figure 9), the large livestock fluctuated greatly, but overall, it showed an increasing trend followed by a decreasing trend, while the number of sheep showed a slow increase followed by a sharp decrease. The annual count of large livestock in Baicheng reached a relatively high level of 539,200 heads around 2002 and then showed a declining trend, reaching a relatively low level of 126,300 heads in 2018. The total number of sheep at the end of the year reached a high level of 2,031,100 heads in 2006 and then showed a sharp decline, reaching a post-decline low of 890,300 heads in 2018. Since the implementation of the “Returning Grazing Land to Grassland” policy by the state in 2003, the number of livestock in Baicheng has gradually decreased. After Jilin Province implemented a ban on grazing in 2013, the number of livestock in Baicheng decreased even more significantly. Accordingly, the grassland area decreased from 90.43 km2 in 1954 to 29.83 km2 in 2000. Afterward, the decrease in grassland area slowed down, and by 2010, the total grassland area reached 30.53 km2.

5.4. Climatic Factors

Against the global backdrop of climate warming, the annual average temperature in Baicheng has shown a rising and warming trend over the past 70 years (Figure 10). From 1951 to 2020, the annual average temperature in Baicheng has increased by about 2 °C, rising about 0.29 °C every decade. Due to its location at the transition zone between farming and pastoral areas, the warming climate provides relatively favorable climatic conditions for the large-scale reclamation of grassland and marshland. However, due to its sensitivity to climate change, it also leads to the abandonment of cropland and degradation of ecosystems [11]. During the same period, the rainfall showed a slight decreasing trend, and in recent years, droughts have become more frequent. The precipitation in 1999, 2000, 2003, 2005, and 2006 was below 300 mm, leading to drought causing the areas of waters and marshland to shrink, resulting in an intensification of soil saline–alkaline land. In 2000, the increase in the area of marshland and some waters in Baicheng was caused by the flood disaster in 1998 [58]. Since the 1980s, the trend of warming and drying in Baicheng has become more pronounced, which is not conducive to natural ecosystems like marshland and grassland, leading to desertification and secondary salinization of marshland and grassland.

6. Discussion

6.1. Analysis of LULC Change Characteristics in Baicheng

Over the past nearly 70 years, located in the transition zone between farming and pastoral areas, Baicheng city’s cropland and grassland have always been the two largest types of land use, accounting for about 2/3 of the total area of Baicheng. The overall trend of LULC change in Baicheng is a decrease in the area of dryland, grassland, and marshland, while the area of other land use types has increased. In 1954, marshland accounted for 15.47% of the area, representing a typical “Five-Flower Grass Pond” landscape in the northeast region with minimal human disturbance. It was the third largest type of land use. However, starting from 1954, the marshland area showed a decreasing trend. By 2020, the marshland area had reduced to half of that in 1954, while the area of saline–alkaline land showed a growing trend. By 2020, saline–alkaline land had become the third largest type of land use. Although there are slight differences in spatial and temporal scales, this research conclusion is consistent with previous studies [58,59]. Over the past 70 years, the main land use type transitions in Baicheng occurred between cropland, marshland, saline–alkaline land, and grassland, and the dynamics gradually slowed down, with the LULC structure becoming increasingly stable. In addition, before 1954, due to the complexity of rice cultivation technology and the imperfection of irrigation technology, rice cultivation was rarely adopted by local farmers, resulting in a small area of paddy fields. Not until the early days of the People’s Republic of China did local governments begin to prioritize rice production, organizing masses to learn rice cultivation techniques, reclaiming wetlands, and fully utilizing the Taoer river and Nen river to expand the area of rice cultivation, leading to a rapid increase in the area of paddy fields. Especially between 1954 and 1976, the dynamics of paddy fields reached 764.11%. With the support of ecological protection and restoration policies, the speed of reclamation of marshland for paddy fields gradually slowed down, while the area of saline–alkaline land converted to paddy fields continued to increase. From 2010 to 2020, saline–alkaline land contributed to 16.86% of the growth in paddy field area. Under the regional green development and the goal of Jilin province’s hundred billion kilograms grain construction, this phenomenon will continue. Furthermore, related research indicates that rice cultivation in western Jilin helps to reduce temperature and increase relative humidity [60], having a positive effect on regional climate.

6.2. The Role of Policy Factors

The relationship between land use policy and land use patterns is mutually influential. Land use policy guides the adjustment of land use patterns and directly drives changes in land use. Conversely, after the land use pattern changes, the government formulates and refines land use policies based on socioeconomic development and ecological environmental conditions.
In Baicheng, in the 1950s, after the founding of the People’s Republic of China, there was an urgent need for food. Under the national policy of “To develop industry, agriculture must be developed correspondingly”, Baicheng vigorously exploited its reserve land resources, triggering a wave of land reclamation. This led to a large area of grassland being cultivated, increasing the area of cropland. At the same time, following the policy of “prioritizing small-scale, and then gradually expanding the area of paddy fields”, Baicheng promoted water conservancy measures, leading to a gradual expansion in rice cultivation area and waters. The early water conservancy measures and the promotion of rice planting techniques changed the crop structure of Baicheng. Rice became an important crop, and rice planting bases were established. The increased paddy fields were primarily located along the Taoer river.
From 1976 to 1988, in order to encourage the enthusiasm of farmers, Baicheng implemented the household responsibility system in 1982 and reformed the agricultural management system. Farmers were allowed to reclaim abandoned croplands and wastelands. At the same time, due to the development of agricultural machinery and the establishment of large-scale farms in Baicheng, some woodlands, grasslands, and sandy lands were used for agricultural purposes. Wetlands were transformed into paddy fields, resulting in a significant increase in the area of cropland.
From 1988 to 2000, on one hand, due to population growth, mineral resource development, and infrastructure construction, construction land occupied a large amount of cropland. As a result, the national government formulated a series of land management policies to restrict the excessive occupation of cropland. On the other hand, in order to increase income levels, farmers reclaimed large areas of cropland. The development of irrigation facilities, fertilizers, and agricultural machinery also promoted the expansion of cropland and the reduction of grassland. By the late 1990s, Baicheng experienced drought and severe flooding, which led to a reduction in water reserves. To support wetland protection and restoration, the national government implemented the “Returning Cropland to Wetland” policy. Baicheng initiated measures such as “Diverting water from Huo to Xiang” and “Diverting water from Tao to Xiang”, and established wetland parks and wetland restoration projects. By 2000, the area of marshland had slightly increased. From 1978 to 2000, the implementation of the Three-North Shelter Forest Projects phases I, II, and III in Baicheng had effectively curbed the reduction of woodland, leading to an increase in shelter forest areas in the region.
In 2003, the number of livestock in Baicheng reached a peak, while overgrazing led to a significant reduction and fragmentation of grasslands, marshlands, and other natural ecosystems [58]. To address the extensive deforestation and associated ecological problems, the national government launched policies centered on ecological construction and the “Returning Farmland to Forest and Grassland” initiative. Jilin province actively responded to these national policies by introducing ecological restoration projects such as the “Ecological Province” and the “Reclamation and Salinization Control of Wastelands”, which resulted in a certain degree of recovery in woodland and grassland areas, as well as a reduction in saline–alkaline land and sandy land areas. Under the policy of “Revitalizing the Old Industrial Base in the Northeast”, Baicheng adjusted its maize cultivation area, expanded the cultivation of cash crops, and significantly increased the area of paddy fields. After 2008, the national land policy emphasized both the protection of land resources and the assurance of economic development. The “National Ecological Function Zoning” and the “National Food Security Medium and Long-Term Planning Outline” were successively formulated and implemented to balance economic development and ecological protection. Although the area of ecological land continued to decrease, the protection and restoration of grasslands, woodlands, and wetlands had been significantly strengthened [61]. Baicheng continued to adjust its agricultural planting structure and expand its paddy fields to support Jilin province’s goal of increasing its grain production capacity by 100 billion kilograms. However, the expanded paddy fields during this period were mainly transformed from wetlands in the Nen river basin. The process of converting dry land to paddy fields consumed a large amount of groundwater, affecting local hydrological conditions and leading to a reduction in the area of rivers and lakes.
After 2010, many of the national policies for ecological protection and economic development benefited Baicheng, including the fifth phase of the Three-North Shelter Forest Project, the Belt and Road Initiative, the prohibition of commercial logging in natural forests, the National New Urbanization Plan, and the new round of revitalization plans for the northeast. Baicheng also established the concept of “Eco-based City Development”, prioritizing ecological protection as a premise for development. Actions were taken to combat desertification and construct the Great Western Barrier, leading to an increase in woodland areas and a reduction in sandy areas. In 2013, Jilin province initiated the “River-Lake Connection” project, resulting in the restoration of wetland and waters areas [62]. Between 2016 and 2020, Baicheng completed ecological construction tasks including grassland governance, afforestation, river–lake connection, and wetland restoration as part of the efforts to build the ecological barrier in Western Jilin [47]. From 2010 to 2020, the area of woodland in Baicheng increased, while grassland, marshland areas recovered, and the area of waters increased. At the same time, sandy land and saline–alkaline land areas decreased, indicating the effectiveness of ecological restoration and environmental management. Moreover, with the continuous promotion of high-standard basic farmland construction projects, in the context of ecological stress, resource constraints, and public demand, the trend in cropland utilization shifted towards a protection mode represented by permanent basic farmland. By 2020, the spatial pattern of cropland in Baicheng had stabilized.

7. Conclusions

Combining multisource remote sensing, topographic maps, meteorological data, and statistical data, this study analyzed the changes in LULC in the Baicheng area from 1954 to 2020 and examined the impact of driving factors. The main conclusions are as follows: Over the past 70 years, there have been significant changes in the LULC structure of Baicheng, which can be generally described as “seven increases and three decreases”, but the area of cropland has always accounted for more than 41% of the total area. The area of saline–alkaline land and paddy field has increased significantly, while grassland, marshland, and unused land have decreased most drastically. There is mutual conversion between grassland and unused land, saline–alkaline land and marshland, with the conversion rate gradually slowing down. The growth of the paddy field area is accelerating, mainly due to the conversion of unused land to paddy fields, the transformation of saline–alkaline land into paddy fields, and the reclamation of marshland for paddy fields. From 1954 to 2020, the dynamic degree of land use in Baicheng first decreased and then gradually increased. The period from 1954 to 1976 was the most active period for land use dynamic changes, while the intensity of change was relatively stable from 1976 to 2020.
From the perspective of driving factors, economic development is the primary driver of LULC changes. With economic growth, the driving role of population factors and macro policy regulation on LULC changes has gradually expanded. The rapid development of agriculture and animal husbandry has led to the loss of some grassland and marshland. Although the government has strengthened ecological protection in the region and the ecological environment has improved, as an ecologically sensitive area, striking a balance between ecological protection and food production still presents significant challenges. It is recommended that Baicheng vigorously promotes ecological breeding models in the future, advocates diverse agricultural planting systems, and integrates agriculture, animal husbandry, and aquaculture; strengthens the development of green agriculture and other low-carbon environmental industries; intensively develops clean energy; reduces the impact of agricultural activities on other ecosystems; continues afforestation efforts; constructs the ecological barrier in western Jilin province; combats land desertification; optimizes land use structure; scientifically resolves the conflict between construction land and cropland; integrates water networks and ecological green spaces; establishes an urban ecological network system to ensure the connectivity and integrity of the ecosystem is protected; gradually implements ecological restoration projects and comprehensive land reclamation projects to restore soil fertility and achieve sustainable agricultural production, which is also an effective way to reduce the conflict between agriculture and ecological functions; promotes local rice brands; develops characteristic animal husbandry and fruit and forestry products; fosters ecotourism and agricultural tourism through green approaches, enhancing the region’s sustainable economic development.

Author Contributions

Conceptualization, J.Y. and Y.L.; methodology, B.P.; software, B.P.; validation, S.Z.; investigation, J.Y. and S.Z.; resources, J.Y. and S.Z.; writing—original draft, B.P.; writing—review & editing, J.Y., Y.L. and S.Z.; supervision, Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was jointly supported by the National Key Research and Development Program of China (grant no. 2021YFD1500102), the Strategic Priority Research Program of the Chinese Academy of Sciences (grant no. XDA28070500), the Jilin Provincial Natural Science Foundation (grant no. 20200201040JC), and the Key Consultation Project of the Chinese Academy of Engineering (grant no. JL2020-001).

Data Availability Statement

Not applicable.

Acknowledgments

The authors extend great gratitude to the anonymous reviewers and editors for their helpful reviews and critical comments.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Location map of the study area.
Figure 1. Location map of the study area.
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Figure 2. Flowchart of the methodology.
Figure 2. Flowchart of the methodology.
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Figure 3. Percentage of different LUCC types in Baicheng from 1954 to 2020.
Figure 3. Percentage of different LUCC types in Baicheng from 1954 to 2020.
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Figure 4. LULC map of Baicheng from 1954 to 2020.
Figure 4. LULC map of Baicheng from 1954 to 2020.
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Figure 5. Comprehensive LULC dynamic degrees in Baicheng from 1954 to 2020. Measured in percentage. Pixel size of 3000 m.
Figure 5. Comprehensive LULC dynamic degrees in Baicheng from 1954 to 2020. Measured in percentage. Pixel size of 3000 m.
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Figure 6. Sankey diagram of LULC type transformation from 1954 to 2020. Measured in ten thousand square hectares.
Figure 6. Sankey diagram of LULC type transformation from 1954 to 2020. Measured in ten thousand square hectares.
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Figure 7. Changes in total population and rural labor force from 1954 to 2020.
Figure 7. Changes in total population and rural labor force from 1954 to 2020.
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Figure 8. Changes in the added value of the primary, secondary, and tertiary industries from 1954 to 2020.
Figure 8. Changes in the added value of the primary, secondary, and tertiary industries from 1954 to 2020.
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Figure 9. Changes in the number of large livestock/sheep and grassland area from 1954 to 2020.
Figure 9. Changes in the number of large livestock/sheep and grassland area from 1954 to 2020.
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Figure 10. Climate factors in Baicheng from 1954 to 2020.
Figure 10. Climate factors in Baicheng from 1954 to 2020.
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Table 1. Dynamic degree of each LULC type in Baicheng from 1954 to 2020 (%).
Table 1. Dynamic degree of each LULC type in Baicheng from 1954 to 2020 (%).
LULC Type1954–19761976–19881988–20002000–20102010–2020
Paddy field764.112.190.512.218.48
Dryland−0.370.110.430.08−0.38
Forest78.15-0.57−0.49−0.120.01
Grassland−2.27−1.65−1.480.23−0.16
Water area4.460.75−0.79−2.100.52
Built-up area10.761.360.040.630.65
Other0.000.190.0913.6095.41
Sandy land2.072.26−0.04−0.23−0.68
Saline-alkaline land27.601.220.32−0.16−0.68
Marshland−1.93−0.730.31−0.05−0.18
Table 2. Eigenvalues and contribution rates of principal components.
Table 2. Eigenvalues and contribution rates of principal components.
ComponentsInitial EigenvaluesExtract the Sum of Squares and Load
AggregateVariance (%)Cumulative (%)AggregateVariance (%)Cumulative (%)
17.87965.65565.6557.87965.65565.655
22.10917.57983.2342.10917.57983.234
30.9037.52890.762
40.5514.59295.354
50.3112.58997.943
60.0970.80898.751
70.0790.65999.410
80.0340.28699.696
90.0280.23399.929
100.0070.05899.986
110.0010.01199.997
120.0000.003100.000
Table 3. LULC change principal component loading matrix.
Table 3. LULC change principal component loading matrix.
Serial NumberDriving FactorPrincipal Component
12
X1Total population (×104)0.7320.557
X2Regional gross domestic product (×104 yuan)0.969−0.204
X3Value added of the primary industry (×104 yuan)0.988−0.072
X4Value added of the secondary industry (×108 yuan)0.927−0.244
X5Value added of the tertiary industry (×108 yuan)0.957−0.219
X6Total output value of agriculture, forestry, animal husbandry, and fishery (×104 yuan)0.989−0.082
X7Cropland planting area (hm2)0.934−0.280
X8Rural labor force (×104)0.9220.274
X9Year-end inventory of large livestock (×104)−0.3930.665
X10Year-end inventory of sheep (×104)0.6340.730
X11Average temperature (°C)0.6160.420
X12Precipitation (mm)0.126−0.577
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MDPI and ACS Style

Peng, B.; Yang, J.; Li, Y.; Zhang, S. Land Use/Land Cover Changes in Baicheng District, China during the Period 1954–2020 and Their Driving Forces. Land 2023, 12, 1845. https://doi.org/10.3390/land12101845

AMA Style

Peng B, Yang J, Li Y, Zhang S. Land Use/Land Cover Changes in Baicheng District, China during the Period 1954–2020 and Their Driving Forces. Land. 2023; 12(10):1845. https://doi.org/10.3390/land12101845

Chicago/Turabian Style

Peng, Bin, Jiuchun Yang, Yixue Li, and Shuwen Zhang. 2023. "Land Use/Land Cover Changes in Baicheng District, China during the Period 1954–2020 and Their Driving Forces" Land 12, no. 10: 1845. https://doi.org/10.3390/land12101845

APA Style

Peng, B., Yang, J., Li, Y., & Zhang, S. (2023). Land Use/Land Cover Changes in Baicheng District, China during the Period 1954–2020 and Their Driving Forces. Land, 12(10), 1845. https://doi.org/10.3390/land12101845

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