1. Introduction
With rapid socio-economic development and accelerated urbanization, the conflict between increasing land use demand and limited land resources has become more and more prominent since the 1990s [
1,
2]. Competitive land behaviors such as the construction land encroachment on arable land and ecological land have resulted in a serious imbalance in land use structure, and the deterioration of the ecological environment [
3]. Frequent land use conflicts (LUCs) problems have become a serious obstacle to the sustainable use of land resources. Therefore, studying the spatio-temporal changes of LUCs is of great importance for promoting regional high-quality development and achieving coordinated regional development, which is a current research hotspot among scholars in China.
LUCs refers to the inconsistency and disharmony among various stakeholders during the process of land resource utilization with respect to land use methods and quantities, and the state of conflicts between land use methods and the ecological environment [
4,
5]. How to assess the level of LUCs and promote high efficiency and rational land use are major concerns for policy makers and researchers. Many previous studies have focused on conflict type identification, conflict driver analysis, and spatio-temporal dynamic analysis. Different models, including the multi-objective evaluation method [
6], game theory [
7], actor network analysis [
8], rapid rural appraisal [
9], and landscape pattern analysis [
10], were used to quantify regional land use intensity and conflict characteristics. For example, Meng, et al. [
10] conducted an attribution analysis of LUCs by analyzing the correlation between LUCs indices, socio-economic factors, and natural environmental factors in the Heihe River. Zhang, et al. [
11] analyzed LUCs based on 3S technology, which obtained a spatial layout of LUCs, and explained the spatio-temporal changes in LUCs in the Yangtze River Delta city cluster over the past 40 years. Kuusaana, et al. [
12] examined the land tenure system in the Asante Akim North District of Ghana, and how it affects LUCs between Fulani pastoralists and smallholder farmers by using a mixed qualitative approach of surveys, in-depth interviews, and focus group discussions. Steinhäußera., et al. [
13] conducted interviews with national and regional stakeholders through participatory survey methods to analyze which LUCs exist and the similarities and differences between national and regional levels and priority regions in Germany. However, most of the current research is focused on LUCs in developed regions at a relatively large spatial scale based on historical spatial land use data [
14], Only a few studies assessed future LUCs based on landscape structure at the microscopic scale.
To evaluate future LUCs, land use and land cover change (LUCC) simulations and predictions under different development scenarios are imperative [
15]. In recent years, the commonly used LUCC simulation models include the Markov model [
16], systems dynamics (SD) model [
17], cellular automata (CA) model [
18], and the conversion of land use and the extent of its effects on small regions (CLUE-S) model [
19]. The Markov model mainly relies on the transition probabilities between different land use categories, but neglects the spatial distribution of land use changes [
20,
21]. The CA and CLUE-S model can simulate the spatial distribution of land use changes, and assess the influence of various factors on LUCC, such as natural and human drivers [
22]. However, the determination of driver weights in the CA model depends on expert experience, which is subjective and easily influenced by human factors [
23], and it cannot simulate and predict land use changes caused by factors such as policy planning and climate impact [
24]. Therefore, coupling models of the Markov, CA, and CLUE-S models are expected to solve the inherent limitations of a singular model while simulating spatial changes in land use [
25]. Liu, et al. [
26] proposed a future land use simulation model (GeoSOS-FLUS) based on a traditional CA model. The GeoSOS-FLUS model can better address the relationship between driving forces and simulate the long-term spatial evolutionary trajectory of various types of land use. By coupling the top-down system dynamics with the bottom-up cellular automata, an adaptive inertia and competition mechanism is established in the CA model, which can effectively deal with the complexity and uncertainty among the intercon-version of different land use types from regional to national scales. The GeoSOS-FLUS model is currently broadly utilized in land use simulation [
27], urban expansion simulation [
28], and ecosystem services value [
29]. In this study, we selected the Markov model combined with the GeoSOS-FLUS to simulate the LUCC in Xiamen.
The contribution of the paper is twofold. Firstly, most previous studies focused on larger-scale regional land use simulation and land use conflict assessment, while this study attempted to provide a reference for policy makers to develop future urban land planning layouts through case studies at the city level. Secondly, this paper simulated future land use conflicts based on different development goals such as cropland protection and ecological civilization construction, which can complement the analysis of the historical status of land use and supplement the planning that mostly is limited to the analysis of the current situation.
This study first assessed the historical land use dynamics during the period of 2010–2020 and simulated future land use trends in Xiamen, China using the Markov and the GeoSOS-FLUS model under three future scenarios: the natural development scenario (NDS), the policy intervention scenario (PIS), and the sustainable development scenario (SDS). Next, a comprehensive LUCs index measurement model was built based on the landscape pattern to analyze the differences in conflict levels and changing characteristics of the LUCC under the future scenarios. This study can provide support for land use management and ecological city construction in Xiamen and can be expanded to other regions in China.
4. Discussion
This study simulated future LUCC under three different development scenarios based on the Markov and the GeoSOS-FLUS model, and analyzed the spatio-temporal characteristics of LUCs in Xiamen by using the LUCs model. The study showed that the LUCs model based on landscape pattern can precisely depict the evolution pattern of LUCs and predict the potential risk of land use in Xiamen. The simulation results can provide support for the implementation of territorial spatial planning, optimization of “three lines” demarcation results, implementation of food security control, and construction of an ecological security early warning system, and also contribute to regional land management and land protection.
With the rapid growth of population and high-speed economic development, construction land is constantly encroaching on arable land, forest land, and other ecological land, and the conflicts between development and protection occurs frequently. Fan, et al. [
43] concluded that about 3.2% of the land area in China has a high or relatively high urbanization function, mainly concentrated in the eastern coastal region and the middle and lower reaches of the Yangtze River. Land use changes in these regions are likely to face the same situation as Xiamen. Therefore, the model framework constructed in this study can also be used for simulating future land use changes in other regions. The “win-win” development pattern is not only applicable to Xiamen, but also can provide important references for the sustainable development of other cities and countries with a high degree of urbanization.
LUCs are inevitable due to land resources scarcity and the unlimited growth of human demand [
44]. The results of this study show that the intensity of LUCs has an overall upwards trend, and human activities play a major role in the process. In this circumstance, a better understanding of land use conflicts is needed. Therefore, we constructed a LUCs model, and successfully identified current and potential land use conflicts in Xiamen. In addition, we integrated various strategic land use plannings (for example, the Overall Plan for Land Utilization in Xiamen, the 14th Five-year Construction of Ecological Civilization Plan in Xiamen, and the 14th Five-year Agriculture and Rural Development Special Plan in Xiamen), and designed three future land use development scenarios. LUCs in Xiamen differ greatly under the three scenarios in 2030. The strategies under the SDS can balance the land use needs of both socio-economic development and regional ecological security with the least LUCs, which could be an optimum solution for the long-term sustainable development in Xiamen.
Although the research results fit the development situation of regional land use well, there are still some limitations: (1) The LUCs model can only reflect the degree of LUCs of various land use types, but cannot accurately reflect the specific geographic location of conflicts. In addition, LUCs are measured only based on the perspective of landscape pattern, which lacks consideration of economic and social factors. Therefore, in the process of identifying future LUCs, combining the qualitative and quantitative methods such as participatory surveys and 3S technology is an important direction to optimize LUCs research. (2) The classification of the conflict levels and model parameters in this study were mainly adopted from previous research experience, which creates difficulty when avoiding the errors caused by subjective factors. Hence, our future research will focus on how to improve the accuracy of the research results. In addition, this paper also lacks comparison with other models. These need to be further studied in the follow-up.
5. Conclusions
The study simulated future LUCC under three different development scenarios, and assessed the spatio-temporal evolution of LUCs in Xiamen. Results indicated that land use/cover in Xiamen has remarkably changed. Cropland area decreased by 84.96 km2, while construction land increased by 108.99 km2 in Xiamen from 2010 to 2020. Most of the expansion of the area of construction land comes from the occupation of the area of cropland. LUCs in Xiamen differ greatly under the three scenarios in 2030. Under the NDS, the rapid urbanization process continuing the previous development trend has led to changes in various land use types, with a reduced area of cropland and an expanded area of construction land. The area of moderate conflict reached 462.15 km2, the area of intense conflict reached 3.78 km2, and the intensity of LUCs showed an overall upward trend. In the PIS, considering the protection of cropland, construction land expansion has been slowed down, and there is a small growth in grassland. The degree of LUCs is moderate compared with the NDS, and is mainly concentrated on two levels of moderate conflict and mild conflict. The moderate conflict area decreased by 23.16% compared with that under the NDS. Under the SDS, due to the balance of economic development and ecological benefits, the vegetation cover in Xiamen was considerably increased, forest and grassland reached the highest level, and the area of both moderate conflict and intense conflict reached the lowest among the three scenarios. The SDS balances the land use needs of both social and economic development and regional ecological security with the least LUCs, which could be an optimum solution for the long-term sustainable development in Xiamen. The results of this study provide support for decisions about eco-city construction and geospatial planning.