Simulating land use/land cover change in an arid region with the coupling models

Abstract

The rapid development of productivity and economy has led to a substantial change in global land use/land cover (LULC), which has caused a series of environmental problems. Therefore, it is particularly important to quantitatively grasp the spatiotemporal pattern of LULC to formulate and implement land use planning. This study extracted LULC by the combination of supervised classification and manual visual interpretation and quantitatively analyzed the spatiotemporal changes in LULC. Finally, the land use situation was simulated, and the driving forces affecting LULC changes were analyzed with the logistic regression-cellular automata-Markov chain (LR-CA-Markov) and FLUS models. The results showed that the ecological environment underwent more noticeable changes in approximately the year 2000. Relatively speaking, LULC changes were the most dramatic during 1987–1997. With the implementation of the Grain for Green Project (GFGP) in 1999, the ecological environment began to develop towards a positive trend, but built-up land area has also grown rapidly. The economy was the main factor influencing the change in LULC. The simulation results showed that the simulation accuracy and kappa coefficient of the LR-CA-Markov and FLUS models were both greater than 0.85, and the prediction results of the same land-type change trend were basically the same. On this basis, the land use scenario in 2027–2047 was predicted. The results showed that the LULC would change dramatically over the next 30 years (likely due to urban expansion). Therefore, LULC research in arid regions can provide theoretical guidance for protecting the ecological environment, rationally planning land use, and realizing the sustainable development of arid zones, such as the economy, society, and ecological environment.

Keywords

• LULC
• Logistic regression
• CA-Markov
• FLUS
• Land use simulation