Policy factors impact analysis based on remote sensing data and the CLUE-S model in the Lijiang River Basin, China

• Published in: Catena (Giessen) Vol. 158; pp. 286 - 297
• Main Authors: Liu, Guang, Jin, Qingwen, Li, Jingyi, Li, Lei, He, Chengxin, Huang, Yuqing, Yao, Yuefeng
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2017
• Subjects: agricultural land; China; CLUE-S; forests; issues and policy; Land use change; Landsat; Lijiang River Basin; mathematical models; regression analysis; remote sensing; Returning Farmland to Forest Program; Scenarios; shrublands; spatial data; watersheds; woodlands; China; Scenarios; CLUE-S; Land use change; Returning Farmland to Forest Program; Lijiang River Basin
• ISSN: 0341-8162; 1872-6887
• DOI: 10.1016/j.catena.2017.07.003

Land use change is affected by many driving factors such as the economy, population, and government policy. This study investigated the relationship between government policy and land use change to develop an understanding applicable to the formulation of strategies for sustainable land use. The Lijiang River Basin in the Guangxi Zhuang Autonomous Region in southern China was selected for this study. The predicted characteristics of land use change were explored using the CLUE-S numerical model and logistic regression. Using Landsat remote sensing imagery as source data, we simulated the tendency of land use change from 1993 to 2020 under two scenarios: a Natural Growth Scenario (NS) and a Government Intervention Scenario (GS), and we analyzed the possible social driving factors. The results revealed that from 1993 to 2015, both construction and cultivated land have shown a tendency of areal increase. Water and woodland areas both decreased from 1993 to 2006 but then they increased dramatically from 2006 to 2015. Shrubland areas increased from 1993 to 2006 but decreased slightly from 2006 to 2015. The CLUE-S model was used to predict the spatial patterns of land use for 2020. It showed that under the NS, the areas of construction and cultivated land increased, while the areas of other land uses decreased. Under the GS, the areas of construction land, woodland, cultivated land, and water all increased, while the areas of the others declined. Furthermore, the area of woodland decreased for every county under the NS, but areas of woodland expansion were located in Lingchuan and Lingui counties under the GS. Hotspots of cultivated land occurred in Lingchuan County under the NS and in Xingan County under the GS. Water area decreased in every county under the NS, whereas increases in water areas occurred in Lingchuan and Guilin counties under the GS. Construction land expanded in Lingchuan County under the NS and in Guilin County under the GS. The Returning Farmland to Forest Program could be considered a successful addition to the eco-environmental policies implemented in the Lijiang River Basin. •Discover the spatiotemporal distribution of recent land use change in the Lijiang River Basin in China.•Predict the spatial patterns of land use for 2020 under two scenarios using the CLUE-S model and logistic regression.•Investigate the influence of Returning Farmland to Forest Program on the tendency of land use change.