Land-Use Spatio-Temporal Change and Its Driving Factors in an Artificial Forest Area in Southwest China

Xiaoqing Zhao, Junwei Pu, Xingyou Wang, Junxu Chen, Liang Emlyn Yang and Zexian Gu
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Xiaoqing Zhao: School of Resource Environment & Earth Science, Yunnan University, Kunming 650091, China
Junwei Pu: School of Resource Environment & Earth Science, Yunnan University, Kunming 650091, China
Xingyou Wang: Chongqing Architectural Design Institute, Chongqing 400000, China
Junxu Chen: School of Resource Environment & Earth Science, Yunnan University, Kunming 650091, China
Liang Emlyn Yang: Graduate School of Human Development in Landscapes, Kiel University, 24118 Kiel, Germany
Zexian Gu: Forestry Bureau of Nujiang Lisu Autonomous Prefecture, Lushui 673100, China

Sustainability, 2018, vol. 10, issue 11, 1-19

Abstract: Understanding the driving factors of land-use spatio-temporal change is important for the guidance of rational land-use management. Based on land-use data, household surveys and social economic data in 2000, 2005, 2010, and 2015, this study adopted the Binary Logistic Regression Model (BLRM) to analyze the driving factors of land-use spatio-temporal change in a large artificial forest area in the Ximeng County, Yunnan province, in Southwest China. Seventeen factors were used to reflect the socio-economic and natural environment conditions in the study area. The results show a land use pattern composed of forestland, dry cropland, and rubber plantation in Ximeng County. Over the past fifteen years, the area of artificial forests increased rapidly due to the “Grain for Green” policy, which has led to increases in rubber plantations, tea gardens, eucalyptus forests, etc. In contrast, the area of natural forest and dry cropland decreased due to reclamations for farming and constructions. The BLRM approach helped to identify the main driving factors of land-use spatio-temporal change, which includes land-use policies (protection of basic farmlands and natural reserves), topography (elevation and slope), accessibility (distance to the human settlements), and potential productivity (fertility and irrigation). The study revealed the relationship between land-use spatio-temporal change and its driving factors in mountainous Southwest China, providing a decision-making basis for rational land-use management and optimal allocation of land resources.

Keywords: land use; spatio-temporal change; driving factors; binary logistic regression model (BLRM); artificial forest area; southwest China (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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