Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 739, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.scitotenv.2020.139622
Keywords
Land cover change; Cluster analysis; Structural equation modeling; Mixed-effects model; Scale effects; Loess Plateau
Categories
Funding
- Chinese Academy of Sciences [XDA23070201]
- National Key Research and Development Program of China [2016YFC0501601]
- International Partnership Program of Chinese Academy of Sciences [121311KYSB20170004]
Ask authors/readers for more resources
Land cover change (LCC) is a major part of environmental change. Exploring the spatiotemporal differences in LCC and the driving factors is the basis for comprehensive research on landscape planning, and it is of great significance for future effective and sustainable landscape management. In this respect, cross-scale research with integrated methods is worthy of more attention, although some studies have discussed the driving forces of LCCs at either regional or local scale. We combined a structural equation model and a mixed-effects model for quantifying the driving forces of LCCs across different scales in the Loess Plateau (China), which is a typical region that has experienced significant LCCs over recent decades.The impacts of biophysical and socioeconomic factors on different change trajectories (agricultural intensification, urbanization and ecological restoration) were found to be inconsistent at different temporal and spatial scales. We found that topography had a negative effect on agricultural intensification during 1990-2010 and on urbanization during 1990-2000, but it had a positive effect on ecological restoration during 2000-2015 at the regional scale. Moreover, although there was no significant impact from economic development on any type of LCCs at the regional scale, its important influence could be seen in some of the township categories. Therefore, the path and scale dependence of driving forces is an important consideration in landscape planning and management to accommodate local conditions and fine-tuned analysis as decision-making supports. (C) 2020 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available