Author
Listed:
- Buting Hong
(School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, Nanjing 210023, China
Key Laboratory of Carbon Neutrality and Territory Optimization, Ministry of Natural Resources, Nanjing 210023, China)
- Jicheng Wang
(Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Ministry of Education, Sichuan Normal University, Chengdu 610066, China
Institute of Geography and Resources Science, Sichuan Normal University, Chengdu 610101, China)
- Jiangtao Xiao
(Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Ministry of Education, Sichuan Normal University, Chengdu 610066, China
Institute of Geography and Resources Science, Sichuan Normal University, Chengdu 610101, China)
- Quanzhi Yuan
(Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Ministry of Education, Sichuan Normal University, Chengdu 610066, China
Institute of Geography and Resources Science, Sichuan Normal University, Chengdu 610101, China)
- Ping Ren
(Key Laboratory of Land Resources Evaluation and Monitoring in Southwest China, Ministry of Education, Sichuan Normal University, Chengdu 610066, China
Institute of Geography and Resources Science, Sichuan Normal University, Chengdu 610101, China)
Abstract
Cropland abandonment (CA) is an increasingly severe global issue, with significant implications for achieving the Sustainable Development Goal of Zero Hunger. In China, widespread CA is particularly evident in remote mountainous regions. However, the rugged terrain and highly fragmented cropland pose significant challenges in mapping abandoned cropland with high precision using remote sensing technology. Moreover, CA is the result of multi-level factors, yet previous studies have primarily analyzed its driving factors from a single level, leading to a lack of comprehensive understanding of the underlying mechanisms. We took Sichuan Province, located in the mountainous regions of Western China, as a case study, utilizing satellite-derived high-precision CA maps to reveal the spatiotemporal patterns of CA. Additionally, we employed hierarchical linear model to explore the determinants of CA and their interactions at both county and municipal levels. The results indicate that the CA rate decreased continuously from 6.75% in 2019 to 4.47% in 2023, with abandoned cropland exhibiting significant spatial clustering. High-value clusters were predominantly concentrated in the western mountainous areas, and hotspots of CA exhibited a general migration trend from the northeast to the southwest. Furthermore, we found that CA is influenced by multi-level factors, with 61% and 39% of the variance in CA being explained at the county and municipal levels, respectively. The agglomeration index of cropland (AI) is a key determinant at the county level, with the Digital Elevation Model (DEM) and the distance to roads also playing significant roles. At the municipal level, urbanization rate and the proportion of non-agricultural employment (PNAE) are dominant factors, and an increase in PNAE weakens the negative impact of AI on CA rates. To curb CA in mountainous areas, we recommend implementing land consolidation projects, improving rural land transfer markets, and strengthening legal mechanisms to combat CA. Our study has broad application prospects, providing critical support for assessing the ecological and environmental consequences of CA and exploring the potential of reutilizing abandoned cropland for food production, bioenergy, and carbon sequestration.
Suggested Citation
Buting Hong & Jicheng Wang & Jiangtao Xiao & Quanzhi Yuan & Ping Ren, 2025.
"Spatiotemporal Patterns and Determinants of Cropland Abandonment in Mountainous Regions of China: A Case Study of Sichuan Province,"
Land, MDPI, vol. 14(3), pages 1-25, March.
Handle:
RePEc:gam:jlands:v:14:y:2025:i:3:p:647-:d:1615182
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:14:y:2025:i:3:p:647-:d:1615182. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.