Author
Listed:
- Yao Cui
(School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China)
- Hongrui Sun
(Ningxia Hui Autonomous Region Natural Resources Survey and Investigation Institute, Yinchuan 750000, China)
- Yaolin Liu
(School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China)
- Ligang Wang
(Ningxia Natural Resources Information Center, Yinchuan 750000, China)
- Yanfang Liu
(School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China)
- Rui An
(School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China)
- Xinyue Zhang
(Chinese Academy of Surveying and Mapping, Beijing 100830, China)
- Yifan Xie
(School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China)
- Lin Zhang
(School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China)
- Jiwei Xu
(School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China)
Abstract
Non-grain use of cultivated land (NGUCL) in ecologically fragile regions has become a major challenge to food security and land sustainability, yet its spatiotemporal dynamics, spatial spillover effects, and associated factors remain insufficiently understood. Taking Ningxia, China, as a typical semi-arid to arid transition zone, this study developed a phenology-informed framework that combined multi-temporal Landsat imagery, random forest classification, spatial autocorrelation analysis, centroid and standard deviation ellipse models, and a spatial lag model to identify and analyze NGUCL in 2005, 2010, 2015, and 2020. Within the cultivated land boundary, NGUCL was further decomposed into cash crop-cultivated farmland (CCCF) and farmland abandonment (FA). The results show that the classification framework achieved robust performance, with overall accuracies above 85% across the benchmark years. Food-crop mapping reached an OA of 86.38–90.12% and a Kappa of 0.80–0.85, while FA mapping reached an OA of 85.60–86.74% and a Kappa of 0.70–0.72. NGUCL in Ningxia exhibited strong subregional differentiation under the gradients of northern irrigation, central arid, and southern mountainous conditions. CCCF was more closely associated with irrigated and agriculturally productive areas, whereas FA was concentrated in ecologically constrained counties and showed stronger dispersion and migration complexity. Spatial econometric results further indicate significant spatial spillover effects, suggesting that NGUCL-related processes in one county are associated with those in neighboring counties. The effects of natural, socioeconomic, and agricultural production factors also varied by type and period, indicating that NGUCL in ecologically fragile regions is not a homogeneous land-use transition process. By distinguishing CCCF from FA, this study provides a more nuanced interpretation of NGUCL and offers empirical evidence for understanding cultivated land transition and governance in ecologically fragile areas.
Suggested Citation
Yao Cui & Hongrui Sun & Yaolin Liu & Ligang Wang & Yanfang Liu & Rui An & Xinyue Zhang & Yifan Xie & Lin Zhang & Jiwei Xu, 2026.
"Spatiotemporal Dynamics, Spatial Spillover Effects, and Driving Mechanisms of Non-Grain Use of Cultivated Land in an Ecologically Fragile Region,"
Land, MDPI, vol. 15(6), pages 1-24, May.
Handle:
RePEc:gam:jlands:v:15:y:2026:i:6:p:910-:d:1951372
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:15:y:2026:i:6:p:910-:d:1951372. 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.