An Integrated Approach for Mapping Multi-Category Abandoned Cropland Based on Swin-Unet, Land-Use Trajectories and Phenological Features in a Double-Cropping Rice Region of Southern China

Cropland abandonment directly undermines the regional food supply, requiring accurate monitoring to inform protection and recultivation policies. However, multi-category abandoned-cropland mapping remains challenging in southern China’s double-cropping rice regions because fragmented fields, frequent cloud/rain conditions, and complex phenology can obscure abandonment signals. Focusing on a typical double-cropping rice region in southern China, this study first used Swin-UNet to generate annual land-use maps from 2018 to 2022 and derive interannual trajectories. It then identified non-cultivated cropland within each year using Normalized Difference Vegetation Index (NDVI) data from key phenological periods and block-adaptive Otsu thresholding. Overlaying cultivation status with land-use trajectories further subdivided non-cultivated cropland into construction-occupied abandoned, naturally abandoned cropland, and fallow cropland. Finally, the spatial differentiation of each type and the potential grain-production gains from recultivating naturally abandoned cropland were analyzed. Results showed that annual classification accuracies from 2018 to 2022 ranged from 94.7 to 95.5%, supporting reliable cropland change trajectory extraction. From 2019 to 2022, total abandoned area decreased from 546.60 km2 to 486.73 km2. Naturally abandoned cropland remained dominant but declined mainly because 18.5–21.7% of it was converted back to stable cropland annually, while construction-occupied abandonment increased and fallow cropland remained relatively stable. Natural abandonment concentrated on moderate slopes near settlements and roads, with a theoretical grain-production potential equivalent to 12.88–15.14% of Maoming’s annual grain output. This study advances abandoned-cropland monitoring from area estimation to type-specific process interpretation and recultivation-priority assessment in southern double-cropping rice regions.

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Journal
Remote Sensing
Published
2026-09-09
DOI
https://doi.org/10.3390/rs18183090
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

An Integrated Approach for Mapping Multi-Category Abandoned Cropland Based on Swin-Unet, Land-Use Trajectories and Phenological Features in a Double-Cropping Rice Region of Southern China

Yuhao Jin, Hengkang Zhu, Falin Zhuang, Xing Mao et al.
Remote Sensing
Remote Sensing in Agriculture
article

An Integrated Approach for Mapping Multi-Category Abandoned Cropland Based on Swin-Unet, Land-Use Trajectories and Phenological Features in a Double-Cropping Rice Region of Southern China

Yuhao Jin, Hengkang Zhu, Falin Zhuang, Xing Mao, Xiaozhen Qiu
article en

Abstract

Cropland abandonment directly undermines the regional food supply, requiring accurate monitoring to inform protection and recultivation policies. However, multi-category abandoned-cropland mapping remains challenging in southern China’s double-cropping rice regions because fragmented fields, frequent cloud/rain conditions, and complex phenology can obscure abandonment signals. Focusing on a typical double-cropping rice region in southern China, this study first used Swin-UNet to generate annual land-use maps from 2018 to 2022 and derive interannual trajectories. It then identified non-cultivated cropland within each year using Normalized Difference Vegetation Index (NDVI) data from key phenological periods and block-adaptive Otsu thresholding. Overlaying cultivation status with land-use trajectories further subdivided non-cultivated cropland into construction-occupied abandoned, naturally abandoned cropland, and fallow cropland. Finally, the spatial differentiation of each type and the potential grain-production gains from recultivating naturally abandoned cropland were analyzed. Results showed that annual classification accuracies from 2018 to 2022 ranged from 94.7 to 95.5%, supporting reliable cropland change trajectory extraction. From 2019 to 2022, total abandoned area decreased from 546.60 km2 to 486.73 km2. Naturally abandoned cropland remained dominant but declined mainly because 18.5–21.7% of it was converted back to stable cropland annually, while construction-occupied abandonment increased and fallow cropland remained relatively stable. Natural abandonment concentrated on moderate slopes near settlements and roads, with a theoretical grain-production potential equivalent to 12.88–15.14% of Maoming’s annual grain output. This study advances abandoned-cropland monitoring from area estimation to type-specific process interpretation and recultivation-priority assessment in southern double-cropping rice regions.

Remote SensingVol. 18(18)
South China Agricultural University (CN), Sun Yat-sen University (CN), Jiangsu Academy of Agricultural Sciences (CN)
Zero hunger
Openalex Percentile: Top 10%
Remote Sensing in Agriculture
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