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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

Sep 2026 · Remote Sensing · 0 citations · 50 references

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.

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