## 5 Conclusions  
In this study, we performed a change detection analysis using high-resolution satellite imagery from multiple time points, constructed training and validation datasets, and applied a random forest classification model to detect abandoned farmland. The results were subsequently subjected to accuracy assessment and spatial distribution analysis. Based on the detected abandoned farmland areas, we analyzed various factors influencing farmland abandonment, including the terrain slope, proximity to residential areas, access to irrigation resources, and transportation infrastructure, to investigate how these factors collectively contribute to the farmland abandonment process. The following conclusions were drawn:  
Abandoned farmland samples were identified using high-resolution imagery, and a random forest classification model was employed to classify the abandoned farmland. Inthe study area, the area of perennial abandoned farmland in the study area is 83.49 hm\({}^{2}\), while the areas of seasonal abandoned farmland for the two periods are 123.10 hm\({}^{2}\) and 454.39 hm\({}^{2}\). The overall classification accuracy is 93.29%. This method is both straightforward and highly accurate, making it well-suited for research on abandoned farmland in tropical regions.  
Based on the results of abandoned farmland extraction, the characteristics of abandoned farmland in the study area were analyzed. Spatial distribution analysis reveals that seasonal abandonment is more widespread than perennial abandonment in the study area. Larger and contiguous areas of abandoned farmland are located in the southeastern part of Qiaotou Township, while smaller patches of abandoned farmland are scattered throughout the region. Regarding the driving factors, large areas of abandoned farmland are predominantly found in regions with relatively gentle slopes, indicating that slope has minimal influence on abandonment. Furthermore, large areas of abandonment are concentrated in regions characterized by poor irrigation conditions, high road network density, and proximity to residential areas, suggesting that these factors significantly influence farmland abandonment. Abandonment due to slope is categorized as a natural ecological type, which can be managed through the reasonable adjustment of agricultural cropping patterns. In contrast, abandonment resulting from irrigation limitations, inadequate transportation infrastructure, and proximity to residential areas is considered a production-related type of abandonment. This type can be addressed by improving irrigation infrastructure, enhancing road networks for better access, and promoting land consolidation or leasing for large-scale agricultural production.  
W.S. resources, data curation, investigation, methodology, software, visualization, writing--original draft; Y.H. supervision, methodology, visualization, writing--review and editing, project administration, funding acquisition; F.X. methodology, software, validation; X.F. supervision, methodology, software, editing; H.Y. resources, methodology; H.D. methodology, software; L.W. supervision, methodology, writing--review and editing, project administration, funding acquisition. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Open Fund of Key Laboratory of Tropical and Subtropical Natural Resources Monitoring in South China, Ministry of Natural Resources (2023 NRRMK05), the National Key R&D Program of China (2023 YFD1900101), and the High-resolution Earth Observation System National Science and Technology Major Project (85-Y50G26-9001-22/23; 83-Y50G23-9001-22/23).  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.