When ratoon longevity matters: Spatial and temporal analysis of sugarcane plant population patterns using features extracted from UAV images

Monitoring the spatial and temporal dynamics of plant populations in sugarcane fields is essential for site-specific management and for sustaining high yields over time. However, to the phenological characteristics of sugarcane make plant detection and mapping particularly challenging. This study aimed to analyze spatial and temporal changes in plant populations within sugarcane ratoon fields using unmanned aerial vehicle (UAV) imagery. The goal was to improve management in commercial plantations and to map susceptibility to plant reduction over time, based on features extracted from UAV data: terrain slope, sugarcane row (path), path angle, gap length, and plant population. UAV imagery was collected over two successive seasons, 2019 and 2020. RGB mosaics were split into tiles (40,000 square pixels) and then into 50 × 50-pixel windows, subsequently used for L∗a∗b∗-based K-means segmentation, identifying sugarcane clumps via centroid extraction and mask filtering, as well as gaps along the rows. Nineteen plots (representing diverse slopes and paths) were analyzed, comparing image-derived and manual plant counts. To assess susceptibility to plant reduction over time, principal component analysis (PCA) and cluster analysis were applied for classification and mapping. The K-means segmentation achieved 91.00 % accuracy in detecting sugarcane plants. Overall, the plant population decreased by 16.00 %, with a 0.70 m increase in gap length over the study period. Regions with terrain slopes of 5.00–8.00 % and above 8.00 % with curved paths had fewer plants compared to flatter areas. Higher terrain slopes correlated with a greater probability of plant population reduction over time. The susceptibility patterns were mapped, providing insights to support management decisions, including the identification of areas requiring replanting and planning for field renovation.