Abstract: Sugarcane planting in Guangxi has been affected by natural disasters, resulting in decreased yields. The information on spatio-temporal dynamics of the sugarcane planting area and growth can provide a reference for planting structure optimization and facilitate disaster control. This study incorporated 652 optimized band combinations of the LANDSAT 8 Operational Land Imager (OLI), normalized difference vegetation index (NDVI), digital elevation model (DEM), and other auxiliary identification characteristic variables into the random forest classification method to interpret continuously in multi-temporal aspects. Google Earth and high-resolution remote sensing image comparison and correction were used to obtain a high-precision sugarcane planting area distribution in Guangxi from 2014 to 2018. The MODIS-NDVI data was used to build a monitoring model of the growth potential difference for dynamic monitoring of sugarcane stem elongation in Guangxi in the last five years. The results showed that: 1) the interpretation method was effective, the overall classification accuracy of sugarcane planting area in Guangxi was >92%, the Kappa coefficient was >0.8, and the five-year mean area relative error was -10.7%. 2) In 2014-2018, the planting area of sugarcane in Guangxi had rapidly decreased in the early stage and slowly increased in the late stage. The main planting areas were in Chongzuo, Nanning, and Laibin. The whole planting area showed a distribution pattern of local agglomeration and overall fragmentation and dispersion, which was closely related to the underlying environmental elements, such as topography, soil type, and river system distribution. 3) The NDVI difference model reflected the interannual and intra-annual spatio-temporal changes in the elongation trend of sugarcane stems in Guangxi, and the yearly growth trend of sugarcane changes frequently between good, normal, and poor. These results revealed the response mechanism of sugarcane in Guangxi to regional climate change, alternation of drought and flood, and the dynamics of soil and water conservation on the underlying surface. Furthermore, this study provides a scientific foundation for optimizing the regional sugarcane planting structure and evaluating water resource utilization efficiency.