Greyback canegrub, Dermolepida albohirtum (Scarabaeidae), is the major pest of the sugarcane industry in Queensland, Australia. Assuming that the vegetation and especially tree species and structure may influence the presence and the dispersal behavior of this pest and thus the spatial variation of damage to sugarcane fields, we analyzed the relationships between landscape indices derived from very high spatial resolution imagery and the occurrence of canegrub damage occurrence. Firstly, we applied object-based image processing techniques on a GeoEye satellite image to produce a detailed land-cover map of the study area in Mulgrave. Secondly, based on the knowledge of canegrub ecology, six landscape attributes were defined and computed from the land-cover map. Thirdly, the relationships between landscape attributes and canegrub damage collected from 2008 to 2013 were analyzed through a generalized linear model. Finally, the best statistical model according to the Akaike Information Criterion (AIC) was used to map areas at risk for canegrub infestation. Among the derived landscape variables, the tree density index around the sugarcane fields, the proximity to forest, and the proximity to palm plantations were all positively correlated with canegrub damage (p<0.001), confirming the importance of trees in the damage occurrence. Our results highlighted the potential of very high spatial resolution remote sensing to identify environmental risk factors and generate risk maps for canegrub damage.