LiDAR (light detection and ranging) sensors have shown good potential to estimate canopy volume and guide variable rate applications in different fruit crops. Oranges are a major crop in Brazil; however the spatial variability of geometrical parameters remains still unknown in large commercial groves, as well as the potential benefit of sensor guided variable rate applications. Thus, the objective of this work was to characterize the spatial variability of the canopy volume in a commercial orange grove. A 25 ha orange grove located in São Paulo, Brazil was chosen for this study. A 2D LiDAR sensor and a GNSS (Global Navigation Satellite System) receiver were mounted on a vehicle to scan the sides of the tree rows as the vehicle moved along the alleys. At each scan, distance values were collected in 181 different directions in the vertical plane. Data were converted into a tridimensional georeferenced point cloud from which the canopy volume of individual trees was computed. A geostatistical analysis was performed to characterize the field’s variability. The canopy volume varied from 1.29 to 26.5 m³ per tree showing a coefficient of variation of 20%. The geostatistical analyses showed a weak spatial dependence and a range of 127 m. The variability found in this field suggests that sensor-based variable rate applications is an appropriate approach to manage inputs according to tree canopy volume variability.