Abstract: It is a critical step to achieve characteristics of trees in various sizes and shapes for modernizing agriculture applications. Target detection could provide technical data for variable-rate precision spraying of agriculture and forestry management. In order to measure the spray targets accurately, an indoor target detection sliding table platform with UTM-30LX laser sensor was built to detect regular-shape objects and artificial trees. A C language-based algorithm was developed to scan and save laser object data in real time, and an image reconstruction algorithm designed with MATLAB software was used to reconstruct laser object data slices to 3-D canopy images and measure tree sizes. The measurement accuracy of the 3-dimentioal reconstruction images of the spray targets were analyzed by the maximum relative error and edge similarity score. The system accuracy was tested with scanning objects of one rectangular cabinet, one foam cylinder and two artificial trees under indoor laboratory conditions for scanning distances of 2.0 to 2.8 m and sensor travel speeds of 0.3 to 0.9 m/s. Results show that the maximum relative errors about length, width and height of the rectangular cabinet are 6.76%, 6.86% and 3.92% compared with manual measurements in multiple measurements, the maximum relative errors about height and diameter of the foam cylinder are 4.25% and 7.33%, the maximum relative errors about height and width of two artificial trees are 4.06%, 5.91% and 3.24%, 4.00% respectively; The minimum edge similarity scores of the two artificial trees are 0.928 8 and 0.932 6 respectively by several experiments. Results verify the accuracy and precision of UTM-30LX laser sensor on several environments and prove that UTM-30LX laser sensor can be applied in the area of variable-rate precision spraying for the detection of targets.