A real-time multispectral remote sensing system with high spatial and temporal resolution was developed in this study. The main components of the system consisted of a CCD camera, a personal computer with a frame grabber board, three ground reflectance calibration panels and camera control software programmed in LabVIEW. The CCD camera was DuncanTech MS4100 multispectral camera with 1920×1080 pixels resolution and controllable via RS232 serial port. This system was mounted across the Morrow Plots in University of Illinois at Urbana-Champaign. It automatically captured RGB and CIR images at any expected time during the whole growing season. An artificial intelligent algorithm was introduced to control the camera parameters to realize image white balance under the ambient illumination conditions. The radiometric calibration and image analysis were completed automatically following each image acquisition. The seasonal trajectory of vegetation indices of different treated corn in Morrow Plots were created based on the large image dataset we acquired. SPAD value was collected as ground truth. Analyzing the relationships between ground truth and indices trajectory, crop growth status could be accessed through indices trajectory.