An automated stand-alone in-field remote sensing system (SIRSS) for in-season crop monitoring

A stand-alone in field remote sensing system (SIRSS) with high spatial and temporal resolution was developed in this study. System control and image processing algorithms consisted of image acquisition control, camera parameter control, crop canopy reflectance calibration, image rectification, image background segmentation and vegetation indices map generation were developed and embedded in the SIRSS. The SIRSS is able to automatically capture multispectral images over a testing field at any predefined time points during the growing season and process captured images in real-time. This paper presents the SIRSS system design, image analysis procedures and determination of vegetation indices. In a validation experiment over an 8-plot corn field with three different nutrient treatments spanning the 2006 growing season, a total of 91 images were acquired and four different vegetation indices were derived from the images of each day. The largest differences of indices values among three treatments were indentified during the V6–V8 stages which implied this period could be the best time to detect variability caused by the nitrogen stress in the cornfield. The SIRSS has shown the potential of monitoring changes in vegetation status and condition.

► We develop a stand-alone in field remote sensing system (SIRSS) with high spatial and temporal resolution. ► We develop system control and image processing algorithms to automatically acquire and process images. ► We investigate temporal effects of vegetation indices.