Relationship of Ground- and Aerial Images-Based Normalized Difference Vegetation Indices of Major Crops Grown in Louisiana.

The use and application of optical remote sensing technology in managing nitrogen (N) fertilizer has been recently established in Louisiana’s crop production systems.  Monitoring plant health and acquisition of normalized difference vegetation index (NDVI) from aerial images taken by a digital camera attached to an unmanned aircraft vehicle has offered advantages in terms of size and speed of data acquisition. This study was conducted to establish the relationship between ground- and aerial image-based NDVI collected from canopies of rice, cotton, and sugarcane during the growth stage where mid-season N fertilizer was applied. For cotton and sugarcane, NDVI was collected and mapped using GreenSeeker® sensors installed in a high-clearance tractor equipped with a Trimble FMX field computer. For rice, NDVI was collected and mapped with a GreenSeeker handheld unit on foot. Images of crop canopies were taken using a multi-rotor copter (Precision Drone® Pacesetter) equipped with a camera modified to capture reflectance at the visible (red, blue, and green) and near infrared spectrum. Geo-referenced images of the canopies (red and near infrared) were converted into geo-referenced NDVI readings. The relationship between NDVI measured by GreenSeeker was highly correlated with aerial image-based NDVI in 2015 and 2016 in cotton, and in rice in 2016. For sugarcane, the correlation of NDVI taken by these two showed platforms were weaker compared to cotton and rice. There were some limitations identified that need to be addressed to ensure that the NDVI based on aerial-images is a reliable indicator of crop health. The preliminary results of this study suggest that among crop and growth stage cycle the correlation of NDVI readings converted from consumer type camera images are positively correlated with ground-based NDVI and has the same ability to determine crop N response.