OPTIMIZING LOW-COST UAV AERIAL IMAGE MOSAICING FOR CROP GROWTH MONITORING

Abstract. High spatial resolution images acquired with drones can provide useful information to farmers for devising suitable management practices and increase crop yield. Data collected as individual frames or have be mosaiced using pattern recognition matching process. Most flight missions collect hundreds of photos high overlap side in order generate mosaic without data gaps distortion. These are aligned the location associated each image. The same features identified multiple generating mosaic. In this process, it is common use all most which requires a lot resources. Uploading processing could take several hours days. Many consultants developing countries may not necessary resources upload images. This study assessed optimal number required an image field any Images were at two different heights directions. First, was generated (100%) followed by subsets containing 90%, through 50% Results obtained will assist us plan settings future acquiring