A tree counting algorithm for precision agriculture tasks

Abstract

Abstract This study proposes an automatic procedure for individual fruit tree identification using GeoEye-1 sensor data. Depending on site-specific pruning practices, the morphologic characteristics of tree crowns may generate one or more brightness peaks (tree top) on the imagery. To optimize tree counting and to minimize typical background noises from orchards (i.e. bare soil, weeds, and man-made objects), a four-step algorithm was implemented with spatial transforms and functions suitable for spaced stands (asymmetrical smoothing filter, local minimum filter, mask layer, and spatial aggregation operator). System performance was evaluated through objective criteria, showing consistent results in fast capturing tree position for precision agriculture tasks.