Assessment and Inventory of Palms in a Plantation by Template Matching of Unmanned Aerial Vehicle (UAV) Image

Abstract

The cost of acquiring real time, high resolution spatial datasets required for effective management of plantation has been a major challenge to farm management in developing country like Nigeria. But recent commercialization of Unmanned Aerial Vehicles (UAVs) has gradually made an affordable means of acquiring these spatial datasets available to individuals and small organizations. This study counts the palm trees in a palm plantation by template matching of digital orthophoto produced by a low cost Unmanned Aerial Vehicle. An aerial survey was carried out at Obafemi Awolowo Teaching and Research Farm using Phantom II Vision quadcopter. Using a flying altitude of 100 m, the plantation, which covers a land area of about 56,0002 m and containing 663 mature palm trees, was surveyed using the UAV. An 11 cm Orthophoto and Digital Surface Model (DSM) were produced. Template Matching algorithm was used to extract individual palm tree stand unto a thematic vector layer. The palm tree distribution map was produced after errors have been corrected using the DSM. The procedure shows that there are 572 palms present in the plantation with 86.27% accuracy in comparison with manual counting. The distribution of the palms in the plantation indicates underutilization of the plantation due to presence of empty and uncultivated area in the plantation. Also, there are presence of foreign trees in the plantation which might be competing with the palm trees for nutrients and thereby reducing the total yield of the plantation.