Oil Palm Nutrient Mapping Using Multispectral Drone

Abstract

Unmanned Aerial Vehicle (UAV) is one of the platforms that have recently proven profitable in agriculture, despite being more commonly used as a carriage platform.  Nevertheless, the use of UAVs for mapping promotes precision agriculture. Foliage mapping and nutrient mapping are examples of mapping techniques that are beneficial for oil palm. Assessing the condition and distribution of nutrient content is essential for plantation management to monitor the health of the trees, identify potential problems such as nutrient deficiency or pest infestation, and optimise management practices for higher yields. Therefore, this study aims to produce nutrient content information from UAV and spectroradiometer data. Compact remote sensing sensors operating at visible (RGB) (0.4-0.7 micrometre), Near Infra-red (NIR) (0.7-1.2 micrometre), thermal infrared (TIR) and Long-wave Infrared (LWIR) bands (7-14 micrometre) were used in this study to determine the concentration of foliage content in the oil palm plantation. Nutrient elements such as Nitrogen (N), Phosphorus (P), Potassium (K), Calcium (Ca), and Magnesium (Mg) were detected from the foliar content as indicated in the 17^th frond of oil palm leaves. This study successfully developed a method for identifying and quantifying the nutrient content of oil palm plantations using a drone platform. This study would aid in predicting oil palm production and provide farm owners and managers with valuable decision-making information.