Plot-based analysis of pest and disease infestation by UAV imageries Daniel Useng (a*), M. Tahir Sapsal (a), Haerani (a), Elvetta (a)
(a) Dept of Agricultural Engineering, Hasanuddin University
* Corr. Author: daniel.useng[at]agri.unhas.ac.id
Abstract
Identification of rice pest attacks is currently still done manually by looking at the condition of the invested plants. This is less effective because the extent of pest and disease infestation cannot be identified precisely due to limited human vision, time constraints, and funding. Unmanned aerial vehicles (UAV) have been widely used in monitoring crop conditions as well as detecting diseased crops due to pests and diseases. This study aims to utilize the Standard RGB imagery obtained by drones to detect infested plants. The method applied field observations and mapping the infested area using GIS software. The results show that the percentage of area for attack by caterpillar stem borers is 9.62%, caterpillars are 2.88%, caterpillars are 10.57%, and planthoppers are 12.5% with some degree of severity.
Keywords: Rice, UAV image, Pest and disease infestation.
