Evaluation Trial of Drought Damage of Rice Based on RGB Aerial Image by UAV - Giamerti, Yuti; Darmadi, Didi; Junaedi, Ahmad; Lubis, Iskandar; Sopandie, Didie; Yuanita Meishanti, Ospa Pea; Sari, Kartika; Hongo, Chiharu; Homma, Koki (Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia, 2024)
Unmanned Aerial Vehicle (UAV) remote sensing is recommended to evaluate damage quickly and quantitatively. Therefore, this study aimed to explore the use of RGB aerial images by UAV for evaluating drought damage of rice through canopy color and coverage. The procedures were conducted in the dry season of 2018 (August – September 2018) at the Balitkabi Experimental field, Muneng, Probolinggo, Indonesia. A split-plot experimental field design was used with 2 factors, namely drought treatments at growth stage (Vegetative/P1, Reproductive/ P2, Generative/P3, and Control/P0), and varieties (Jatiluhur/V1, IPB9G/V2, IPB 3S/V3, Hipa 19/V4, Inpari-17/ V5, Mekongga/V6, Mentik Wangi/V7, Ciherang/V8). Canopy temperature data were then obtained using FLUKE 574 Infrared Thermometer, while images were taken with an RGB camera (Zenmuse X5) attached to Drone DJI Inspire I. The images were taken twice during the treatment (4 DAT and 15 DAT), followed by analysis using QGIS 2.18 and ImageJ. The results showed that RGB aerial images by UAV could be used in agricultural insurance in Indonesia, and similar countries around the world. Although the effect on yield needed to be evaluated, quick assessment by UAV was still an effective tool. In addition, drought damage evaluation through canopy color was better than canopy coverage in terms of analysis. The conversion from RGB to Lab color space increased the determination coefficient in multiple regression of color values against temperature difference (Tc-Ta).