Tea is one of Indonesia's most famous commodities, which is dominantly planted on the Java Island of Indonesia. Tea is one of the leading sources of exports, and the Indonesian government is very concerned about the stability of their export commodity sustainability. Therefore, monitoring and evaluating its sustainability and availability become necessary. One of the solutions to the tea plantation monitoring and management program is mapping through remote sensing and GIS. In this study, high-resolution multispectral imageries are captured from a UAV and used to map the tea plantation with three vegetation indexes (VIs). An Object-Based Image Analysis (OBIA) is used to classify the tea field's condition based on spectral characteristics. The results of this study are: (i) high-resolution multispectral imageries can be used to map the tea plantation with different VIs, and (ii) SAVI is the best VI to map the tea plantation since it has the lowest RMSE value with observed data. Hopefully, this study can support the government program on their export commodity with valuable baseline information on the tea plantation.

Keywords: tea plantation mapping, OBIA, spatial analysis, vegetation index, UAV