Paddy field mapping using UAV multi-spectral imagery

Abstract

Paddy is the most famous crop in Indonesia, which dominantly planted primarily in the west and central part of Indonesia. Rice paddy field is the main food source for most of the Indonesian and Indonesian government are very considered about the stability of their food security program. Therefore, monitoring and evaluation of its sustainability and availability become a national priority. One of the solutions to agricultural monitoring and management program is mapping through remote sensing system. In the study, we used high-resolution multi-spectral imagery collected from unmanned aerial vehicles (UAV) to map the paddy field and differentiate them based on their spectral characteristics. An Object-Based Image Analysis (OBIA) method applied to the image for classifying the stage rice paddy field based on their spectral signature. The results of this study are: (i) a high-resolution map of paddy field and its classifications based on the period of planting, (ii) a comparison table showing the different spectral response for a different type of crops such as banana and tea. Hopefully, this study can support the government program on food security with valuable baseline information of the paddy field.