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Low-Altitude Drone Based Imagery for Rice Productivity Estimation
Daniel Useng (a*), Christaldo W (a), Salengke (a)

a) Dept. od Agric. Engineering, Hasanuddin University, Indonesia
*) daniel.useng[at]agri.unhas.ac.id


Abstract

As the staple food of many countries in the world, rice paddy have been grown in many regions with different climatic and environmental conditions. The major problem in rice growing in tropical regions is the productivity that considered low compared to the potential yiels expected. This problem is due to many regulating factors such as low input of fertilizers and pest and diseases infestations.
Monitoring the crop conditions during the planting seasons can be used to estimate the potential yield expected at the end of the season. Crop imaging using the conventional camera (RGB) offer an important tools in precicting the crop conditions as well as the potetential yield of the crop. This research using the drone based imagery to monitor the ricecrop condition to predict the croop yield during the rainy season (August-November) in South Sulawesi - Indonesia. The crop yield is predicted using some vegetation indices (VI) developed based on the digital numbers of RGB images.
The result shows that some Vegetation Indices such as RGBVI (Red Green Blue Vegetation Index) and ExG (Excess Green)and others shows good correlations with crop yields especially on the images acquired around the maximum growth of the crop, i.e at 75 days after planting.

Keywords: Drone, Rice, Vegetation Index, RGB image

Topic: Geospatial Agriculture

Plain Format | Corresponding Author (Daniel Useng)

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