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All Journal Journal of Geospatial Science and Technology
Gema Wahyu Fadhilah
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Earth & Planetary Sciences Engineering

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The Impact of Tree Density on Automated Oil Palm Tree Counting Accuracy Gema Wahyu Fadhilah; Hanif Ilmawan
Journal of Geospatial Science and Technology Vol 2 No 1 (2024): Journal of Geospatial Science and Technology
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jgst.v2i1.13691

Abstract

The rapid development of oil palm plantations in Kualuh Leidong Subdistrict, Labuhanbatu Utara District, North Sumatra Province has led to an increased need for effective and efficient monitoring and supervision of oil palm trees. One method that supports such monitoring and supervision is the use of an automatic counting method using orthophoto data. This orthophoto data was used for automatic tree counting using a deep learning method with the Faster R-CNN algorithm. The study considered two planting patterns: regular planting patterns with spacing of 4 to 9 meters, and random planting patterns with varying spacing. Data processing involved an epoch value of 80 and a batch size value of 4. The accuracy of the automatic oil palm tree counting was evaluated based on the density of the spacing between trees with reference to the ground truth. The findings indicated that the deep learning Faster R-CNN algorithm achieved higher accuracy in automatic calculations for regular planting patterns.
Co-Authors Hanif Ilmawan