Development of Automatic Counting System for Palm Oil Tree Based on Remote Sensing Imagery

DOI

10.2991/978-94-6463-086-2_68How to use a DOI?

Keywords

Palm oil; Deep learning; Remote sensing; You only look once

Abstract

Data on the number of palm oil tree plantations on cultivated land is essential in a company's cultivation activities. Limitations of collecting data number of palm oil trees using the terrestrial method are the effectiveness of times, in terms of costs, and coverage area. Utilization of remote sensing with aerial imagery and deep learning method could present the results more efficiently. This research aims to detect and calculate the number of palm oil trees using the You Only Look Once (YOLO) version 3 architecture object detection model based on remote sensing imagery. The aerial image is collected using the Unmanned Aerial Vehicle (UAV) to train and validation the model. The detection results by the model are stored as a shapefile for further processing using the Quantum Geographic Information System (Q-GIS) to determine the number and display the detection results of palm oil trees. The total number of objects detected as trees through the model is 559 palm oil trees. The actual number of palm oil trees recorded was 590 palm oil trees. Based on the Mean Average Percentage Error (MAPE) value obtained, which is 0.057627, it shows that the model built is good and can be used to estimate the number of palm oil trees. In the future, evaluation and optimization of the model can be carried out by adjusting the number of iterations and increasing the amount of training data.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Mukhes Sri Muna
AU  - Andri Prima Nugroho
AU  - Muhdan Syarovy
AU  - Ardan Wiratmoko
AU  - Suwardi
AU  - Lilik Sutiarso
PY  - 2022
DA  - 2022/12/28
TI  - Development of Automatic Counting System for Palm Oil Tree Based on Remote Sensing Imagery
BT  - Proceedings of the International Conference on Sustainable Environment, Agriculture and Tourism (ICOSEAT 2022)
PB  - Atlantis Press
SP  - 503
EP  - 508
SN  - 2468-5747
UR  - https://doi.org/10.2991/978-94-6463-086-2_68
DO  - 10.2991/978-94-6463-086-2_68
ID  - Muna2022
ER  -