Integration of Low-Cost GNSS and Multispectral Camera to Increase Oil Palm Position Accuracy and Health Monitoring

The Global Navigation Satellite System facilitates efficient agricultural initiatives, resolving land ownership and precise plantation monitoring issues. The oil palm sector is deeply integrated into various economies due to the world's use in food supplies, cosmetics, and oil biodiesel production. However, local farmers have trouble managing the plantation’s condition and land ownership due to the underdeveloped modern technology at their disposal. The Normalized Difference Vegetation Index was employed in order to assess the NDVI camera oil palm tree growth, utilizing a MAPIR Survey3 RGN Multispectral Camera integrated with red, green, and near IR sensors. Images were taken directly on the surface level to enable focused analysis on the palm trees. This included the use of an MPAR calibration ground target placed beside the leaves for data accuracy and an operator that held the camera to the trees. Utilizing this strategy allowed for a more intricate and detailed analysis of each oil palm tree, and due to the coordination of the trees, aerial images were produced to create a detailed image. Low-cost GNSS instruments alongside RTK technology were employed in determining the coordinate position of the oil palm trees. Considerable relationships were found between NDVI and content in chlorophyll: NDVI-G and Chl a (r = 0.679), NDVI-B and Chl a (r = 0.618), and NDVI-B and Chl b(r = 0.657). The positional errors obtained varied within –0.105 to 0.166 meters for low-cost GNSS and –0.159 to 0.083 meters for geodetic GNSS, the latter recording the least MAE of 0.053. This research work found a cheap and accurate oil palm growth monitoring system using multispectral sensors. This method overcomes the technological gap of local farmers and provides an alternative strategy for the management of plantations. Doi: 10.28991/CEJ-2025-011-03-010 Full Text: PDF

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Journal
Civil Engineering Journal
Published
2025-03-01
DOI
https://doi.org/10.28991/cej-2025-011-03-010
Citations
2
Primary Topic
Vehicle License Plate Recognition
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article
Field-Weighted Citation Impact
2.27
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article

Integration of Low-Cost GNSS and Multispectral Camera to Increase Oil Palm Position Accuracy and Health Monitoring

Deni Kusumawardani, Lisnawita Lisnawita, Fadlilatul Taufany, Luki Adi Triawan et al.
2 citations
Civil Engineering Journal
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article

Integration of Low-Cost GNSS and Multispectral Camera to Increase Oil Palm Position Accuracy and Health Monitoring

Deni Kusumawardani, Lisnawita Lisnawita, Fadlilatul Taufany, Luki Adi Triawan, Mokhamad Nur Cahyadi, Muhammad Aldila Syariz, F. Haq, S. S. Wismaroh, T. B. Saputro, Miko Cahya Laksmana
article en
2 citations

Abstract

The Global Navigation Satellite System facilitates efficient agricultural initiatives, resolving land ownership and precise plantation monitoring issues. The oil palm sector is deeply integrated into various economies due to the world's use in food supplies, cosmetics, and oil biodiesel production. However, local farmers have trouble managing the plantation’s condition and land ownership due to the underdeveloped modern technology at their disposal. The Normalized Difference Vegetation Index was employed in order to assess the NDVI camera oil palm tree growth, utilizing a MAPIR Survey3 RGN Multispectral Camera integrated with red, green, and near IR sensors. Images were taken directly on the surface level to enable focused analysis on the palm trees. This included the use of an MPAR calibration ground target placed beside the leaves for data accuracy and an operator that held the camera to the trees. Utilizing this strategy allowed for a more intricate and detailed analysis of each oil palm tree, and due to the coordination of the trees, aerial images were produced to create a detailed image. Low-cost GNSS instruments alongside RTK technology were employed in determining the coordinate position of the oil palm trees. Considerable relationships were found between NDVI and content in chlorophyll: NDVI-G and Chl a (r = 0.679), NDVI-B and Chl a (r = 0.618), and NDVI-B and Chl b(r = 0.657). The positional errors obtained varied within –0.105 to 0.166 meters for low-cost GNSS and –0.159 to 0.083 meters for geodetic GNSS, the latter recording the least MAE of 0.053. This research work found a cheap and accurate oil palm growth monitoring system using multispectral sensors. This method overcomes the technological gap of local farmers and provides an alternative strategy for the management of plantations. Doi: 10.28991/CEJ-2025-011-03-010 Full Text: PDF

Civil Engineering JournalVol. 11(3)
Sepuluh Nopember Institute of Technology (ID), Universitas Airlangga (ID), Universitas Sumatera Utara (ID), Universitas Pembinaan Masyarakat Indonesia Medan (ID)
Openalex Percentile: Top 13%
Vehicle License Plate Recognition
2.27
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