Palm Oil Health Monitoring Based on Vegetation Index through Unmanned Aerial Vehicles (UAV)/Drone Tools
The plantation sector has an urgency in technological renewal and development, especially in palm oil. Palm oil commodities are included in the staples needed by the Indonesian people for various products and as one of the sectors that generate the largest foreign exchange. Palm oil plantation manag...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Gadjah Mada
2025-07-01
|
| Series: | Journal of Geospatial Information Science and Engineering |
| Subjects: | |
| Online Access: | https://jurnal.ugm.ac.id/jgise/article/view/99921 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850113772272746496 |
|---|---|
| author | Baskara Suprojo Fikri Ainur Rosyidi |
| author_facet | Baskara Suprojo Fikri Ainur Rosyidi |
| author_sort | Baskara Suprojo |
| collection | DOAJ |
| description | The plantation sector has an urgency in technological renewal and development, especially in palm oil. Palm oil commodities are included in the staples needed by the Indonesian people for various products and as one of the sectors that generate the largest foreign exchange. Palm oil plantation management practices that have been carried out manually are less able to control plant health, especially during the pandemic which has caused severe impacts in Indonesia. The purpose of this research is to showcase the implementation of Smart Agriculture through the utilization of Unmanned Aerial Vehicle (UAV)/Drone technology in determining palm oil health. This research uses spatial analysis to detect the level of palm oil health by utilizing aerial photographs and GIS software with the Visible Atmospherically Resistant Index (VARI) method which can detect differences in the wavelength of the spectrum reflected by the plant canopy. This research is located in Argomulyo Village, Sepaku District, Penajam Paser Utara Regency, East Kalimantan Province, with abundant palm oil plantations. It was found that out of 2,167 samples of palm oil plants in the studied plantation, 14% were very unhealthy, 34.61% were unhealthy, 36.54% were healthy, and 14.85% were very healthy. |
| format | Article |
| id | doaj-art-2d18dec64eb44b37a80d035232e14d9d |
| institution | OA Journals |
| issn | 2623-1182 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Universitas Gadjah Mada |
| record_format | Article |
| series | Journal of Geospatial Information Science and Engineering |
| spelling | doaj-art-2d18dec64eb44b37a80d035232e14d9d2025-08-20T02:37:04ZengUniversitas Gadjah MadaJournal of Geospatial Information Science and Engineering2623-11822025-07-0181759010.22146/jgise.9992137734Palm Oil Health Monitoring Based on Vegetation Index through Unmanned Aerial Vehicles (UAV)/Drone ToolsBaskara Suprojo0Fikri Ainur Rosyidi1Kantor Pertanahan Kabupaten Kutai KartanegaraSekolah Tinggi Pertanahan Nasional, IndonesiaThe plantation sector has an urgency in technological renewal and development, especially in palm oil. Palm oil commodities are included in the staples needed by the Indonesian people for various products and as one of the sectors that generate the largest foreign exchange. Palm oil plantation management practices that have been carried out manually are less able to control plant health, especially during the pandemic which has caused severe impacts in Indonesia. The purpose of this research is to showcase the implementation of Smart Agriculture through the utilization of Unmanned Aerial Vehicle (UAV)/Drone technology in determining palm oil health. This research uses spatial analysis to detect the level of palm oil health by utilizing aerial photographs and GIS software with the Visible Atmospherically Resistant Index (VARI) method which can detect differences in the wavelength of the spectrum reflected by the plant canopy. This research is located in Argomulyo Village, Sepaku District, Penajam Paser Utara Regency, East Kalimantan Province, with abundant palm oil plantations. It was found that out of 2,167 samples of palm oil plants in the studied plantation, 14% were very unhealthy, 34.61% were unhealthy, 36.54% were healthy, and 14.85% were very healthy.https://jurnal.ugm.ac.id/jgise/article/view/99921aerial photography, palm oil health, smart agriculture, vari |
| spellingShingle | Baskara Suprojo Fikri Ainur Rosyidi Palm Oil Health Monitoring Based on Vegetation Index through Unmanned Aerial Vehicles (UAV)/Drone Tools Journal of Geospatial Information Science and Engineering aerial photography, palm oil health, smart agriculture, vari |
| title | Palm Oil Health Monitoring Based on Vegetation Index through Unmanned Aerial Vehicles (UAV)/Drone Tools |
| title_full | Palm Oil Health Monitoring Based on Vegetation Index through Unmanned Aerial Vehicles (UAV)/Drone Tools |
| title_fullStr | Palm Oil Health Monitoring Based on Vegetation Index through Unmanned Aerial Vehicles (UAV)/Drone Tools |
| title_full_unstemmed | Palm Oil Health Monitoring Based on Vegetation Index through Unmanned Aerial Vehicles (UAV)/Drone Tools |
| title_short | Palm Oil Health Monitoring Based on Vegetation Index through Unmanned Aerial Vehicles (UAV)/Drone Tools |
| title_sort | palm oil health monitoring based on vegetation index through unmanned aerial vehicles uav drone tools |
| topic | aerial photography, palm oil health, smart agriculture, vari |
| url | https://jurnal.ugm.ac.id/jgise/article/view/99921 |
| work_keys_str_mv | AT baskarasuprojo palmoilhealthmonitoringbasedonvegetationindexthroughunmannedaerialvehiclesuavdronetools AT fikriainurrosyidi palmoilhealthmonitoringbasedonvegetationindexthroughunmannedaerialvehiclesuavdronetools |