Malaysia is the world's second-largest exporter of palm oil after Indonesia, with about 5.08 million hectare of oil palm plantations. Most of the plantations are owned by private farmers who work on a small scale and desperately need an autonomous platform with an affordable price for crop management since it can provide quick and accurate information for making smart decisions. The drone is one of the breakthroughs for smart and precision agriculture farming. By recording high spatial and temporal resolution photos, drones can be vastly utilized intelligently, simply, and cost-effectively to monitor crop and vegetation factors. Recently, many have been considering using drones for agricultural purposes such as crop irrigation and growth for yield estimation, health determination, disease detection, and spraying. This technology is easy-to-operate, flexible, and low-cost. Drones can also provide live data from various types of sensors (multispectral, Near Infrared Reflectance (NIR), LiDAR, etc.), with high resolution imagery up to less than one centimeters per pixel. With this information, it can help a lot in replanting planning, oil palm data census for inventory data, calculation of land use, the distance between crops, canopy size, oil palm height, and crop density. All this data and information is very useful in the development of support systems in decision-making and estimating plantation management-based results.
|Schematic overview showed the different ways to extract spatial information in the areas, the useful platforms and the optimal UAV sensors, throughout a growing season of a crop. The optimal sensors for UAVs were also shown.|
Zailani Khuzaimah, Nazmi Mat Nawi, Siti Nooradzah Adam, Bahareh Kalantar, Okoli Jude Emeka and Naonori Ueda, Application and Potential of Drone Technology in Oil Palm Plantation: Potential and Limitations, Journal of Sensors, vol. 2022, Article ID 5385505, 18 pages, 2022.
Artikel penuh: https://doi.org/10.1155/2022/5385505
Tarikh Input: 29/09/2022 | Kemaskini: 29/09/2022 | ainzubaidah
UNIVERSITI PUTRA MALAYSIA
43400 UPM SERDANG