Development of Spatial Database System Based on Cloud Computing Remote Sensing for Monitoring of Oil Palm Plantation in Indonesia

Abstract

Oil palm plantations provide the highest amount of foreign exchange earnings for the Indonesian government. However, according to the Indonesian Ministry of Agriculture, the foreign exchange has dropped to 20%. Therefore, to increase oil palm productivity, the President Republic of Indonesia issued Instruction No. 6 of 2019 regarding National Action Plan for Sustainable Oil Palm Plantation 2019–2024, one of the actions to increase national oil palm productivity is strengthening data infrastructure. Considering that the oil palm plantations in Indonesia are highly extensive and spread across almost all parts of Indonesia, cloud computing remote sensing technology is a satisfactory solution for monitoring oil palm plantations. This study aims to develop a spatial database system for monitoring oil palm plantation in Indonesia based on cloud computing remote sensing data. The methodology includes user needs and spatial data identification as Indonesian regulations, combined with focus group discussions, normalized geographic data normalization, and spatial database development using conceptual, logical, and physical models and system design and data visualization. The resulting spatial database system for monitoring oil palm plantations in Indonesia based on cloud computing remote sensing has been constructed by leveraging data saved in the cloud on ArcGIS Living Atlas of The World. The data recorded in ArcGIS Online are then linked to a visualization system created using the ArcGIS operation dashboard. The dashboard has been developed based on user needs and displays information about oil palm plantation age, administration boundaries, rainfall, terrestrial ecosystems, hot spots, and weather conditions.