Using LAPER Quadcopter Imagery for Precision Oil Palm Geospatial Intelligence (OP GeoInt)

Abstract

Maintaining consistent productive health of perennial crop such an oil palm is challenging, yet crucial for sustaining optimum yield. Oil palm production requires precision farming (PF) solution which conventionally makes use satellite remote sensing techniques to capture agricultural data. Nevertheless, such techniques suffer from constraints due to low spatial and temporal resolution as well as autonomy issues. Proliferation of micro unmanned aerial vehicles (UAVs) has made production of digital aerial imagery (DAI) become cheaper and easier. DAI conjugated with advances in photogrammetry workflow and analytics post-processing enable powerful geovisualization manipulation. Advance geovisualization manipulation of DAI has promising potentials to leverage precision oil palm (POP) farming. The study reported in this paper aims to adapt UAV-based personal remote sensing (PRS) techniques in producing DAI geovisualization and mapping to accommodate POP provisioning. A Study were carried out using Low Altitudes Personal Remote Sensing (LAPER), a customized micro UAV quadcopter, for acquiring oil palm DAI, and extensive postprocessing workflow in producing oil palm explorative geovisualization and actionable base maps. Various simple yet insightful and actionable oil palm base maps were generated from the workflow. The paper concludes that LAPER is capable of adequately supplying temporal geospatial data for provisioning POP and oil palm geospatial intelligence (GeoInt) and oil palm planters can make use of LAPER imagery for geovisualization tasks for suggesting systematic actions in plantation management.