IDENTIFICATION OF IRRIGATION CHANNELS USING LIDAR DRONE TECHNOLOGY USING OBJECT-BASED IMAGE ANALYSIS METHOD (OBIA)
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Abstract
Irrigation infrastructure is a facility structure that can support all activities related to irrigation. The existence of irrigation infrastructure that can function optimally and effectively, especially to meet agricultural water needs can increase agricultural productivity. Maintenance of irrigation infrastructure is one of the efforts to protect food agricultural land and can sustainably support the national food security program. Monitoring of the condition of assets that support the function of the irrigation network infrastructure on a regular basis needs to be carried out. Monitoring the physical condition of irrigation canals plays an important role because irrigation canals are a sustainable system for supplying water to many agricultural areas. In addition, irrigation canals can also function to protect agricultural crops from flooding and inundation due to excess water. Unmanned aerial vehicle or drone technology can be an alternative to monitoring irrigation channels. High-resolution images obtained from this technology can provide clear results with a high level of detail. Besides being able to carry camera sensors, the addition of LiDAR sensors on drones can add important information about physical conditions for the benefit of monitoring irrigation canals. This study was conducted to determine the potential of LiDAR drones for identification of irrigation canals that have several dimensions. The method used in this study uses analysis with OBIA (Object Based Image Analysis). The addition of information from LiDAR can increase the accuracy for identification of irrigation canals in orthophoto images with a resolution of 8 millimeters.
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