Abstract
Coral reefs provide a range of ecological services and support highly diverse coastal ecosystem. However, the extent of living corals has been reduced by half globally as a result of anthropogenic natural stressors. Continuous monitoring by deploying accessible remote sensing (RS) methods to map coral habitats is necessary for effective conservation and management strategies. Recently, there has been an increased use of Remotely Piloted Aircraft Systems (RPAS) for coral reef RS. Image misalignment is considered a key problem in the Structure from Motion (SfM) workflow. Combinations of image alignment settings (IAS) and key point limit (KPL) optimizations aim to improve quality of the sparse cloud while lowering SfM reconstruction uncertainty, increasing projection accuracy, and ultimately improving coral habitat classification accuracy. In this study, the orthoimages were produced from a total of 25 IAS (lowest, low, medium, high and highest) and KPM (5k, 10k, 20k, 40k, and 60k) combinations using Agisoft™ Metashape software. Measurements of geometric distortion, efficiency, and completeness were used to evaluate these orthoimages with three visible bands. Results that satisfied the requirements for both geometric quality, spectral accuracy, processing efficiency identified the optimum alignment methods needed for routinely monitoring and mapping of coral reefs of Pulau Bidong. The SfM-image alignment techniques chosen for this study could produce the coral mapping extent, a higher number of tie points and matches, better image alignment success and coral habitat classification accuracy, less processing time and memory usage and no geometric distortions. The development of the methodology for the optimum parametrization of RPAS multispectral imagery would be beneficial to researchers studying coral reefs, marine sciences, and RS data analysts. It would provide them reliable methods for evaluating the quality of orthoimages and faster processing methods to achieve coastal RS objectives.
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