Comparative Study of Pixel-Based and Object-Based Classifications in Benthic Mapping

A. N. Othman, Nurhanisah Hashim, Pauziyah Mohamad Salim, Puteri Norsarifah Suhada Mohd Zaidi
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Abstract

Coral reefs have been degrading rapidly throughout the last decade due to climate change and other human activities. Classification and mapping of benthic floors and associated ecosystems such as coral reefs are both inefficient and expensive using traditional ground-based methods. New technologies using publicly available and commercial satellite imageries are crucial for accurate classification and mapping of coral reefs' distribution, management and monitoring. The study utilized the medium (Sentinel 2B with 20 m) and high (SPOT 7 with 1.5m) resolution satellite imageries for benthic mapping of Mabul island’s benthic using pixel-based and object-based classification methods. Results of the study show that the overall accuracy of the pixel-based classification method for Sentinel 2 and SPOT 7 were 97.5% and 90%, respectively. For the object-based technique, the overall classification was slightly lower with 87.05% and 82.81%, respectively. This study suggests pixel-based classification provides better overall accuracy than object-based classification. However, conducting more assessments at different water depths and field surveys is necessary to determine accurate results. This can be achieved in the future by using more advanced technology such as drones and lidar data.
底栖生物制图中基于像素和基于对象分类的比较研究
在过去十年中,由于气候变化和其他人类活动,珊瑚礁正在迅速退化。使用传统的地面方法对底栖层和相关生态系统(如珊瑚礁)进行分类和绘制地图既低效又昂贵。利用公开和商业卫星图像的新技术对于珊瑚礁的分布、管理和监测的准确分类和绘图至关重要。该研究利用中分辨率(Sentinel 2B,分辨率为20 m)和高分辨率(SPOT 7,分辨率为1.5m)卫星图像,采用基于像素和基于对象的分类方法对Mabul岛的底栖生物进行了测绘。研究结果表明,Sentinel 2和SPOT 7基于像元的分类方法的总体准确率分别为97.5%和90%。对于基于对象的技术,总体分类率略低,分别为87.05%和82.81%。该研究表明,基于像素的分类比基于对象的分类提供了更好的整体准确性。然而,为了确定准确的结果,需要在不同的水深和实地调查中进行更多的评估。这可以在未来通过使用更先进的技术,如无人机和激光雷达数据来实现。
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