Acquiring detailed information on wetland plant species is critical for monitoring wetland ecosystem restoration and management. The emerging technique of Unmanned Aircraft System (UAS) photogrammetry has immense potential for such applications. In this study, we assessed the capacity of UAS photogrammetric products for classifying and mapping a large number of wetland plant species using contemporary Object-Based Image Analysis (OBIA) and machine learning methods. Our testing results in a heterogeneous coastal wetland demonstrated the benefit of centimeter-level orthoimagery and vertical products from UAS photogrammetry for mapping 17 species compared with standard aerial photography products. We achieved an overall accuracy (OA) of 71.3% and 84.8% for mapping 17 species and 10 major species, respectively. Our study suggests that UAS photogrammetry is a valuable tool for mapping wetland species composition and distribution.

获取有关湿地植物物种的详细信息对于监测湿地生态系统的恢复和管理至关重要。无人机系统（UAS）摄影测量技术的新兴技术在此类应用中具有巨大的潜力。在这项研究中，我们使用当代的基于对象的图像分析（OBIA）和机器学习方法，评估了UAS摄影测量产品对大量湿地植物物种进行分类和绘制地图的能力。我们在异质沿海湿地上的测试结果表明，与标准航空摄影产品相比，UAS摄影测量技术所获得的厘米级正射影像和垂直影像可用于绘制17种物种。我们分别绘制17个物种和10个主要物种的总准确度（OA）为71.3％和84.8％。