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遥感技术以实时、准确、多尺度、可重复等优点广泛应用于红树林遥感制图中。目前,我国空间分辨率最高的红树林遥感制图是基于Sentinel数据产生的10米数据集,此外,大多中国红树林遥感制图中忽略了潮汐的影响,导致红树林遥感制图结果不精准。本文利用国产高分二号数据源,顾及潮汐淹没的影响实现空间分辨率1米的2020年中国红树林遥感制图。具体地,选取覆盖中国海岸线具有红树林分布的高分二号影像312景,首先对影像进行面向对象多尺度分割,采用红树林淹没指数作为顾及潮汐影响的表征参数,结合随机森林分类方法完成中国红树林高分遥感制图。研究结果表明：2020年中国红树林面积为29576.48 ha,95%的红树林主要分布在广西、广东、海南三个省份,其总体分类精度为92%,Kappa系数为0.89,尚未顾及潮汐影响的结果比顾及潮汐影响的结果少2531.24 ha。本文生产的红树林高分数据集可为中国红树林生态系统的监测、管理及评估提供高精度的数据支持,具有重要的实际应用价值。
Remote sensing technology is widely used in mangrove forest mapping with the advantages of real-time, accuracy, multi-scale and repeatability. Until now, mangrove forest dataset with the highest spatial resolution in China is produced by 10 m Sentinel data. In addition, most existing mangrove forest dataset in China ignored the influence of tide, leading to low spatial-resolution and inaccurate mapping. Based on Chinese Gaofen-2 images, this paper is aimed at mapping Chinese mangrove forests in 2020 with a spatial-resolution of 1 m under the tide. Specifically, 312 scenes of GaoFen-2 image covering China"s coastline were selected. Firstly, the selected images were segmented by object-based multi-scale method, and the submerged mangrove recognition index was used as a tidal influence indicator. Finally, the high-resolution mapping of mangrove forest in China was conducted by random forest classifier. The results show that the mangrove area in China in 2020 was 29576.48 ha, 95% of which were mainly distributed in Guangxi, Guangdong and Hainan Provinces. The overall classification accuracy was 92% and Kappa coefficient was 0.89. The mangrove area without tidal influence was 2531.24 ha less than that with tidal influence. The high-resolution mangrove dataset generated in this paper can provide high-precision data support for the monitoring, management and evaluation of mangrove ecosystem in China, and it is valuable for practical application.