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摘要： 选取北部湾的东部地区(广东省和广西壮族自治区交界处)为研究区，探索利用资源三号卫星影像，建立大范围红树林遥感信息提取和精细分类模式。首先根据地物波谱特征提取水陆边线，并建立缓冲区生成红树林生长适宜区；再通过基于面向对象的阈值分类方法提取红树林植被信息；最后采用基于像元的最近邻、贝叶斯和随机森林方法对红树林进行树种级分类。结果表明：采用结合阈值法的面向对象遥感分类可以对整景资源三号卫星影像准确提取水陆边线并有效提取红树林分布区，采用基于像元的随机森林法对红树林树种级分类可以得到较好的分类效果(总体分类精度82.84%)，优于最近邻法和贝叶斯法。基于混合方法的红树林提取与树种分类模式适用于大范围的红树林分类与制图，同时也证实了资源三号卫星数据应用于海岸带红树林研究的有效性。 关键词： 资源三号;  红树林提取;  遥感分类;  北部湾     Abstract: A hybrid mangrove forest extraction and species classification model for large coastal region was proposed using a ZY-3 (ZiYuan-3) image in the eastern part of Beibu Gulf (located at the junction of Guangdong and Guangxi).Firstly，the coastline was extracted according to the spectral features of ZY-3 image.Secondly，the buffer zone along with the coastline was generated as the suitable area of mangrove distribution.Mangrove forests and non-mangrove areas were then further classified using threshold method based on object-based image classification in these areas.Finally，Mangrove forests were classified at specie level using three pixel-based supervised classification methods，k-Nearest Neighbor，Bayes，and Random Forest.The classification results and accuracies were also compared and discussed.The results indicated that object-based threshold method can extract the coastline accurately and map the mangrove forests effectively.The pixel-based random forest classifier can obtain satisfactory results (the overall accuracy of 82.24%) of mangrove species classification than the other classifiers.In summary，the hybrid mode proposed in this paper is suitable for mangrove forests mapping and species classification in a large region.It is also validated the feasibility application of ZY-3 image in coastal mangrove research.

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