为探索局地尺度红树林幼林空间分布信息准确提取的适用方法,以广西钦州茅尾海一个天然红树林幼林典型分布区作研究区,选择WorldView-3为数据源,采用非监督分类、面向对象最邻近分类的方法进行实验。结果表明:非监督分类和面向对象分类的总体精度分别为95.8%和96.2%,Kappa系数分别为0.906 8和0.913 7,说明2种较为简单的图像分类方法都可准确地提取红树林幼林信息;但前者得到的仅仅是幼树个体树冠覆盖的信息,不包含幼树间的滩涂,“椒盐”效应明显,后者得到的信息不仅包含幼树个体,也包含幼树间的滩涂,反映了红树林幼树的分布范围,因此,红树林幼林空间分布信息提取以面向对象分析方法为宜。红树林幼林树冠小,其空间分布信息提取需采用高空间分辨率遥感数据,一般宜优于1.0m,最好达到0.3m,并且宜选用处于低潮位、红树林裸露的遥感数据。
To explore an efficient method for mapping young mangrove forest exactly in local level,Unsupervised classification and object-oriented nearest neighbor classification were test on WorldView-3 remote sensing image in Maoweihai bay in Guangxi,south China,where a plenty of young mangrove forests grow.The results indicated that the overall accuracies of unsupervised and object-oriented classification were 95.8% and 96.2% respectively,and the kappa indexes were 0.906 8 and 0.913 7 respectively,that meant two simple methods could be used to accurately map the distribution of young mangrove forest.But the former output represented only the crown coverage of young trees and did not include the bare bead between the trees,and there was a significant salt and pepper effect on the map,and the latter output was the extent of young tree distribution for it included not only the extent of young trees crown but also the beach near by the trees,therefore,the object-oriented classification was more suitable for extracting the extend information of young mangrove forest than pixel-based method.Young mangrove forests have small crowns,high resolution remote sensing image must be used to map their extent,1.0 m or small resolution of images were recommended,0.3 m resolution of image was preferable.On the other hand,the images acquired in low tide period were needed.
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