基于ALOS数据的盐城海岸带湿地提取

Yongling Weng, X. Fan, Jinmei Tao
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引用次数: 0

摘要

江苏沿海地区湿地资源丰富,拥有全球相关的湿地储量。然而,随着人类活动的日益频繁,湿地面积不断缩小。本文选择5张ALOS AVNIR-2影像以及1张低潮时额外获取的TM影像,对盐城滨海湿地进行研究。在实地工作中,调查了各子类和植被覆盖度的特征,然后采用二层决策树方法区分不同的湿地类别。最后将总面积划分为8个主要湿地类,总体精度为97.16%,Kappa系数为0.96。在28个现场记录的样本中,只有2个采样点的分类有偏差,结果令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wetland extraction of Yancheng coastal area based on ALOS data
Jiangsu coastal area is abundant in wetland resources and possesses wetland reserve of global relevancy. However, the wetland area has been shrinking with more and more human activities. In this paper, 5 ALOS AVNIR-2 images as well as an additional TM image acquired at low tide level were selected to carry out a research of Yancheng coastal wetland. Characteristics of subcategories and vegetation coverage were surveyed during filed work before a 2-tier decision tree method was adopted to distinguish different wetland categories. At last, the total area was classified as 8 major wetland categories with an overall accuracy of 97.16% as well as Kappa coefficient of 0.96. Only 2 sampling sites biased in the classification when 28 field recorded samples were compared and the result was satisfying.
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