Sea surface correction of high spatial resolution Ikonos images to improve bottom mapping in near-shore environments

被引:181
作者
Hochberg, EJ [1 ]
Andréfouët, S
Tyler, MR
机构
[1] Univ Hawaii, Hawaii Inst Marine Biol, Sch Ocean & Earth Sci & Technol, Kaneohe, HI 96744 USA
[2] Univ S Florida, Coll Marine Sci, Inst Marine Remote Sensing, St Petersburg, FL 33701 USA
[3] Western Washington Univ, Huxley Coll Environm Studies, Dept Environm Sci, Bellingham, WA 98225 USA
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2003年 / 41卷 / 07期
基金
美国国家航空航天局; 美国海洋和大气管理局;
关键词
classification; coral reef; glint; Lee Stocking Island; radiative transfer; remote sensing;
D O I
10.1109/TGRS.2003.815408
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
A significant number of high spatial resolution (4 in) Ikonos images acquired over shallow coastal environments present quasi-stochastic sea surface effects that seriously compromise reconnaissance of bottom features. This problem is common in wide field-of-view images where there is limited control on acquisition conditions other than cloud cover. To eliminate most of these wave and glint patterns, we use the near-infrared band, which exhibits maximum absorption and minimal water leaving radiance over clear waters, to characterize the spatial distribution of relative glint intensity, which is then scaled by absolute glint intensities in each of the visible bands. The result is subtracted from the visible bands, thus filtering out glint effects. Corrected visible bands clearly reveal seabed structural features obscured in the original data. Before- and after-correction classifications of an Ikonos image of Lee Stocking Island (Bahamas) reveal an improvement of user's accuracies for critical benthic habitat classes such as coral-dominated habitat (46.8% versus 60.5%) or dense seagrass beds (31.7% versus 52.1%). This technique offers potential to use previously discarded sections of high spatial resolution airborne or satellite images of optically shallow water for mapping substrate features.
引用
收藏
页码:1724 / 1729
页数:6
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