高光谱航空数据在印尼热带泥炭沼泽森林树种识别中的应用

2022 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) Pub Date : 2022-12-21 DOI:10.1109/AGERS56232.2022.10093651

Laju Gandharum, Heri Sadmono, D. B. Sencaki, A. Eugenie, Hari Prayogi, I. F. Cahyaningtiyas

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引用次数: 0

摘要

像HyMAP这样的高光谱遥感成像提供了极其精确的光谱数据。因此，利用光谱角成像仪(SAM)技术，HyMap是印度尼西亚热带泥炭沼泽森林等偏远地区树种鉴别的理想选择。结果表明，邦卡(Bangka)、Gercinia和巴劳(Balau)三种树种的定位优势明显。在0.2弧度阈值下，这3种分别占研究区面积的56.69%、29.18%和4.44%。通过提高阈值(从0.2到0.3弧度)，未分类像素的百分比降低了3.72%。

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Application of Hyperspectral Airborne Data for Discriminating Tree Species in Tropical Peat Swamp Forest, Indonesia

Hyperspectral remote sensing imaging, like HyMAP, offers extremely precise spectrum data. Therefore, by using a spectral angle mapper (SAM) technique, HyMap was ideal for differentiating tree species in remote places like tropical peat swamp forests in Indonesia. The results showed tree species of Bangka, Gercinia, and Balau were mapped more dominantly than others. At a threshold of 0.2 radians, these three species, in that order, dominated 56.69%, 29.18%, and 4.44% of the study area. The percentage of unclassified pixels was decreased by 3.72% by raising the threshold (from 0.2 to 0.3 radians).

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2022 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)

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