利用高光谱影像对澳大利亚昆士兰州剩余树种和再生阶段的鉴别

A. Apan, S. Phinn, T. Maraseni
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引用次数: 7

摘要

本研究评估了高光谱图像在澳大利亚昆士兰州东南部残木树种和林分更新阶段的鉴别中的应用。利用HyMap™机载系统获取的3种木本植被(即populnea Eucalyptus、Acacia pendula和Eucalyptus orgadophila)的反射率数据,采用偏最小二乘(PLS)回归进行分析。同时,对三组代表林分更新状况的金银花树种进行了评价。PLS对这类树种的预测准确率在83 ~ 88%之间。最显著的光谱带包括可见光区(峰值在558nm和689nm)、近红外区(峰值在987nm)和短波红外区(峰值在1788nm)。高光谱数据能够区分出金银花的老林和幼林,准确率为72%。这些结果证实了高光谱数据在植被制图和林分特征方面的潜在效用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discrimination of remnant tree species and regeneration stages in Queensland, Australia using hyperspectral imagery
This study assessed the utility of hyperspectral imagery in discriminating remnant tree species and stand regeneration stages in Southeast Queensland, Australia. Reflectance data of three species of woody vegetation (i.e. Eucalyptus populnea, Acacia pendula and Eucalyptus orgadophila), acquired using a HyMap™ airborne system, were analysed using partial least squares (PLS) regression. Three groups of E. orgadophila species, representing stand regeneration status, were also evaluated. For discriminating such tree species, the PLS results showed high prediction accuracy ranging from 83–88%. The most significant spectral bands span from the visible region (peak at 558nm and 689nm), near-infrared region (peak at 987nm), and shortwave infrared region (peak at 1788nm). Hyperspectral data was able to discriminate the old stand of E. orgadophila from the young stand, with a moderate accuracy of 72%. Results such as these confirmed the potential utility of hyperspectral data in vegetation mapping and stand characterisation.
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