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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Investigating the Capability of Few Strategically Placed Worldview-2 Multispectral Bands to Discriminate Forest Species in KwaZulu-Natal, South Africa
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Investigating the Capability of Few Strategically Placed Worldview-2 Multispectral Bands to Discriminate Forest Species in KwaZulu-Natal, South Africa

机译:调查在南非夸祖鲁-纳塔尔省很少有策略性放置Worldview-2多光谱带以区分森林物种的能力

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摘要

WorldView-2 multispectral wavebands (8 wavebands; 427–908 nm spectral range; 2 m spatial resolution) were utilized to classify six commercial forest species (Eucalyptus grandis, Eucalyptus nitens, Eucalyptus smithii, Pinus patula, Pinus elliotii and Acacia mearnsii) in South Africa using the partial least squares discriminant analysis (PLS-DA) technique. Results indicate that the WorldView-2 imagery produced an overall accuracy of 85.42% and a kappa statistic value of 0.83, with individual forest species accuracies ranging between 63% and 100%. The variable importance in the projection (VIP) method was then used to identify the most important wavebands that were most effective in discriminating the forest species. Four VIP bands were ranked with thresholds greater than one and produced an overall accuracy of 84.38% and kappa value of 0.81, with individual forest species accuracies between 69% and 100%. More specifically, the VIP bands that were found to be important in the classification were the coastal blue (427 nm), blue (478 nm), green (546 nm) and red (659 nm) and confirmed the relative importance of the visible region of the electromagnetic spectrum in discriminating forest species. Overall, results indicate that multispectral information characterized by greater spatial resolution can successfully discriminate between and within forest species, thus providing an accurate framework for commercial forest species mapping.
机译:WorldView-2多光谱波段(8个波段; 427-908 nm光谱范围; 2 m空间分辨率)被用来对南部的六种商品林物种(桉木,桉树,史密斯桉,樟子松,pat松和金合欢)进行分类。非洲使用偏最小二乘判别分析(PLS-DA)技术。结果表明,WorldView-2影像的总体准确度为85.42%,kappa统计值为0.83,单个森林物种的准确度在63%至100%之间。然后使用投影中的可变重要性(VIP)方法来识别对森林物种最有效的最重要波段。对四个VIP频段进行了排名,其阈值大于1,其总体准确度为84.38%,kappa值为0.81,单个森林物种的准确度在69%至100%之间。更具体地说,发现在分类中很重要的VIP波段是沿海蓝色(427 nm),蓝色(478 nm),绿色(546 nm)和红色(659 nm),并确认了可见区域的相对重要性电磁光谱在区分森林物种中的作用。总体而言,结果表明,以更高的空间分辨率为特征的多光谱信息可以成功地区分森林物种及其内部,从而为商品林物种制图提供了准确的框架。

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