Assessment of defoliation during the Dendrolimus tabulaeformis Tsai et Liu disaster outbreak using UAV-based hyperspectral images
Assessment of defoliation during the Dendrolimus tabulaeformis Tsai et Liu disaster outbreak using UAV-based hyperspectral images
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使用基于无人机的高光谱图像评估油松毛虫 Tsai 和 Liu 灾害爆发期间的落叶情况
DOI：
10.1016/j.rse.2018.08.024
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发表时间：
2018-11
影响因子：
13.5
通讯作者：
Feng Haikuan
中科院分区：
文献类型：
--
作者：
Zhang Ning;Zhang Xiaoli;Yang Guijun;Zhu Chenghao;Huo Langning;Feng Haikuan
由于昆虫引起的森林干扰的频率和强度都在增加，因此需要有有效的方法来精确监测灾害的程度并绘制灾情图。基于无人机的高光谱成像技术是一种有效的森林健康状况调查与监测技术。在这篇文章中，我们提出了一个新的框架，利用基于无人机的高光谱图像来识别油树limus tabulaeformis造成的损伤程度。中国辽宁省建平县油鸡属（tabulaeformis）。首先，通过对比主成分分析（PCA）、逐次投影算法（SPA）和类间不稳定指数（ISIC）三种波段选择算法，实现了高光谱图像的数据约简。在此基础上，提出了具有最佳波段选择效率和交叉验证精度的ISIC-SPA联合算法。ISIC-SPA从125个原始波段中只选择了3个敏感波段，均方根误差为0.1535。然后，根据三个敏感波段的反射率和相应的落叶率分析，构建了分段指数PI， B(710 + 738 - 522)，并找到PI的阈值来划分落叶等级。最后，建立分段偏最小二乘回归模型，利用最优波段定量估计落叶量，识别和划分对单株树的损害程度。对比亚迪造成损害的评估准确性。tabulaeformisat使用ISIC-SPA-P-PLSR框架的树级达到95.23%。
The increased frequency and intensity of insect-induced forest disturbances necessitates effective methods to precisely monitor and map the degree of disaster. Unmanned aerial vehicle (UAV)-based hyperspectral imaging is an effective technology for surveying and monitoring forest health. In this article, a novel framework that utilizes a UAV-based hyperspectral image is proposed to identify the degree of damage caused byDendrolimus tabulaeformis Tsai et Liu(D.tabulaeformis) in Jianping county of Liaoning province, China. First, data reduction of the hyperspectral image is achieved by comparing three waveband selection algorithms: principal components analysis (PCA), the successive projection algorithm (SPA), and the instability index between classes (ISIC). On this basis, a joint algorithm, ISIC-SPA, which demonstrates the best waveband selection efficiency and good cross-validation accuracy, is proposed. ISIC-SPA is used to select only three sensitive wavebands from 125 original wavebands with a root mean square error of 0.1535. Then, according to analysis of the three sensitive wavebands' reflectance and the corresponding defoliation rate, the piecewise index (PI, B(710 + 738 - 522)) was constructed and the threshold of PI was found to divide the defoliation level. Finally, a piecewise partial least-squares regression model was established to quantitatively estimate the defoliation using the optimal wavebands to identify and demarcate the damage level to individual trees. The assessment accuracy of damage caused byD.tabulaeformisat the tree level reached 95.23% using the ISIC-SPA-P-PLSR framework.
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影响因子：
3.7
作者：
Fan J;Xie Y;Xue J;Zhang Y;Yang Q
通讯作者：
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影响因子：
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作者：
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通讯作者：
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作者：
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通讯作者：
Mian, Ajmal