Determining the Drying Out of Coniferous Trees Using Airborne and Satellite Data

ARS Pub Date : 2021-06-02 DOI:10.4236/ARS.2021.102002
Sviatlana I. Guliaeva, I. Bruchkousky, L. Katkovsky
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引用次数: 0

Abstract

In recent decades, the problem of drying out of conifers has become a subject of significant importance due to the widespread mortality of trees caused by stem pest’s damage. Early detection of areas affected by insect outbreaks is of great relevance for preventing the further spread of pests. Forests of Belarus are largely affected by conifers dieback caused by the bark beetle. The aim of the study was to identify drying out conifers using a TripleSat satellite multispectral image of a woodland area in Belarus based on preliminary airborne measurements. Spectrometers operating in a spectral range of 400 - 900 nm were used in airborne measurements, resulting in distinguishing various drying out stages with an accuracy of 27% - 74% for aerial data. In this study, a supervised classification of the TripleSat image based on the method of linear discriminant analysis (LDA) was performed. The input data for LDA algorithm is a set of remote sensing vegetation indices. Results of the study demonstrate that about 90% of the test site is at the green-attack stage that is confirmed by ground surveys of this area.
利用航空和卫星数据确定针叶树的干燥
近几十年来,由于树干害虫的破坏导致树木普遍死亡,针叶树的干燥问题已成为一个非常重要的问题。及早发现受昆虫爆发影响的地区对于防止害虫的进一步传播具有重要意义。白俄罗斯的森林在很大程度上受到由树皮甲虫引起的针叶树枯死的影响。这项研究的目的是使用TripleSat卫星基于初步空气测量的白俄罗斯林地多光谱图像来识别干涸的针叶树。在航空测量中使用了在400-900 nm光谱范围内工作的光谱仪,从而区分了不同的干燥阶段,航空数据的准确率为27%-74%。在本研究中,基于线性判别分析(LDA)方法对TripleSat图像进行了监督分类。LDA算法的输入数据是一组遥感植被指数。研究结果表明,该地区的地面调查证实,约90%的试验场地处于绿色攻击阶段。
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来源期刊
ARS
ARS
CiteScore
0.10
自引率
0.00%
发文量
8
审稿时长
12 weeks
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