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Characterizing the Spatial Distribution of Oak Wilt Disease Using Remote Sensing Data

机译：使用遥感数据表征橡木枯萎病的空间分布

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摘要

This study categorized the damaged trees by Supervised Classification using time-series-aerial photographs of Bukhan, Cheonggae and Suri mountains because oak wilt disease seemed to be concentrated in the metropolitan regions. In order to analyze thespatial characteristics of the damaged areas, the geographical characteristics such as elevation and slope were statistically analyzed to confirm their strong correlation. Based on the results from the statistical analysis of Moran's I, we have retrievedthe following: (i) the value of Moran's I in Bukhan mountain is estimated to be 0.25, 0.32, and 0.24 in 2009, 2010 and 2012, respectively, (ii) the value of Moran's I in Cheonggye mountain estimated to be 0.26, 0.32 and 0.22 in 2010, 2012 and 2014, respectively and (iii) the value of Moran's I in Suri mountain estimated to be 0.42 and 0.42 in 2012 and 2014. respectively. These numbers suggest that the damaged trees are distributed in clusters. In addition, we conducted hotspot analysis to identify howthe damaged tree clusters shift over time and we were able to verify that hotspots move in time series. According to our research outcome from the analysis of the entire hotspot areas (z-score>1.65), there were 80 percent probability of oak wilt diseaseoccurring in the broadleaf or mixed-stand forests with elevation of 200~400 m and slope of 20-40 degrees. This result indicates that oak wilt disease hotspots can occur or shift into areas with the above geographical features or forest conditions. Therefore, this research outcome can be used as a basic resource when predicting the oak wilt disease spread-patterns, and it can also prevent disease and insect pest related harms to assist the policy makers to better implement the necessary solutions.
机译：由于橡树萎蔫病似乎集中在大都市地区，因此本研究利用布汗山、清盖山和苏里山的时间序列航空照片，通过监督分类对受损树木进行分类。为了分析受损区域的空间特征，对海拔和坡度等地理特征进行了统计分析，以确认它们之间的强相关性。根据莫兰I的统计分析结果，我们得出以下结论：（I）2009年、2010年和2012年，布汗山的莫兰I值分别为0.25、0.32和0.24；（ii）2010年、2012年和2014年，清溪山的莫兰I值分别为0.26、0.32和0.22，（iii）2012年和2014年，苏里山莫兰I的价值分别为0.42和0.42。分别地这些数字表明受损的树木是成簇分布的。此外，我们还进行了热点分析，以确定受损的树簇是如何随时间推移而移动的，我们能够验证热点是否在时间序列中移动。根据我们对整个热点地区的分析结果（z评分>1.65），在海拔200~400m、坡度20~40度的阔叶林或混交林中发生橡树枯萎病的概率为80%。这一结果表明，橡树萎蔫病热点可能发生或转移到具有上述地理特征或森林条件的地区。因此，本研究成果可以作为预测橡树萎蔫病传播模式的基础资源，也可以预防与病虫害相关的危害，帮助决策者更好地实施必要的解决方案。

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