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Verifying Haze Dispersion from Peatland Fires using Classified Landsat 8

机译:使用分类的Landsat 8验证泥炭地火灾的霾扩散

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Haze dispersion from peatland fire that influence human health can be recognized by analyzing haze trajectory pattern. Previous studies have successfully analyzed haze dispersion as the result of the simulation using HYSPLIT. However the haze dispersion have not verified and compared with the real situation. This study aims to verify haze dispersion from peatland fires in Riau Province using Landsat 8. The Landsat 8 was classified using the C5.0 decision tree algorithm. There were eight classes used in the classification which are cloud, smoke/haze, water body, shadow, built up area, burning area, burned area, and vegetation. The best classification model has the accuracy of 97.58% and kappa coefficient of 0.97. This study has successfully verified 58 haze locations in the study area. As many 98.28% of those locations were found on smoke/haze and cloud. In addition, about 41.38% of 58 haze points are located at height and pressure that are harmful for human health.
机译:通过分析霾的轨迹模式,可以认识到泥炭地火灾引起的霾扩散对人类健康的影响。先前的研究已经成功地使用HYSPLIT分析了雾度散布。然而,雾度的分散还没有经过验证并与实际情况进行了比较。这项研究的目的是使用Landsat 8验证廖内省泥炭地大火的霾散。Landsat 8使用C5.0决策树算法进行分类。在分类中使用了八类,分别是云,烟/霾,水体,阴影,建筑面积,燃烧面积,燃烧面积和植被。最佳分类模型的准确度为97.58%,kappa系数为0.97。这项研究已成功验证了研究区域中的58个雾霾位置。在这些地点中,有多达98.28%的地点是烟雾/烟雾和云。此外,在58个霾点中,约有41.38%位于对人体健康有害的高度和压力下。

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