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Verifying Haze Dispersion from Peatland Fires using Classified Landsat 8

机译:使用分类的Landsat 8从泥炭地火灾中验证Haze Dispersion

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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:通过分析雾霾轨迹模式,可以通过分析壁炉轨道的泥炭地火灾的阴霾分散。以前的研究成功地分析了使用HYSPLIT的模拟结果的雾度分散。然而,与真实情况没有验证雾度分散。本研究旨在验证利用Landsat 8的泥炭地火灾的雾地散道探讨。使用C5.0决策树算法分类Landsat 8。分类中有八种课程,云,烟雾/雾度,水体,阴影,建筑面积,燃烧区域,烧毁区域和植被。最佳分类模型的准确性为97.58%,kappa系数为0.97。本研究成功验证了研究区的58个雾度位置。在烟雾/阴霾和云中发现了多个地点的98.28%。此外,约41.38%的58个雾度点位于对人类健康有害的高度和压力。

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