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An approach of surface coal fire detection from ASTER and Landsat-8 thermal data: Jharia coal field, India

机译:一种基于ASTER和Landsat-8热数据的地面煤火探测方法:印度哈里亚煤炭田

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Radiant temperature images from thermal remote sensing sensors are used to delineate surface coal fires, by deriving a cut-off temperature to separate coal-fire from non-fire pixels. Temperature contrast of coal fire and background elements (rocks and vegetation etc.) controls this cut-off temperature. This contrast varies across the coal field, as it is influenced by variability of associated rock types, proportion of vegetation cover and intensity of coal fires etc. We have delineated coal fires from background, based on separation in data clusters in maximum v/s mean radiant temperature (13th band of ASTER and 10th band of Landsat-8) scatter-plot, derived using randomly distributed homogeneous pixel-blocks (9 x 9 pixels for ASTER and 27 x 27 pixels for Landsat-8), covering the entire coal bearing geological formation. It is seen that, for both the datasets, overall temperature variability of background and fires can be addressed using this regional cut-off. However, the summer time ASTER data could not delineate fire pixels for one specific mine (Bhulanbararee) as opposed to the winter time Landsat-8 data. The contrast of radiant temperature of fire and background terrain elements, specific to this mine, is different from the regional contrast of fire and background, during summer. This is due to the higher solar heating of background rocky outcrops, thus, reducing their temperature contrast with fire. The specific cut-off temperature determined for this mine, to extract this fire, differs from the regional cut-off. This is derived by reducing the pixel-block size of the temperature data. It is seen that, summer-time ASTER image is useful for fire detection but required additional processing to determine a local threshold, along with the regional threshold to capture all the fires. However, the winter Landsat-8 data was better for fire detection with a regional threshold. (C) 2015 Elsevier B.V. All rights reserved.
机译:来自热遥感传感器的辐射温度图像通过得出临界温度来将煤火与非火像素区分开来描绘煤表面火。煤火和背景元素(岩石和植被等)的温度对比控制着该临界温度。这种对比在整个煤田中都不同,因为它受相关岩石类型,植被覆盖比例和煤火强度等的变化的影响。基于最大v / s均值在数据集群中的分离,我们已经从背景中描绘了煤火。辐射温度(ASTER的第13波段和Landsat-8的第10波段)散点图,使用随机分布的同质像素块(ASTER的9 x 9像素和Landsat-8的27 x 27像素)得出,覆盖了整个煤层地质构造。可以看出,对于这两个数据集,背景和火灾的总体温度变化都可以使用该区域性临界值来解决。但是,与冬季的Landsat-8数据相比,夏季的ASTER数据无法描绘出一个特定矿井(Bhulanbararee)的火象素。该矿山特定的火与背景地形元素的辐射温度对比与夏季的火与背景区域对比不同。这是由于背景岩石露头的日光加热较高,因此降低了它们与火的温度对比。为开采此火而确定的该矿的特定边界温度与区域边界不同。这是通过减小温度数据的像素块大小得出的。可以看出,夏季的ASTER图像对于火灾探测很有用,但需要额外的处理来确定局部阈值,以及捕获所有火灾的区域阈值。但是,冬季Landsat-8数据对于具有区域阈值的火灾探测效果更好。 (C)2015 Elsevier B.V.保留所有权利。

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