首页> 外文期刊>Journal of Geophysical Research. Biogeosciences >Minas de Riotinto (south Spain) forest fire: Burned area assessment and fire severity mapping using Landsat 5-TM, Envisat-MERIS, and Terra-MODIS postfire images
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Minas de Riotinto (south Spain) forest fire: Burned area assessment and fire severity mapping using Landsat 5-TM, Envisat-MERIS, and Terra-MODIS postfire images

机译:Minas de Riotinto(西班牙南部)森林火灾:使用Landsat 5-TM,Envisat-MERIS和Terra-MODIS火灾后图像进行烧毁面积评估和火灾严重程度制图

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摘要

This analysis concerns an estimation of burned area and fire severity levels in an area affected by a large wildfire that took place in the south of Spain in July 2004. Fire severity is defined in this work as the impact of fire on the vegetation. The objective was to find an efficient method for quick fire severity mapping based on remote sensing techniques that can be useful for postfire forest management. Several methods for image analysis (Linear Spectral Unmixing, Matched Filtering and Normalized Burn Ratio Index) were applied to postfire Landsat 5-TM, Envisat-MERIS, and Terra-MODIS images. Maps depicting fire severity of three levels of an acceptable reliability were obtained using a small amount of field data and following a simple method of processing. Linear spectral unmixing produced the best classifications for MERIS and MODIS images, while the matched filtering technique produced the most accurate classification for the TM image. These preliminary results show that short-term fire severity maps can be obtained by means of high- to medium-resolution postfire remote sensing data, in order to evaluate the situation after a forest fire and plan forest restoration works.
机译:该分析涉及对2004年7月在西班牙南部发生的一场大野火影响的区域的燃烧面积和火灾严重性水平的估计。在此工作中,火灾严重性定义为火灾对植被的影响。目的是找到一种基于遥感技术的快速火灾严重性制图的有效方法,该方法可用于森林火灾后的管理。几种图像分析方法(线性光谱分解,匹配滤波和归一化燃烧比率指数)已应用于大火后Landsat 5-TM,Envisat-MERIS和Terra-MODIS图像。使用少量现场数据并遵循简单的处理方法,获得了描述三个级别的可接受可靠性的火灾严重性的地图。线性光谱分解对MERIS和MODIS图像产生了最好的分类,而匹配的滤波技术对TM图像产生了最准确的分类。这些初步结果表明,可以通过高分辨率至中分辨率的火灾后遥感数据获得短期火灾严重性图,以便评估森林火灾后的状况并计划森林恢复工作。

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