Yu Chao, Chen Liang-fu, Li Shen-shen, Tao Jin-hua, Su Lin
Guang Pu Xue Yu Guang Pu Fen Xi. 2015 Mar;35(3):739-45.
Biomass burning makes up an important part of both trace gases and particulate matter emissions, which can efficiently degrade air quality and reduce visibility, destabilize the global climate system at regional to global scales. Burned area is one of the primary parameters necessary to estimate emissions, and considered to be the largest source of error in the emission inventory. Satellite-based fire observations can offer a reliable source of fire occurrence data on regional and global scales, a variety of sensors have been used to detect and map fires in two general approaches: burn scar mapping and active fire detection. However, both of the two approaches have limitations. In this article, we explore the relationship between hotspot data and burned area for the Southeastern United States, where a significant amount of biomass burnings from both prescribed and wild fire took place. MODIS (Moderate resolution imaging spectrometer) data, which has high temporal-resolution, can be used to monitor ground biomass. burning in time and provided hot spot data in this study. However, pixel size of MODIS hot spot can't stand for the real ground burned area. Through analysis of the variation of vegetation band reflectance between pre- and post-burn, we extracted the burned area from Landsat-5 TM (Thematic Mapper) images by using the differential normalized burn ratio (dNBR) which is based on TM band4 (0.84 μm) and TM band 7(2.22 μm) data. We combined MODIS fire hot spot data and Landsat-5 TM burned scars data to build the burned area estimation model, results showed that the linear correlation coefficient is 0.63 and the relationships vary as a function of vegetation cover. Based on the National Land Cover Database (NLCD), we built burned area estimation model over different vegetation cover, and got effective burned area per fire pixel, values for forest, grassland, shrub, cropland and wetland are 0.69, 1.27, 0.86, 0.72 and 0.94 km2 respectively. We validated the burned area estimates by using the ground survey data from National interagency Fire Center (NIFC), our results are more close to the ground survey data than burned area from Global Fire Emissions Database (GFED) and MODIS burned area product (MCD45), which omitted many small prescribed fires. We concluded that our model can provide more accurate burned area parameters for developing fire emission inventory, and be better for estimating emissions from biomass burning.
生物质燃烧是微量气体和颗粒物排放的重要组成部分,它会有效降低空气质量、减少能见度,在区域到全球尺度上破坏全球气候系统。燃烧面积是估算排放量所需的主要参数之一,被认为是排放清单中最大的误差来源。基于卫星的火灾观测能够在区域和全球尺度上提供可靠的火灾发生数据,多种传感器已被用于通过两种常规方法检测和绘制火灾:燃烧疤痕测绘和明火探测。然而,这两种方法都存在局限性。在本文中,我们探究了美国东南部热点数据与燃烧面积之间的关系,该地区发生了大量来自规定燃烧和野火的生物质燃烧。具有高时间分辨率的中分辨率成像光谱仪(MODIS)数据可用于及时监测地面生物质燃烧,并在本研究中提供热点数据。然而,MODIS热点的像素大小不能代表实际的地面燃烧面积。通过分析燃烧前后植被波段反射率的变化,我们利用基于陆地卫星5号专题制图仪(TM)的波段4(0.84微米)和波段7(2.22微米)数据的差分归一化燃烧比(dNBR)从陆地卫星5号TM图像中提取了燃烧面积。我们将MODIS火灾热点数据与陆地卫星5号TM燃烧疤痕数据相结合,构建了燃烧面积估算模型,结果表明线性相关系数为0.63,且这种关系随植被覆盖度而变化。基于国家土地覆盖数据库(NLCD),我们构建了不同植被覆盖度下的燃烧面积估算模型,并得出每个火灾像素的有效燃烧面积,森林、草地、灌木、农田和湿地的数值分别为0.69、1.27、0.86、0.72和0.94平方千米。我们利用来自国家跨部门火灾中心(NIFC)的地面调查数据对燃烧面积估算结果进行了验证,我们的结果比全球火灾排放数据库(GFED)和MODIS燃烧面积产品(MCD45)的燃烧面积更接近地面调查数据,后两者遗漏了许多小规模的规定燃烧。我们得出结论,我们的模型能够为编制火灾排放清单提供更准确的燃烧面积参数,并且更有利于估算生物质燃烧的排放量。