Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite
文献类型：期刊论文
| 作者 | Yu Chao1; Chen Liang-fu1; Li Shen-shen1; Tao Jin-hua1; Su Lin1 |
| 刊名 | SPECTROSCOPY AND SPECTRAL ANALYSIS
 |
| 出版日期 | 2015 |
| 卷号 | 35期号:3页码:1981-2006 |
| 关键词 | Biomass burning MODIS Landsat Fire Hot Spot Burned Area the differential normalized burn ratio (dNBR) |
| 通讯作者 | Chen, LF (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China. |
| 英文摘要 | 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 bum ratio (dNBR) which is based on TM band4 (0. 84 mu m) and TM band 7(2. 22 mu m) 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 km(2) 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. |
| 研究领域[WOS] | Spectroscopy |
| 收录类别 | SCI ; EI |
| 语种 | 中文 |
| WOS记录号 | WOS:000351025600034 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38262]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.[Yu Chao 2.Chen Liang-fu 3.Li Shen-shen 4.Tao Jin-hua 5.Su Lin] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 6.[Yu Chao] Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu Chao,Chen Liang-fu,Li Shen-shen,et al. Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS,2015,35(3):1981-2006. |
| APA | Yu Chao,Chen Liang-fu,Li Shen-shen,Tao Jin-hua,&Su Lin.(2015).Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite.SPECTROSCOPY AND SPECTRAL ANALYSIS,35(3),1981-2006. |
| MLA | Yu Chao,et al."Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite".SPECTROSCOPY AND SPECTRAL ANALYSIS 35.3(2015):1981-2006. |
入库方式： OAI收割
来源：遥感与数字地球研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。