浏览全部资源
扫码关注微信
纸质出版日期： 2020-05-07 ，
扫 描 看 全 文
郑伟,陈洁,闫华,刘诚,唐世浩.2020.FY-3D/MERSI-II全球火点监测产品及其应用.遥感学报,24(5): 521-530
Zheng W, Chen J, Yan H, Liu C and Tang S H. 2020. Global fire monitoring products of FY-3D/MERSI-II and their applications. Journal of Remote Sensing(Chinese). 24(5): 521-530
FY-3D/MERSI-II全球火点监测产品主要包括全球范围内的火点位置、亚像元火点面积和火点强度等信息，可用于实时监测全球范围的森林草原火灾、秸秆焚烧等生物质燃烧状况。火点判识算法主要根据中红外通道对高温热源的敏感特性，即含有火点的中红外通道像元辐亮度和亮温较远红外通道的辐亮度和亮温偏高，同时较周边非火点的中红外像元偏高，建立合适的阈值可探测含有火点的像元。亚像元火点面积估算主要使用中红外单通道估算，根据亚像元火点面积估算结果对火点强度进行分级，不同的级别表示不同程度的火点辐射强度。基于全球火点自动判识结果，每日生成0.01°分辨率的卫星遥感日全球火点产品，每月生产0.25°×0.25°格点的全球月火点密度图。在利用FY-3D/MERSI-II火点产品开展的全球火点监测应用中，对多起全球重大野火事件进行了监测，为防灾减灾、全球气候变化研究、生态环境保护等方面提供卫星遥感信息支持。
Fengyun/Medium Resolution Spectral Imager-II (FY-3D/MERSI-II) global fire products can be used in real-time monitoring of forest and grassland fires
straw burning
and other biomass burning worldwide. This paper discusses FY-3D/MERSI-II global fire products
including the methods
product contents
and applications.
Fire spot discerning considers several conditions
such as cloud contamination
cloud edge
and thin cloud influences. Subpixel size evaluation uses a single channel with fire temperature set to 750 K. Fire intensity level is established on the basis of Fire Radiative Power (FRP) and is calculated using sub-pixel size and fire temperature. Daily global fire products with 0.01° spatial resolution are generated
and global monthly fire spot density maps with 0.25°×0.25° grid points are produced monthly on the basis of the results of automatic global fire spot discerning.
We selected the results in several typical areas
including Northeast China
Russian Far East
South America
and South-central Africa
from May to June 2018
and compared them using interactive fire spot discerning as the truth to verify the accuracy of automatic fire spot discerning in Fengyun/Medium Resolution Spectral Imager-II (FY-3D/MERSI-II) global fire monitoring. The statistical analysis results show that the accuracy of the automatic fire monitoring algorithm reaches more than 95. The daily FY-3D/MERSI-II global fire products include fire location
subpixel size (in hectare
temperature
fire intensity level
and FRP. Two application examples are introduced
where the first example is for monitoring the huge wildfire that occurred in California
US in 2018
and the second example is for analyzing the temporal and spatial changing features of wildfire around the Arctic Pole circle in the summer of 2018.
The FY-3 global fire spot discerning algorithm considers various weather and underlying conditions
making it suitable for fire monitoring in different regions of the world. The results show that the proposed algorithm has good accuracy. The rich detection information and global observation ability of FY-3 meteorological satellite reach the international advanced level of forest and grassland fire monitoring. FY-3 global fire product can be used for disaster prevention and mitigation
climate change
and ecological environment protection worldwide. In future studies
we will develop methods
such as burned area assessment and estimation of biomass carbon emissions
smoke impact prediction
and forest and grassland fire risk warning. FY-3 meteorological satellite will play a huge role in global wildfire monitoring and early warning and prediction services.
遥感风云三号火点监测中红外全球范围日和月产品
remote sensingFY-3fire monitoringmiddle infrared channelglobaldaily and monthly products
Chen J, Zheng W, Gao H, Shao J L and Liu C. 2015. Estimation method of straw burned area based on multi-source satellite remote sensing. Transactions of the Chinese Society of Agricultural Engineering, 31(3): 207-214
陈洁, 郑伟, 高浩, 邵佳丽, 刘诚. 2015. 多源卫星遥感农作物秸秆焚烧过火区面积估算方法. 农业工程学报, 31(3): 207-214 [DOI: 10.3969/j.issn.1002-6819.2015.03.027http://dx.doi.org/10.3969/j.issn.1002-6819.2015.03.027]
Dozier J. 1981. A method for satellite identification of surface temperature fields of subpixel resolution. Remote Sensing of Environment, 11: 221-229 [DOI: 10.1016/0034-4257(81) 90021-3http://dx.doi.org/10.1016/0034-4257(81) 90021-3]
Giglio L, Descloitres J, Justice C O and Kaufman Y J. 2003. An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment, 87(2/3): 273-282 [DOI: 10.1016/S0034-4257(03)00184-6http://dx.doi.org/10.1016/S0034-4257(03)00184-6]
He Q J and Liu C. 2008. Improved algorithm of self-adaptive fire detection for MODIS data. Journal of Remote Sensing, 12(3): 448-453
何全军, 刘诚. 2008. MODIS数据自适应火点检测的改进算法. 遥感学报, 12(3): 448-453 [DOI: 10.11834/ jrs.20080361http://dx.doi.org/10.11834/ jrs.20080361]
Kaufman Y J, Kleidman R G and King M D. 1998. SCAR‐B fires in the tropics: properties and remote sensing from EOS-MODIS. Journal of Geophysical Research: Atmospheres, 103(D24): 31955-31968 [DOI: 10.1029/98jd02460http://dx.doi.org/10.1029/98jd02460]
Liu C, Li Y J, Yan H, Zhang P, Zhao H M and Xu Z. 2003. The improvement of fire monitoring method for meteorological satellite. Meteorological Monthly, 29(S1): 35-40
刘诚, 李亚军, 阎华, 张鹏, 赵洪淼, 徐喆. 2003. 气象卫星火情监测判识方法的改进. 气象, 29(S1): 35-40 [DOI: 10.7519/j.issn.1000-0526.2003.s1.008http://dx.doi.org/10.7519/j.issn.1000-0526.2003.s1.008]
Liu C, Li Y J, Zhao C H, Yan H and Zhao H M. 2004. The method of evaluating sub-pixel size and temperature of fire spot in AVHRR data. Journal of Applied Meteorological Science, 15(3): 273-280
刘诚, 李亚君, 赵长海, 阎华, 赵洪淼. 2004. 气象卫星亚像元火点面积和亮温估算方法. 应用气象学报, 15(3): 273-280 [DOI: 10.3969/j.issn.1001-7313.2004.03.003http://dx.doi.org/10.3969/j.issn.1001-7313.2004.03.003]
Liu Y J and Yang Z D. 2001. The Principle and arithmetic of MODIS. Beijing: Science Press: 273
刘玉洁, 杨忠东,. 2001. MODIS遥感信息处理原理与算法. 北京: 科学出版社
Matson M and Schneider S R. 1984. Fire Detection Using the NOAA-Series Satellite. NOAA Technical Report NESDIS 7. Washington: National Oceanic and Atmospheric Administration, National Environmental Satellite Data and Information Service
Rong Z G, Liu C, Sun H, Ma L J, Lu N M, Liu J J, Zhang Y X, Zhong S Q, Zhang Y, Zhang P, Zhang J S, Li Y J, Zhang X Q, Ma R S and Wang J H. 2007. Sensitivity experiment for fire detecting using satellites' data and new detection channel selection for fire remote sensing. Advances in Earth Science, 22(8): 866-871
戎志国, 刘诚, 孙涵, 马轮基, 卢乃锰, 刘京晶, 张玉香, 钟仕全, 张艳, 张鹏, 张甲珅, 李亚君, 张行清, 马瑞升, 王君华. 2007. 卫星火情探测灵敏度试验与火情遥感新探测通道选择. 地球科学进展, 22(8): 866-871 [DOI: 10.3321/j.issn: 1001-8166.2007.08.013http://dx.doi.org/10.3321/j.issn: 1001-8166.2007.08.013]
Tan M Y, Chen Z X, Cao X, Chen J, Yang W and Gu Z H. 2007. Burn scar mapping in steppe using MODIS data. Journal of Remote Sensing, 11(3): 1993-2002
谭明艳, 陈仲新, 曹鑫, 陈晋, 杨伟, 辜智慧. 2007. 利用MODIS识别草原火灾迹地方法的研究. 遥感学报, 11(3): 1993-2002 [DOI: 10.11834/jrs. 20070347http://dx.doi.org/10.11834/jrs. 20070347]
Yang J. 2012. Meteorological satellites and their applications. Beijing: China Meteorological Press.
杨军. 2012. 气象卫星及其应用. 北京: 气象出版社
Zheng W, Li Y J, Liu C and Wang M. 2011. Extracting forest burned scar region area based on multi-source remote sensing data. Scientia Silvae Sinicae, 47(8): 192-195
郑伟, 李亚军, 刘诚, 王萌. 2011. 基于多源卫星遥感数据的森林过火区面积估算方法. 林业科学, 47(8): 192-195 [DOI: 10.11707/j.1001- 7488.20110830http://dx.doi.org/10.11707/j.1001- 7488.20110830]
Zheng W, Shao J L, Wang M and Liu C. 2013. Dynamic monitoring and analysis of grassland fire based on multi-source satellite remote sensing data. Journal of Natural Disasters, 22(3): 54-61
郑伟, 邵佳丽, 王萌, 刘诚. 2013. 多源卫星遥感草原火灾动态监测分析. 自然灾害学报, 22(3): 54-61 [DOI: 10.13577/j.jnd.2013.0308http://dx.doi.org/10.13577/j.jnd.2013.0308]
相关作者
相关机构
京公网安备11010802024621