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遥感技术与应用  2020, Vol. 35 Issue (5): 1099-1108    DOI: 10.11873/j.issn.1004-0323.2020.5.1099
遥感应用     
基于FY-3D MERSI数据的火点识别方法研究
殷针针1,2(),陈方1,2,3(),林政阳1,2,杨阿强1,李斌1
1.中国科学院遥感与数字地球研究所 中国科学院数字地球重点实验室,北京 100094
2.中国科学院大学,北京 100049
3.海南省地球观测重点实验室,海南 三亚 572029
Active Fire Monitoring based on FY-3D MERSI Satellite Data
Zhenzhen Yin1,2(),Fang Chen1,2,3(),Zhengyang Lin1,2,Aqaing Yang1,Bin Li1
1.Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100094,China
2.University of Chinese Academy of Sciences,Beijing 100049,China
3.Hainan Key Laboratory of Earth Observation,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Sanya 572029,China
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摘要:

火灾是一种全球性的自然灾害,及时准确地识别火点信息对防灾减灾及开展气候变化研究具有重要意义。基于我国新一代极轨卫星FY-3D MERSI影像数据,提出了改进的潜在火点识别算法,结合动态阈值法和上下文检测方法进行火点识别实验,并采用FY-3C VIRR数据、MOD14A1火点产品和Landsat8 OLI数据对火点识别结果进行验证分析。实验结果表明:改进后的算法能够快速有效地提取出火点信息,且对小型火点有较好的提取效果,为实现有效的灾情监测提供了方法手段。

关键词: FY-3D MERSI火点识别动态阈值上下文算法对比验证    
Abstract:

Fire is a global natural hazard. Effective methods of active fire monitoring would significantly contribute to disaster risk reduction as well as the studies on climate change. Based on the MERSI data from a new generation polar-orbiting FY-3D satellite in China, we proposed an improved algorithm for potential fire pixels identification. Then, dynamic threshold and a contextual fire detection algorithm are combined to carry out the fire monitoring experiment. FY-3C VIRR data, MOD14A1 fire products, and Landsat8 OLI data are used to validate and analyze the detection results. The results show that the improved algorithm can effectively detect fire spots including small fires, which provides a method for the effective hazard monitoring.

Key words: FY-3D MERSI    Active fire monitoring    Dynamic threshold    Contextual fire detection    Validation
收稿日期: 2019-04-08 出版日期: 2020-11-26
ZTFLH:  TP79  
基金资助: 国家自然科学基金项目(41871345)
通讯作者: 陈方     E-mail: yinzz@radi.ac.cn;chenfang_group@radi.ac.cn
作者简介: 殷针针(1994-),女,河南周口人,硕士研究生,主要从事火灾遥感监测研究。E?mail: yinzz@radi.ac.cn
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引用本文:

殷针针,陈方,林政阳,杨阿强,李斌. 基于FY-3D MERSI数据的火点识别方法研究[J]. 遥感技术与应用, 2020, 35(5): 1099-1108.

Zhenzhen Yin,Fang Chen,Zhengyang Lin,Aqaing Yang,Bin Li. Active Fire Monitoring based on FY-3D MERSI Satellite Data. Remote Sensing Technology and Application, 2020, 35(5): 1099-1108.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2020.5.1099        http://www.rsta.ac.cn/CN/Y2020/V35/I5/1099

图1  研究区FY-3D MERSI图像
通道序号中心波长/μm光谱带宽/nm空间分辨率/m主要用途代码
10.4750250真彩色(蓝),识别地面信息r1
20.5550250真彩色(绿),识别地面信息r2
30.6550250真彩色(红),识别地面信息r2
61.64501 000消除虚警r6
120.67201 000云和陆地识别,滤除耀斑r12
150.865201 000云和陆地识别,滤除耀斑r15
203.7961801 000火点识别T20
2410.7141 000250火点识别T24
2511.9481 000250云和陆地识别T25
表 1  FY-3D MERSI数据应用火点监测的光谱通道特性
图2  实验流程图
类型维数通道号系数项定标后量纲
定标系数Float32[19,3]1-19k0,k1,k2反射率—无量纲
表 2  MERSI L1数据可见光通道定标系数
图3  潜在火点识别结果对比图
图4  改进前潜在火点识别结果的分析图
图5  不同影像数据的火点识别结果图(Ⅰ、Ⅱ、Ⅲ、Ⅳ:不同影像数据的火点提取结果在MERSI图像上的显示;Ⅰ/Ⅱ/Ⅲ/Ⅳ-A/B/C/D:不同影像数据的子区域的火点提取结果)
图6  火点提取结果的对比验证图(A Ⅰ?Ⅱ、B Ⅰ?Ⅱ、C Ⅰ?Ⅱ、D Ⅰ?Ⅱ:四块子区域上FY?3D MERSI数据与FY?3C VIRR数据火点信息的对比验证结果;A Ⅰ?Ⅲ、B Ⅰ?Ⅲ、C Ⅰ?Ⅲ、D Ⅰ?Ⅲ:四块子区域上FY?3D MERSI数据与MOD14A1数据火点信息的对比验证结果;A Ⅰ?Ⅳ、B Ⅰ?Ⅳ、C Ⅰ?Ⅳ、D Ⅰ?Ⅳ:四块子区域上FY-3D MERSI数据与Landsat8 OLI数据火点信息的对比验证结果。)
图7  火点信息分布区域
验证数据FY3C VIRRMOD14A1Landsat8 OLI
验证数据的火点像元数目27032170
FY-3D MERSI数据的火点像元数目304304289
匹配度/%66.7874.0122.84
错分率/%33.2225.9977.16
漏分率/%24.8129.915.71
表3  火点识别结果精度评价表
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