Article(id=1156986622043575188, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156963927277003616, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2403286, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1714924800000, receivedDateStr=2024-05-06, revisedDate=1735142400000, revisedDateStr=2024-12-26, acceptedDate=null, acceptedDateStr=null, onlineDate=1753776706467, onlineDateStr=2025-07-29, pubDate=1742227200000, pubDateStr=2025-03-18, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753776706467, onlineIssueDateStr=2025-07-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753776706467, creator=13701087609, updateTime=1753776706467, updator=13701087609, issue=Issue{id=1156963927277003616, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='8', pageStart='3079', pageEnd='3528', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753771295613, creator=13701087609, updateTime=1753777038876, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1156988016305726153, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156963927277003616, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1156988016305726154, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156963927277003616, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3247, endPage=3257, ext={EN=ArticleExt(id=1156986625034113948, articleId=1156986622043575188, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Mountain Fire Monitoring and Early Warning Method of Transmission Line Based on Fengyun-3E Satellite, columnId=1156963928891806289, journalTitle=Science Technology and Engineering, columnName=Electrical Technology, runingTitle=null, highlight=null, articleAbstract=

With the construction of a new type of power system with new energy as the main body under the "double carbon" target, the challenges of natural disasters such as wildfires, icing and typhoons in the production, transmission and distribution of electric energy are more severe. Therefore, a fire point identification algorithm based on the world's first operational dawn-dusk orbit meteorological satellite Fengyun-3E satellite (FY-3E) was proposed, which was suitable for mountain fire monitoring in transmission line corridors, the adverse effects of large solar zenith angle observation conditions and satellite perspective differences on the accurate acquisition of infrared channel detection data were eliminated. Cloud information extraction and cloud pixel fire point extraction under complex atmospheric observation conditions were realized, which reduced fire point false alarms and missed alarms. The analysis of mixed pixel linear spectrum separation method shows that the fire point detection sensitivity of FY-3E mid-infrared channel is 4 times higher than that of geostationary meteorological satellite. The effectiveness of the proposed algorithm and the superiority of FY-3E in fire detection sensitivity, spatial range accuracy and positioning accuracy were verified. Compared with geostationary meteorological satellites, the fire location accuracy can be increased by more than one time, and it can effectively detect the fire time in advance by the transmission line operation and maintenance department, and guide the relevant departments to take timely measures to reduce the impact of wildfires on power grid operation.

, correspAuthors=Jie CHEN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Jing-jing FAN, Jin-song LI, Jie CHEN, Hui Yuan, Shuai Wang, Sheng-zhi Chang), CN=ArticleExt(id=1156986835059692351, articleId=1156986622043575188, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=基于风云三号$\mathrm{E}$星的输电线路山火监测预警方法, columnId=1154013917111115781, journalTitle=科学技术与工程, columnName=电工技术, runingTitle=null, highlight=null, articleAbstract=

随着“双碳”目标下以新能源为主体的新型电力系统构建,电能的生产、输送和分配各个环节受山火、覆冰、台风等自然灾害的挑战更加严峻。为此,提出了一种基于全球首颗业务化晨昏轨道气象卫星风云三号E星(FY-3E)的适用于输电线路走廊山火监测的火点判识算法,消除了大太阳天顶角观测条件和卫星视角差异对红外通道探测数据准确获取带来的不利影响,实现了复杂大气观测条件下的云信息提取和云像元火点提取,减少了火点误告警和漏告警。利用混合像元线性波谱分离方法分析表明,FY-3E中红外通道火点探测灵敏度达到静止气象卫星的4倍。在北方某省级电网应用,验证了所提算法的有效性与FY-3E在火点探测灵敏度、空间范围精度、定位精度的优越性,火点定位精度较静止气象卫星可提升1倍以上,能够有效提前输电线路运维部门发现火情时间,降低山火对电网运行的影响。

, correspAuthors=陈洁, authorNote=null, correspAuthorsNote=
*陈洁(1983—),男,汉族,浙江上虞人,硕士,高级工程师。研究方向:卫星遥感技术在自然灾害、生态环境和气候变化。E-mail: chenjie@cma.gov.cn。
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范晶晶(1992-),女,汉族,山西定襄人,硕士,工程师。研究方向:输变电设备灾害监测预警。E-mail: fanjjsxdky@163.com。

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范晶晶(1992-),女,汉族,山西定襄人,硕士,工程师。研究方向:输变电设备灾害监测预警。E-mail: fanjjsxdky@163.com。

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范晶晶(1992-),女,汉族,山西定襄人,硕士,工程师。研究方向:输变电设备灾害监测预警。E-mail: fanjjsxdky@163.com。

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Taiyuan 030001 China), AuthorCompanyExt(id=1156986845566423164, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, companyId=1156986845558034554, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3 山西世纪中试电力科学技术有限公司 太原 030001)])], figs=[ArticleFig(id=1156986851572666673, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Fig. 1, caption=Time distribution of mountain fire occurrence days in China from 2019 to 2021, figureFileSmall=KQhyIM8iv7+ruhdhHGqA0g==, figureFileBig=wHzJD3MBJkpDPGEzYqeAPg==, tableContent=null), ArticleFig(id=1156986851652358451, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=图1, caption=2019-2021 年中国地区山火发生日时间分布, figureFileSmall=KQhyIM8iv7+ruhdhHGqA0g==, figureFileBig=wHzJD3MBJkpDPGEzYqeAPg==, tableContent=null), ArticleFig(id=1156986851719467317, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Fig. 2, caption=Brightness temperature increment curve of the mixed pixel with different fire area for ${3.8\mu }\mathrm{m}$ mid-infrared channel and ${10.8\mu }\mathrm{m}$ far-infrared channel, figureFileSmall=EZSOhD/LIm/3WYNoio7TnQ==, figureFileBig=SE6CWxWIAaJhil5SkswdBQ==, tableContent=null), ArticleFig(id=1156986851794964791, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=图2, caption= ${3.8\mu }\mathrm{m}$ 中红外通道和 ${10.8\mu }\mathrm{m}$ 远红外通道混合像元亮温增量随火场面积变化曲线, figureFileSmall=EZSOhD/LIm/3WYNoio7TnQ==, figureFileBig=SE6CWxWIAaJhil5SkswdBQ==, tableContent=null), ArticleFig(id=1156986851870462265, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Fig. 3, caption=Brightness temperature increment of the mixed pixel of FY-3E, H8 and GK-2A mid-infrared channels with fire area, figureFileSmall=erdw1yN++MKFHYL/irZ2VA==, figureFileBig=FtIjSx6cBHyKjDEAehZ7sA==, tableContent=null), ArticleFig(id=1156986851945959739, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=图3, caption=FY-3E 及 H8、GK-2A 中红外通道的混合像元亮温增量随火场面积变化曲线, figureFileSmall=erdw1yN++MKFHYL/irZ2VA==, figureFileBig=FtIjSx6cBHyKjDEAehZ7sA==, tableContent=null), ArticleFig(id=1156986852000485693, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Fig. 4, caption=Flow chart of fire spot identification by FY-3E satellite, figureFileSmall=7WJkC+kPckqetv8h/m5rVQ==, figureFileBig=0AazNHFWZrguS00ENbt6Cw==, tableContent=null), ArticleFig(id=1156986852101148990, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=图4, caption=FY-3E 火点判识流程图

$R$ 为中红外通道原始反射率;${R}^{\prime }$ 为中红外通道反射率订正后的值;$z$ 为太阳天顶角;$\theta$ 为卫星天顶角;$\varphi$ 为卫星观测角;$T$ 为订正后的亮温;${\Delta T}$ 为不同卫星天顶角$\theta$ 的亮温订正值;${T}_{\mathrm{b}}$ 为原始亮度温度;${C}_{1}\text{、}{C}_{2}$ 为普朗克常数;$\nu$ 为探测波段的中心波数;$E$ 为定标后的辐射通量密度;${R}_{\mathrm{e}}$ 为地球半径;$H$ 为卫星高度;${T}_{3.8}$ 为待判像元中红外通道的亮温值;$K$ 为开尔文;${T}_{{3.8}\_ \mathrm{{bg}}}$ 为背景像元在中红外通道内的亮温值;${T}_{{3.8}- {10.8}}$ 为待判像元中红外与远红外通道亮温差;${T}_{{3.8}\_ {10.8}\mathrm{{bg}}}$ 为背景像元中红外与远红外通道亮温差;${\mathrm{{TC}}}_{{3.8}\mathrm{{th}}}$ 为云像元中红外亮温阈值;${T}_{{3.8}- {10.8}\mathrm{{th}}}$ 为云像元中红外与远红外亮温差值阈值;${\mathrm{{TC}}}_{\text{fireth }}$ 为云像元火点判识阈值;$\delta {T}_{{3.8}\mathrm{\;{bg}}}$ 为背景像元在中红外通道内的亮温标准差;$\delta {T}_{{3.8}- {10.8}\mathrm{{bg}}}$ 为背景像元中红外与远红外通道亮温差的标准差;$\alpha \left({{P}_{\mathrm{v}};{P}_{\mathrm{c}}, z}\right)$ 为校正系数函数;${P}_{\mathrm{v}}$ 为区域内非植被像元比例;${P}_{\mathrm{c}}$ 为区域内云像元比例

, figureFileSmall=7WJkC+kPckqetv8h/m5rVQ==, figureFileBig=0AazNHFWZrguS00ENbt6Cw==, tableContent=null), ArticleFig(id=1156986852164063552, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Fig. 5, caption=Curves of normalized earth emission and reflection of solar black-body radiation, figureFileSmall=GTzflicR9Pnstcj0rKt5JQ==, figureFileBig=nTukCelI2u5dSall4cHMYw==, tableContent=null), ArticleFig(id=1156986852243755329, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=图5, caption=归一化地球发射和反射太阳黑体辐射曲线

$\lambda$ 为波长;$T$ 为温度;$B\left({\lambda , T}\right)$ 为普朗克函数;$R$ 为反射率

, figureFileSmall=GTzflicR9Pnstcj0rKt5JQ==, figureFileBig=nTukCelI2u5dSall4cHMYw==, tableContent=null), ArticleFig(id=1156986852306669892, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Fig. 6, caption=Schematic diagram of the solar and satellite observation angles, figureFileSmall=mrYH2zAJuvPkf95LyUbRjw==, figureFileBig=2vsL9Ox/ug5Q7xCA4vIUoA==, tableContent=null), ArticleFig(id=1156986852361195844, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=图6, caption=太阳、卫星观测角度示意图

$z$ 为太阳天顶角,表示太阳入射线与像元地平面法线的夹角;$\theta$ 为卫星天顶角,表示卫星传感器与像元的连线和像元地平面法线的夹角;$\varphi$ 为卫星观测角,表示卫星传感器与像元的连线和卫星传感器与地心连线所成的夹角;${R}_{\mathrm{e}}$ 为地球半径

, figureFileSmall=mrYH2zAJuvPkf95LyUbRjw==, figureFileBig=2vsL9Ox/ug5Q7xCA4vIUoA==, tableContent=null), ArticleFig(id=1156986852440887622, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Fig. 7, caption=Relative position between fire spot location and transmission line, figureFileSmall=cOZvskyk7k6e083vUCxukg==, figureFileBig=53YuRgi/5kt4WMIwFbLxkQ==, tableContent=null), ArticleFig(id=1156986852499607881, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=图7, caption=火点定位与输电线路相对位置, figureFileSmall=cOZvskyk7k6e083vUCxukg==, figureFileBig=53YuRgi/5kt4WMIwFbLxkQ==, tableContent=null), ArticleFig(id=1156986852562522443, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Fig. 8, caption=Fire spot scene in Tianzhen County, Shanxi Province, figureFileSmall=mj+F3PUL4gApuNR/fjhcsw==, figureFileBig=gyXrFOtR5U/BHTAU36VW4g==, tableContent=null), ArticleFig(id=1156986852633825613, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=图8, caption=山西省天镇县火点现场情况, figureFileSmall=mj+F3PUL4gApuNR/fjhcsw==, figureFileBig=gyXrFOtR5U/BHTAU36VW4g==, tableContent=null), ArticleFig(id=1156986852726100302, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Fig. 9, caption=FY-3E 3. 8,10.8,12μm three-channel RGB composite image of fire in Tianzhen County, Shanxi Province at 16:50 on March, 30, 2022, figureFileSmall=A+gY2OQ161sykpYcKkfupQ==, figureFileBig=rCyyGifwrXnD7ohQOuphBA==, tableContent=null), ArticleFig(id=1156986852822569296, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=图9, caption=2022 年 3 月 30 日 16:50 山西省天镇县火情 FY-3E3.8、 10.8、12μm 三通道 RGB 合成图

红色区域为火区,包含 2 个火点像元;黄色十字表示现场核实火情位置

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亮红色区域为火区;黄色十字表示现场核实火情位置

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白色表示亮度温度较高;黑色表示亮度温度较低;红框区域为判识的火点像元

, figureFileSmall=DkY2vRMS0UvH/TowbFXe6A==, figureFileBig=8gO2TEibhPr3zN1+dz9PdQ==, tableContent=null), ArticleFig(id=1156986853636264294, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Fig. 15, caption=Brightness temperatures of FY-3E and GK-2A mid-infrared channels in Shuocheng District fire area, Shanxi Province from 17:50 to 18:25, figureFileSmall=n5L4Oru16gg3AJDbWr42AQ==, figureFileBig=09ti2a1OkLQLjXop0VPgsQ==, tableContent=null), ArticleFig(id=1156986853686595944, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=图15, caption=17:50-18:25 山西省朔城区火场区域 FY-3E 和 GK-2A 中红外通道亮温数据, figureFileSmall=n5L4Oru16gg3AJDbWr42AQ==, figureFileBig=09ti2a1OkLQLjXop0VPgsQ==, tableContent=null), ArticleFig(id=1156986853749510507, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Table 1, caption=Major parameters of FY-3E/MERSI-LL channels ${}^{\left\lbrack {24}- {25}\right\rbrack }$, figureFileSmall=null, figureFileBig=null, tableContent=
通道编号 中心波长/ μm 通道带宽/$\mathrm{{nm}}$ 空间分辨 率/km 主要用途
1 0.70 400 1 微光图像、夜间 定量遥感
2 3.80 180 1 火、地表温度、海表温度、云参数
3 4.05 155 1
4 7.20 500 1 大气水汽
5 8.55 300 1 卷云,云发射
6 10.80 1000 0.25 地表温度、海表温度、云参数
7 12.00 1000 0.25 地表温度、海表温度、云参数
), ArticleFig(id=1156986853825007982, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=表1, caption=FY-3E/MERSI-LL 通道参数 ${}^{\left\lbrack {24}- {25}\right\rbrack }$, figureFileSmall=null, figureFileBig=null, tableContent=
通道编号 中心波长/ μm 通道带宽/$\mathrm{{nm}}$ 空间分辨 率/km 主要用途
1 0.70 400 1 微光图像、夜间 定量遥感
2 3.80 180 1 火、地表温度、海表温度、云参数
3 4.05 155 1
4 7.20 500 1 大气水汽
5 8.55 300 1 卷云,云发射
6 10.80 1000 0.25 地表温度、海表温度、云参数
7 12.00 1000 0.25 地表温度、海表温度、云参数
), ArticleFig(id=1156986853883728241, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Table 2, caption=Cloud pixel identification method, figureFileSmall=null, figureFileBig=null, tableContent=
序号 条件
1 ${T}_{3.8}- {T}_{10.8}< 4\mathrm{\;K}$
2 ${T}_{3,8}- {T}_{{10},8}> {20}\mathrm{\;K}\&\left({{T}_{3,8}< {275}\mathrm{\;K}\mid {T}_{{10},8}< {270}\mathrm{\;K}}\right)$
), ArticleFig(id=1156986853996974453, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=表2, caption=云像元判识方法, figureFileSmall=null, figureFileBig=null, tableContent=
序号 条件
1 ${T}_{3.8}- {T}_{10.8}< 4\mathrm{\;K}$
2 ${T}_{3,8}- {T}_{{10},8}> {20}\mathrm{\;K}\&\left({{T}_{3,8}< {275}\mathrm{\;K}\mid {T}_{{10},8}< {270}\mathrm{\;K}}\right)$
), ArticleFig(id=1156986854068277625, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=EN, label=Table 3, caption=Monitoring fire spot information of FY-3E and H8 in Tianzhen County, Shanxi Province on March 30, 2022, figureFileSmall=null, figureFileBig=null, tableContent=
卫星 发现火 情时间 监测山 火像元 数/个 面积/km ${}^{2}$ 东西 距离/$\mathrm{{km}}$ 南北 距离/$\mathrm{{km}}$ 火点定 位与实 测火情 距离 $/\mathrm{{km}}$
FY-3E 16 :50 2 1.9 1.7 1.1 1.12
H8 17 :00 1 3.9 1.7 2.3 3.25
), ArticleFig(id=1156986854139580796, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156986622043575188, language=CN, label=表3, caption=2022 年 3 月 30 日山西省天镇县火点 FY-3E 和 H8 监测信息, figureFileSmall=null, figureFileBig=null, tableContent=
卫星 发现火 情时间 监测山 火像元 数/个 面积/km ${}^{2}$ 东西 距离/$\mathrm{{km}}$ 南北 距离/$\mathrm{{km}}$ 火点定 位与实 测火情 距离 $/\mathrm{{km}}$
FY-3E 16 :50 2 1.9 1.7 1.1 1.12
H8 17 :00 1 3.9 1.7 2.3 3.25
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基于风云三号$\mathrm{E}$星的输电线路山火监测预警方法
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范晶晶 1 , 李劲松 1 , 陈洁 2, * , 原辉 1 , 王帅 1 , 常圣志 3
科学技术与工程 | 电工技术 2025,25(8): 3247-3257
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科学技术与工程 | 电工技术 2025, 25(8): 3247-3257
基于风云三号$\mathrm{E}$星的输电线路山火监测预警方法
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范晶晶1 , 李劲松1, 陈洁2, * , 原辉1, 王帅1, 常圣志3
作者信息
  • 1 国网山西省电力公司 电力科学研究院 太原 030001
  • 2 国家卫星气象中心 北京 100081
  • 3 山西世纪中试电力科学技术有限公司 太原 030001
  • 范晶晶(1992-),女,汉族,山西定襄人,硕士,工程师。研究方向:输变电设备灾害监测预警。E-mail: fanjjsxdky@163.com。

通讯作者:

*陈洁(1983—),男,汉族,浙江上虞人,硕士,高级工程师。研究方向:卫星遥感技术在自然灾害、生态环境和气候变化。E-mail: chenjie@cma.gov.cn。
Mountain Fire Monitoring and Early Warning Method of Transmission Line Based on Fengyun-3E Satellite
Jing-jing FAN1 , Jin-song LI1, Jie CHEN2, * , Hui Yuan1, Shuai Wang1, Sheng-zhi Chang3
Affiliations
  • 1 State Grid Shanxi Electric Power Research Institute Taiyuan 030001 China
  • 2 National Satellite Meteorological Center Beijing 100081 China
  • 3 Shanxi Century Central Test Electricity Science & Technology Co., Ltd. Taiyuan 030001 China
出版时间: 2025-03-18 doi: 10.12404/j.issn.1671-1815.2403286
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随着“双碳”目标下以新能源为主体的新型电力系统构建,电能的生产、输送和分配各个环节受山火、覆冰、台风等自然灾害的挑战更加严峻。为此,提出了一种基于全球首颗业务化晨昏轨道气象卫星风云三号E星(FY-3E)的适用于输电线路走廊山火监测的火点判识算法,消除了大太阳天顶角观测条件和卫星视角差异对红外通道探测数据准确获取带来的不利影响,实现了复杂大气观测条件下的云信息提取和云像元火点提取,减少了火点误告警和漏告警。利用混合像元线性波谱分离方法分析表明,FY-3E中红外通道火点探测灵敏度达到静止气象卫星的4倍。在北方某省级电网应用,验证了所提算法的有效性与FY-3E在火点探测灵敏度、空间范围精度、定位精度的优越性,火点定位精度较静止气象卫星可提升1倍以上,能够有效提前输电线路运维部门发现火情时间,降低山火对电网运行的影响。

风云三号E星(FY-3E)  /  输电线路山火  /  火点判识  /  晨昏时段监测  /  卫星遥感

With the construction of a new type of power system with new energy as the main body under the "double carbon" target, the challenges of natural disasters such as wildfires, icing and typhoons in the production, transmission and distribution of electric energy are more severe. Therefore, a fire point identification algorithm based on the world's first operational dawn-dusk orbit meteorological satellite Fengyun-3E satellite (FY-3E) was proposed, which was suitable for mountain fire monitoring in transmission line corridors, the adverse effects of large solar zenith angle observation conditions and satellite perspective differences on the accurate acquisition of infrared channel detection data were eliminated. Cloud information extraction and cloud pixel fire point extraction under complex atmospheric observation conditions were realized, which reduced fire point false alarms and missed alarms. The analysis of mixed pixel linear spectrum separation method shows that the fire point detection sensitivity of FY-3E mid-infrared channel is 4 times higher than that of geostationary meteorological satellite. The effectiveness of the proposed algorithm and the superiority of FY-3E in fire detection sensitivity, spatial range accuracy and positioning accuracy were verified. Compared with geostationary meteorological satellites, the fire location accuracy can be increased by more than one time, and it can effectively detect the fire time in advance by the transmission line operation and maintenance department, and guide the relevant departments to take timely measures to reduce the impact of wildfires on power grid operation.

Fengyun-3E satellite (FY-3E)  /  mountain fire of transmission line  /  fire point identification  /  dawn-dusk monitoring  /  satellite remote sensing
范晶晶, 李劲松, 陈洁, 原辉, 王帅, 常圣志. 基于风云三号$\mathrm{E}$星的输电线路山火监测预警方法. 科学技术与工程, 2025 , 25 (8) : 3247 -3257 . DOI: 10.12404/j.issn.1671-1815.2403286
Jing-jing FAN, Jin-song LI, Jie CHEN, Hui Yuan, Shuai Wang, Sheng-zhi Chang. Mountain Fire Monitoring and Early Warning Method of Transmission Line Based on Fengyun-3E Satellite[J]. Science Technology and Engineering, 2025 , 25 (8) : 3247 -3257 . DOI: 10.12404/j.issn.1671-1815.2403286
为了实现低碳减排和 “碳中和” 的目标, 需要大幅提高风能、太阳能等可再生能源的利用率。在中国,可再生能源主要分布在西北地区和沿海地区, 清洁电能需要通过大规模、远距离的输电线路输至南部负荷中心, 输电线路经常要穿越森林草原等高高植被覆盖地区${}^{\left\lbrack 1 \cdot 2\right\rbrack }$。工农业用火、雷击起火等引发的山火,可使输电电路通道持续处于低绝缘状态, 容易导致长时间故障, 引发大范围停电事故, 严重危害社会生产及人民生活[3-6]。为了有效降低山火灾害对输电线路的威胁, 提高山火监测预警的准确度和及时率至关重要。
目前,输电线路山火监测手段主要有人工巡视、飞机巡航、可见光和红外图像监拍及气象卫星遥感[7]。气象卫星遥感具有监测范围广、观测频率高、成本低等优点,已成为山火监测预警的重要手${\mathbb{段}}^{\left\lbrack {8.9}\right\rbrack }$。极轨气象卫星和静止气象卫星已被广泛用于山火监测。极轨气象卫星主要有: 国家极地轨道环境操作卫星 (National Polar-orbiting Operational Environmental Satellite System Preparatory Project, NPP)、美国国家海洋与大气管理局系列(National Oceanic and Atmospheric Administration, NOAA)、地球观测系统系列 (Earth Observing System, EOS) 和中国的风云三号系列 (FY-3C、FY-3D)。静止气象卫星包括葵花 8 号(Himawari-8, H8)、韩国多用途卫星 (Geo-Kompsat-2A, GK-2A)、欧洲 Meteosat 第二代卫星 (MSG)、地球静止轨道环境业务卫星 (GOES-16) 和中国的风云四号系列 (FY-4A、FY-4B)${}^{\left\lbrack {10}\text{-15}\right\rbrack }$
尽管静止气象卫星具有极高的时间分辨率,但相对较低的空间分辨率和火灾探测灵敏度容易使其漏掉输电线路附近的一些较小火情。极轨气象卫星能实现观测的全球覆盖, 并将使用几乎恒定的当地太阳时间每天两次观测每个位置[16]。而且,极轨气象卫星距离地球较近, 只有静止气象卫星距地约 1/5,空间分辨率显著高于静止气象卫星。人工火场验证试验表明,地球观测系统中分辨率成像光谱仪(Earth Observing System/moderate-resolution imaging spectroradiometer, EOS/MODIS) 和风云三号 D 星搭载的 II 型中分辨率光谱成像仪 (Fengyun-3D/ medium resolution spectral imager- II , FY-3D/MERSI-II) 能够识别的最小火场面积约为${100}{\mathrm{\;m}}^{2\left\lbrack {{17}- {18}}\right\rbrack }$
风云三号 E 星 (FY-3E) 于 2022 年 3 月正式运行,是全球首颗业务化晨昏轨道气象卫星,其搭载的中分辨率光谱成像仪(微光型)MERSI-LL(medium resolution spectral imager-LL) 在性能上有明显提升, 为傍晚时段山火精准监测提供了新的技术手段。国家卫星气象中心在风云三号系列卫星数据的基础上, 已开展了一系列的火点判识算法研究和火点监测产品开发应用工作[19-21]。但是由于光谱成像仪和观测时间的差异, 传统的火点判识算法无法应用于 FY-3E。
鉴于此,基于晨昏时段大气状况和 FY-3E/ MERSI-LL 仪器特性, 提出考虑红外辐射订正和复杂大气观测条件的火点判识算法, 并利用混合像元线性分解方法定量分析 FY-3E/MERSI-LL 与 Hima-wari-8/AHI、Geo-Kompsat-2A/AMI 不同分辨率中红外通道对火点探测灵敏度的影响。首次将 FY-3E 应用于电网输电线路山火监测预警工作中,应用实例验证所提算法的有效性和 FY-3E 相比静止气象卫星$\mathrm{H}8$$\mathrm{{GK}}2\mathrm{\;A}$ 的优越性,能够有效提升输电线路山火监测预警能力。
目前极轨气象卫星的过境时间集中分布在当地时间$9 :{00}- {11}: {00}$${13}: {00}- {16}: {00}^{\left\lbrack {22}- {23}\right\rbrack }$,在 16:00-19:00 时段存在监测间隙。图1 为 2019-2021 年中国地区山火发生日时间分布统计图,中国地区傍晚时段 (16:00-19:00) 发生的山火数量仅次于下午时段, 无极轨气象卫星过境监测容易造成火点漏告警。
风云三号E星(FY-3E)是由中国自主研制的全球首颗业务化晨昏轨道气象卫星,于 2021 年 7 月 5 日在酒泉卫星发射中心发射, 2022 年 3 月正式投入运行。FY-3E 卫星发射重量为${2.3}\mathrm{t}$,设计使用年限 8 年,轨道倾角${98.75}^{\circ }$,轨道标称高度约为 836$\mathrm{{km}}$。每日地方时 05:30 和 17:30 两次观测地球表面。FY-3E 搭载全新研制的中分辨率光谱成像仪 (微光型) MERSI-LL,共设置 7 个观测通道, 包括 1 个微光通道, 6 个热红外通道。MERSI-LL 通道的主要技术参数如表${1}^{\left\lbrack {24}- {25}\right\rbrack }$ 所示。相比于中国地区目前常用于山火监测的静止气象卫星$\mathrm{H}8$$\mathrm{{GK}}-2\mathrm{\;A},\mathrm{{FY}}-$ $3\mathrm{E}$ 在中红外和远红外通道空间分辨率上有明显提升。
根据维恩位移定律, 黑体辐射峰值与温度成反比,常温 (约${290}\mathrm{\;K}$) 地表辐射峰值波长在${11\mu }\mathrm{m}$ 波长范围左右,地面发生火情时温度一般在${750}\mathrm{\;K}$ 以上,其热辐射峰值波长靠近${4\mu }\mathrm{m}$ 的中红外通道。因此, 可以利用火场辐射和未发生燃烧时背景辐射在${4\mu }\mathrm{m}$${11\mu }\mathrm{m}$ 波段的差异进行火情监测[26-28]
FY-3E/MERSI-LL 拥有$1\mathrm{\;{km}}$ 分辨率的${3.8\mu }\mathrm{m}$ 中红外通道,${250}\mathrm{\;m}$ 分辨率的${10.8\mu }\mathrm{m}$${12\mu }\mathrm{m}$ 远红外通道。按分辨率较高的远红外通道计算,${250}\mathrm{\;m}$ 分辨率像元覆盖面积约为${62500}{\mathrm{\;m}}^{2}$,而森林草原火场极少有在如此大的范围内同时燃烧的情况。因此, 覆盖火场的像元可看作含有火场的混合像元。
山火发生后, 由于明火的温度和辐射率高出地表其他物体数倍至数百倍, 根据混合像元线性分解方法, 含有火点的混合像元的辐射强度可表示为明火区能量与非明火区能量的线性组合,如式 (1)[29] 所示。
${L}_{i\operatorname{mix}}= P{L}_{\mathrm{{ft}}}+ \left({1 - P}\right){L}_{\mathrm{{bg}}}\\= P\frac{{C}_{1}{\lambda }_{i}^{-5}}{\pi \left({{\mathrm{e}}^{\frac{{C}_{2}}{{\lambda }_{i}{T}_{\mathrm{{ff}}}}}-1}\right)} +\left({1 - P}\right)\frac{{C}_{1}{\lambda }_{i}^{-5}}{\pi \left({{\mathrm{e}}^{\frac{{C}_{2}}{{\lambda }_{i}{T}_{\mathrm{{bg}}}}}-1}\right)} $
式 (1) 中:${L}_{i\operatorname{mix}}$$i$ 通道火点像元的辐射强度;$P$ 为亚像元明火区占像元面积的比例;${L}_{\mathrm{{ft}}}$${L}_{\mathrm{{bg}}}$ 分别为明火区和非明火区 (火点周围背景) 的辐射强度;${T}_{\mathrm{{ft}}}$${T}_{\mathrm{{bg}}}$ 分别为火点像元温度和背景温度;${\lambda }_{i}$$i$ 通道火点像元的中心波长;${C}_{1}$ 为第一普朗克常数,为${1.91043}\times$ ${10}^{8}\mathrm{\;W}\cdot \mu {\mathrm{m}}^{4}/\left({{\mathrm{m}}^{2}\cdot \mathrm{{sr}}}\right);{C}_{2}$ 为第二普朗克常数,为 1.438${768}\times {10}^{4}\mathrm{{\mu m}}\cdot \mathrm{K}$
判识火点像元的主要标准是被探测像元的亮温是否异常高于周边像元 (假设两者具有相同的下垫面类型)。设${T}_{i\operatorname{mix}}$ 为含有火点的混合像元亮温,${T}_{\mathrm{{bg}}}$ 为背景像元亮温,则$i$ 通道含火点的混合像元与背景像元的亮温差异$\Delta {T}_{i}$ 可由式 (2) 获得。
$\Delta {T}_{i}= {T}_{i\operatorname{mix}}- {T}_{\mathrm{{bg}}}\\= \frac{{C}_{2}}{{\lambda }_{i}\ln \left({1 +\frac{{C}_{1}}{\pi {\lambda }_{i}^{5}{L}_{i\operatorname{mix}}}}\right)} -\frac{{C}_{2}}{{\lambda }_{i}\ln \left({1 +\frac{{C}_{1}}{\pi {\lambda }_{i}^{5}{L}_{\mathrm{{bg}}}}}\right)} $
假设背景温度为${290}\mathrm{\;K}$,火点温度为${800}\mathrm{\;K}$,将火场面积换算为亚像元明火区占比,根据式 (2) 绘制混合像元在${3.8\mu }\mathrm{m}$ 中红外通道和${10.8\mu }\mathrm{m}$ 远红外通道的亮温增量与火场面积的关系曲线, 如图2 所示。随着火场面积逐步增大, 中红外通道监测的含有火点的混合像元亮温增量增速明显,且与远红外通道亮温增量差异逐渐增大。即使火场面积很小时,中红外通道监测的亮温增量也很明显。因此, 基于中红外通道亮温对含有火点像元高灵敏的特点, 可以利用火点像元与周边背景像元在中红外通道亮温及中红外通道与远红外通道亮温差这两个特征值的差异来判识火点。
利用式 (2) 对 FY-3E$1\mathrm{\;{km}}$ 分辨率${3.8\mu }\mathrm{m}$ 中红外通道与静止气象卫星$\mathrm{H}8$$\mathrm{{GK}}-2\mathrm{\;A}2\mathrm{\;{km}}$ 分辨率${3.8\mu }\mathrm{m}$ 中红外通道火点探测灵敏度进行定量对比分析。图3 为 FY-3E 和 H8、GK-2A 中红外通道的混合像元亮温增量随火场面积变化曲线。当火场面积为${80}{\mathrm{\;m}}^{2}$,亚像元明火区占比$P$ 为 FY-3E$1\mathrm{\;{km}}$ 分辨率像元的 0.008%, FY-3E 中红外通亮温增量约为$7\mathrm{\;K}$,超出中国地区通常的火点判识阈值 (6K),而$\mathrm{H}8\text{、}\mathrm{{GK}}-2\mathrm{\;A}$ 中红外通道的亮温增量只有约${1.8}\mathrm{\;K}$,当火场面积为${300}{\mathrm{\;m}}^{2}$ 时,$\mathrm{H}8\text{、}\mathrm{{GK}}-2\mathrm{\;A}$ 中红外通道亮温增量才达到中国地区火点判识阈值 (6K)。由此可见, FY-3E$1\mathrm{\;{km}}$ 分辨率中红外通道火点判识灵敏度是静止气象卫星$\mathrm{H}8$$\mathrm{{GK}}-2\mathrm{\;A}2\mathrm{\;{km}}$ 分辨率中红外通道的约 4 倍, 能够探测到百平方米面积大小的火点。
传统的人机交互火点监测方式通过对中红外、 近红外、可见光通道组成的多通道合成图判识火点, 对人工经验和图像处理技术依赖性高。基于 EOS/MODIS 和 FY-3D/MERSI-II 火点判识算法[22], 根据晨昏时段大气状况和 FY-3E/MERSI-LL 仪器特性,综合考虑大太阳天顶角观测条件和卫星视角对红外通道探测数据的影响, 复杂大气条件下的云信息提取和云像元火点提取, 提出一种 FY-3E 火点自动判识算法, 根据火点引起 FY-3E 中红外通道辐射亮度和亮温值的急剧变化和中红外与远红外通道辐亮度和亮温差异的显著变化进行火点判识。图4 为 FY-3E 火点判识流程。
依据山火监测原理,中红外和远红外通道亮温数据的准确获取对火点判识至关重要。图5 为归一化地球发射和反射太阳黑体辐射曲线。${3.8\mu }\mathrm{m}$ 中红外通道接近于地球大气辐射光谱曲线与反射太阳光谱曲线相交处, 因此, 中红外通道在晨昏时段接收的辐射既有地 (云) 面发射的辐射,也有地 (云) 面反射的太阳辐射,而${10.8\mu }\mathrm{m}$${12.0\mu }\mathrm{m}$ 远红外通道接收的主要是由地球发射的辐射[30]
图6 给出了太阳、卫星观测角度示意图。
太阳天顶角决定了卫星观测地面时的照明条件, 太阳天顶角越小, 照明条件越好, 卫星接收到的反射太阳辐射越多。FY-3E 扫描带宽约为${2500}\mathrm{\;{km}}$,探测范围较大, 太阳天顶角在同一扫描带的不同位置探测点的差异很大, 因此, 中红外通道的反射率需要进行太阳天顶角订正, 即将不同太阳天顶角下的探测值归一化为太阳位于天顶时的探测值。传统的太阳天顶角订正公式为
${R}^{\prime }= \frac{R}{\cos z}$
式 (3) 中:$R$ 为中红外通道原始反射率;${R}^{\prime }$ 为中红外通道反射率订正后的值。
由于 FY-3E 为晨昏时段观测,太阳天顶角很大,$\cos z$ 很小,使用式 (3) 修正会出现大量的过饱和像元,因此,需要对传统的太阳天顶角订正公式进行修正[16],根据经验修正后订正公式为
${R}^{\prime }= \frac{R}{\cos \left\lbrack {z\left({{1.0}- {1.3}\sin {0.05z}}\right)}\right\rbrack }$
试验表明,当太阳天顶角接近 90 度时,式(4) 的修正比例约为式 (3) 的$1/8$,产生更少的过饱和像元。因此,采用式 (4) 对太阳天顶角进行订正。
受地球曲率和大气衰减的影响, 不同的卫星视角会导致红外通道的探测数据出现差异, 被测像元愈靠近扫描条带的边缘, 辐射到达星载探测仪器的大气光学路径越长,大气衰减越严重。因此,为了消除卫星观测视角不同导致被测像元红外通道亮温数值的差异, 需要对原始探测数据进行临边订正处理,将其统一为卫星处于天顶探测时的数值,采用 NESDIS 全球拼图系统中所使用的经验订正方法进行临边变暗订正,其订正表达式为[31-32]
$ T ={T}_{\mathrm{b}}+ {\Delta T}$
${\Delta T}= \left({{e}^{0.00012}-1}\right)\left({{0.107.2T}- {26.81}}\right)$
式中:$T$ 为订正后的亮温;${\Delta T}$ 为不同卫星天顶角$\theta$ 的亮温订正值;${T}_{\mathrm{b}}$ 为原始亮度温度,由普朗克公式计算得
${T}_{\mathrm{b}}= \frac{{C}_{2}}{\ln \left({{C}_{1}\frac{{v}^{3}}{E}+ 1}\right)} $
$\theta =\arcsin \left(\frac{{R}_{\mathrm{e}}+ H}{{R}_{\mathrm{e}}\sin \varphi }\right)$
式中:${C}_{1}\text{、}{C}_{2}$ 为普朗克常数;$\nu$ 为探测波段的中心波数;$E$ 为定标后的辐射通量密度;${R}_{\mathrm{e}}$ 为地球半径;$H$ 为卫星高度;$\varphi$ 为卫星观测角。
云覆盖会对火点判识造成显著的影响。一方面云层的存在易遮挡地面火情信息,造成进入传感器火点能量衰减导致漏判; 另一方面云层产生的镜面反射会引起亮温异常增大导致火点误判。由于 FY-3E/MERSI-LL 为晨昏时段观测,无有效的可见光通道信息辅助云像元判识[33],因此,无法使用目前主流的 MODIS 云检测算法 (Cloud Mask) 提取云像元信息[34],需要充分利用中红外和远红外通道亮温数据进行提取。云像元判识方法如表2 所示, 当满足其中任意一条,即可被判识为云像元。
根据火点监测原理,背景亮温获取是判识火点过程的重要步骤, 通常根据探测像元周边像元的亮温平均值来计算。然而监测区域内太阳辐射在云面、水体等引起的反射、不同植被类型覆盖和包含火点的像元都会影响背景亮温的计算, 导致背景亮温值偏高, 从而漏判真实火点。因此首先需要筛选出这类可疑高温像元。文献 [35] 提出采用背景亮温的标准差来进行火点判识, 有效解决了背景亮温计算偏高的问题。所提出的判识可疑高温像元的方法为:选择监测区域像元中位于 20% 比例高温度的像元作为待判像元, 根据式 (9) 对待判像元逐一进行可疑高温像元判识处理:
${T}_{3.8}\geq {T}_{{3.8}\text{ mean }}+ \min \left({2{T}_{{3.8}\mathrm{{std}}\_ \mathrm{{bg}}},{T}_{\text{th }}}\right)$
式 (9) 中:${T}_{{3.8}\mathrm{{mean}}}$ 为监测区域所有像元亮温平均值;${T}_{{3.8}\mathrm{{std}}\_ \mathrm{{bg}}}$ 为监测区域所有像元亮温的标准差;${T}_{\mathrm{{th}}}$ 为背景亮温阈值,与下垫面均一程度有关,初始值可设为$5\mathrm{\;K}$
将探测像元周边的可疑高温像元和云像元筛除后, 剩余像元作为有效像元计算探测像元的背景亮温信息,即有效像元亮温的平均值,包括${3.8\mu }\mathrm{m}$ 中红外通道亮温平均值、${10.8\mu }\mathrm{m}$ 远红外通道亮温平均值、${3.8\mu }\mathrm{m}$ 中红外通道与${10.8\mu }\mathrm{m}$ 远红外通道亮温差异平均值等。参与背景亮温计算的像元选取流程为: 选择探测像元周边邻域$5 \times 5$ 个像元中的有效像元, 如有效像元数目不到邻域像元总数的${20}\%$,扩大到$7 \times 7\text{、}9 \times 9\text{、}{11}\times {11}$,直至${19}\times {19}$,如仍不满足条件, 放弃该探测像元的火点判识。
在获取背景亮温的基础上进行火点确认, 确认条件分为绝对阈值条件和相对阈值条件。绝对阈值条件通过比较待判像元亮温与设定阈值大小进行判识。相对阈值条件通过比较中红外通道亮温和中、远红外通道亮温差值在待判像元与周边背景像元的亮温差异判识火点。具体地,当待判像元满足式 (10) 或者式(11)时,可确认为火点像元。FY-3E 卫星为晨昏轨道气象卫星,观测时段太阳天顶角较大,同时由于不考虑可见光校正处理, 因此基于红外通道的判识条件较 MODIS 和 FY-3D 更为严格[22]
${T}_{3.8}> {340}\mathrm{\;K}$
$\left\{\begin{array}{l}{T}_{3.8}\geq {T}_{{3.8}- \mathrm{{bg}}}+ \alpha \left({{P}_{\mathrm{v}},{P}_{\mathrm{c}}, z}\right)\delta {T}_{{3.8}- \mathrm{{bg}}}\\{T}_{{3.8}- {10.8}}\geq {T}_{{3.8}- {10.8}\mathrm{\;{bg}}}+ \alpha \left({{P}_{\mathrm{v}},{P}_{\mathrm{c}}, z}\right)\delta {T}_{{3.8}- {10.8}\mathrm{\;{bg}}}\\\alpha \left({{P}_{\mathrm{v}},{P}_{\mathrm{c}}, z}\right)= \left({{1.2}\cos {\theta }_{z}+ 1}\right)\left({1 +{P}_{\mathrm{v}}}\right){\left(1 +{P}_{\mathrm{c}}\right)}^{2}\end{array}\right.$
式中:${T}_{{3.8}\mathrm{\_ }\mathrm{{bg}}}$ 为背景像元在中红外通道内的亮温值;$\delta {T}_{{3.8}\_ \mathrm{{bg}}}$ 为背景像元在中红外通道内的亮温标准差;${T}_{{3.8}\_ {10.8}}$ 为待判像元中红外与远红外通道亮温差;${T}_{{3.8}\_ {10.8}\mathrm{{bg}}}$ 为背景像元中红外与远红外通道亮温差;$\delta {T}_{{3.8}- {10.8}\mathrm{{bg}}}$ 为背景像元中红外与远红外通道亮温差的标准差;$\alpha \left({{P}_{\mathrm{v}},{P}_{\mathrm{c}}, z}\right)$ 为校正系数函数,与非植被像元比例、云像元比例和太阳天顶角有关;${P}_{\mathrm{v}}$ 为区域内非植被像元比例;${P}_{\mathrm{c}}$ 为区域内云像元比例;$z$ 为太阳天顶角。
传统火点判识算法中通常放弃云区像元火点提取[17-18,33,35],导致部分火点漏判。事实上,薄云情况下一定的火场能量能够穿透云层到达卫星传感器,具备火点判识条件。为了在多种条件下最大程度地提取火点信息, 提出在薄云条件下的火点判识方法, 步骤如下。
步骤 1 云像元潜在火点筛选。
当云像元满足以下条件时,判断其为潜在火点, 并计算其背景亮温平均值。
$\left\{\begin{array}{l}{T}_{3.8}\geq {\mathrm{{TC}}}_{{3.8}\mathrm{\;{th}}}\\{T}_{{3.8}\_ {10.8}}\geq {T}_{{3.8}\_ {10.8}\mathrm{\;{th}}}\end{array}\right.$
式(12)中:${\mathrm{{TC}}}_{{3.8}\mathrm{\;{th}}}$ 为云像元中红外亮温阈值;${T}_{{3.8}- {10.8}\mathrm{\;{th}}}$ 为云像元中红外与远红外亮温差值阈值。
步骤 2 云像元火点确认。
若潜在火点像元亮温符合下列条件, 则判定该像元为云像元火点。
${T}_{3.8}\geq {T}_{{3.8}\_ \mathrm{{bg}}}+ {\mathrm{{TC}}}_{\text{fireth }}$
式(13)中:${\mathrm{{TC}}}_{\text{fireth }}$ 为云像元火点判识阈值。
自 2022 年 3 月 FY-3E 正式运行以来, FY-3E 火点判识算法已应用于北方某省级电网输电线路山火监测预警中, 结合输电线路坐标分析火点对电网安全的威胁,多次在输电线路山火防治中起到关键作用,验证了算法的有效性,帮助运维人员及时发现火情并采取有效处置措施。针对其中两起典型威胁输电线路安全运行的山火,利用人机交互方式对 FY-3E 与 H8、GK-2A 的红外多光谱数据进行对比分析, 验证了 FY-3E 在火点探测灵敏度、空间范围精度和定位精度方面的明显优势。
2022 年 3 月 30 日 16:50, FY-3E 基于第 2 节所述的火点判识算法监测到山西省大同市天镇县火情,定位经纬度$\left({{114.0406}^{\circ }\mathrm{E},{40.4001}^{\circ }\mathrm{N}}\right)$,距最近的 220 kV GY 线 1.4 km,火点位置$3\mathrm{\;{km}}$ 内有 5 条${220}\mathrm{{kV}}$ 输电线路,火点定位与线路相对位置如图7 所示。运维人员核实现场实际火情位置距线路约${300}\mathrm{\;m}$,现场情况如图8 所示。静止气象卫星$\mathrm{H}8$ 也监测到此处火情, 但是 H8 在 17:00 才开始监测到火情,比 FY-3E 滞后 10 min。
图9 为 16:50 大同市天镇县山火 FY-3E 多通道$\left({{3.8}\text{、}{10.8}\text{、}{12.0\mu }\mathrm{m}}\right)$ 火情监测合成图。图10(a)图10(b) 分别为与图9 同一区域的${16}: {50}$${17}: {00}\mathrm{\;H}8$ 多通道$\left({{3.8}\text{、}{0.26}\text{、}{0.64\mu }\mathrm{m}}\right)$ 火情监测合成图。可以看出, 在 16:50 相同时次火情监测合成图中, FY-3E 监测到 2 个火点像元, H8 火情监测图中真实火情位置未见明显红色亮区,未监测到火情。直到下一时次 17:00 在 H8 火情监测合成图中出现一个亮红色像元, H8 开始监测到此处火情。
图11${16}: {50}- {17}: {20}$ 火场区域 FY-3E 和 H8 的${3.8\mu }\mathrm{m}$ 中红外通道亮温数据,${16}: {50}$ 时次 FY-3E 像元亮温为${322.8}\mathrm{\;K}$,与背景温差高达${27.1}\mathrm{\;K}$,远超火点判识阈值, 有效监测到火情。而同一时次 H8 像元亮温为${289.77}\mathrm{\;K}$,与背景温差只有${0.8}\mathrm{\;K}$,未达到判识阈值,漏判火情。随火势增强,之后的 17:00 和 17:10 两个时次, H8 火点位置像元温度达到 297.92 K 和 296.11 K,与背景温差分别为${8.42}\mathrm{\;K}$${6.45}\mathrm{\;K}$,达到火点判识阈值。上述火场区域火点像元亮温值及与背景亮温差数据,验证了 FY-3E 火点探测灵敏度明显优于$\mathrm{H}8$,能够提前发现较小火点,此例中 FY-3E 较静止气象卫星 H8 提前 10 min 监测到火情。
图9 中 FY-3E 监测到的 2 个火点像元覆盖面积约为$2{\mathrm{\;{km}}}^{2}$,卫星火点定位位置 (监测火区的几何中心) 与实际火情位置 (黄色十字) 距离约为${1.12}\mathrm{\;{km}}$图10(b) 中 H8 监测到 1 个火点像元, 覆盖面积约为$4{\mathrm{\;{km}}}^{2}$,卫星火点定位位置与实际火情位置偏差约为${3.25}\mathrm{\;{km}}$,定位偏差约为$\mathrm{{FY}}- 3\mathrm{E}$ 的 3 倍。表3 为此处火情 FY-3E 和 H8 具体监测信息。对比监测山火像元个数、覆盖面积和火点定位与实测火情距离等信息可以发现, FY-3E 在火点探测空间范围精度和定位精度方面都优于$\mathrm{H}8$,定位精度较$\mathrm{H}8$ 可提升 1 倍以上。
2022 年 4 月 7 日 17:50, FY-3E 基于第 2 节所述火点判识算法监测到山西省朔州市朔城区火情, 火点定位距最近的${500}\mathrm{{kV}}\mathrm{{MXI}}$ 线小于${500}\mathrm{\;m}$,如图12 所示, 现场情况如图13 所示。静止气象卫星 GK-2A 于 18:15 首次监测到此处火情,比 FY-3E 晚 25 min。
图14(a)图14(b) 分别为同一区域 FY-3E 和 GK-2A第一次监测到此处火情时次的原始${3.8\mu }\mathrm{m}$ 中红外通道图像。FY-3E 监测火点像元的面积约为$1{\mathrm{\;{km}}}^{2}$,占$\mathrm{{GK}}- 2\mathrm{\;A}$ 火点像元面积的$1/4$,火点探测空间范围精度明显优于$\mathrm{{GK}}- 2\mathrm{\;A}$,同一区域图像内包含更精细的亮温信息。
图15${17}: {50}- {18}: {25}$ 火场区域 FY-3E 和 GK-2A的中红外通道亮温数据,17:50 FY-3E 火点位置像元亮温为${312.9}\mathrm{\;K}$,与背景温差为${8.8}\mathrm{\;K}$,超出火点判识阈值, 有效监测到火情。而同一时次 (17:55) GK-2A 监测的火情区域亮温为${297.0}\mathrm{\;K}$,与背景亮温差为${5.6}\mathrm{\;K}$,未达到$\mathrm{{GK}}- 2\mathrm{\;A}$ 的判识阈值,直到${18}: {15}$ 时,亮温差才达到${6.1}\mathrm{\;K}$,超出判识阈值, 识别到火情。从火场区域中红外通道原始数据分析, FY-3E 在像元亮温绝对值及与背景亮温温差值上, 相比 GK-2A 都有明显升高, 火点探测灵敏度优于$\mathrm{{GK}}- 2\mathrm{\;A}$。此例中$\mathrm{{FY}}- 3\mathrm{E}$ 较静止气象卫星$\mathrm{{GK}}- 2\mathrm{\;A}$ 提前${25}\mathrm{\;{min}}$ 监测到火情。
近年来, 持续高温、干旱、大风等极端天气频繁出现,山火数量显著增加,提升山火监测预警能力对保障电力可靠供应具有重要意义。基于全球首颗业务化晨昏轨道气象卫星 FY-3E, 提出一种火点判识算法并将其应用于北方某省级电网输电线路山火监测预警中,得出如下结论。
(1)提出的 FY-3E 火点自动判识算法, 对红外通道数据进行太阳天顶角订正, 热红外临边订正, 消除了大太阳天顶角观测条件和卫星视角差异对红外通道探测数据准确获取带来的不利影响, 实现了复杂大气观测条件下的云信息提取和云像元火点提取,减少了火点误告警和漏告警。
(2)通过混合像元线性波谱分离方法,对FY-3E$1\mathrm{\;{km}}$ 分辨率中红外通道与静止气象卫星$\mathrm{H}8$、GK-2A$2\mathrm{\;{km}}$ 分辨率中红外通道在火点探测中的差异进行定量分析。结果表明, FY-3E 火点探测灵敏度是 H8 和 GK-2A 的约 4 倍, 能够明显提升对较小火点的探测能力。
(3)在北方某省级电网应用,验证了所提出的 FY-3E火点判识算法的有效性及其相比静止气象卫星 H8 和 GK-2A 在火点探测灵敏度、空间范围精度和定位精度的明显优势。利用 FY-3E 对输电线路附近山火进行监测预警, 能够有效提前发现火情时间,大幅提升现场查找火情效率,指导运维单位及时采取处置措施,减轻山火对电网运行的影响。
需要注意的是,虽然 FY-3E 相比 H8 和 GK-2A 具有更高的火点探测灵敏度和定位精度, 但其观测频次较低, 在对持续时间较短和快速变化的火情监测方面存在局限性, 同时无法实现像静止气象卫星一样对同一火情的连续动态监测。为了满足输电线路山火监测高精度、高时效性的要求,后续将研究 FY-3E 和 GK-2A、H8 等多源卫星数据融合的山火监测技术, 进一步提升卫星遥感山火监测预警效果。同时, 虽然提出了薄云条件下卫星判识火点的方法, 但是云层遮挡依然是造成卫星热源漏监测的主要原因。因此, 有效结合广域的卫星监测, 流动的直升机、无人机、人工巡视和固定监拍装置等多种技术手段, 实现优势互补, 是提升电网输电线路山火监测预警能力的未来方向。
  • 国家重点研发计划(2021YFC3000300)
  • 国网山西省电力公司科技项目(52053023000D)
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2025年第25卷第8期
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doi: 10.12404/j.issn.1671-1815.2403286
  • 接收时间:2024-05-06
  • 首发时间:2025-07-29
  • 出版时间:2025-03-18
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  • 收稿日期:2024-05-06
  • 修回日期:2024-12-26
基金
国家重点研发计划(2021YFC3000300)
国网山西省电力公司科技项目(52053023000D)
作者信息
    1 国网山西省电力公司 电力科学研究院 太原 030001
    2 国家卫星气象中心 北京 100081
    3 山西世纪中试电力科学技术有限公司 太原 030001

通讯作者:

*陈洁(1983—),男,汉族,浙江上虞人,硕士,高级工程师。研究方向:卫星遥感技术在自然灾害、生态环境和气候变化。E-mail: chenjie@cma.gov.cn。
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
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占总种数比例
Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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