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    杨光, 宁吉彬, 舒立福, 何诚, 邸雪颖. 黑龙江大兴安岭卫星热点预报森林火灾准确性研究[J]. 北京林业大学学报, 2017, 39(12): 1-9. DOI: 10.13332/j.1000-1522.20170147
    引用本文: 杨光, 宁吉彬, 舒立福, 何诚, 邸雪颖. 黑龙江大兴安岭卫星热点预报森林火灾准确性研究[J]. 北京林业大学学报, 2017, 39(12): 1-9. DOI: 10.13332/j.1000-1522.20170147
    YANG Guang, NING Ji-bin, SHU Li-fu, HE Cheng, DI Xue-ying. Study on the accuracy of forest fire prediction by satellite hot spots in Daxing'an Mountains of Heilongjiang, northeastern China[J]. Journal of Beijing Forestry University, 2017, 39(12): 1-9. DOI: 10.13332/j.1000-1522.20170147
    Citation: YANG Guang, NING Ji-bin, SHU Li-fu, HE Cheng, DI Xue-ying. Study on the accuracy of forest fire prediction by satellite hot spots in Daxing'an Mountains of Heilongjiang, northeastern China[J]. Journal of Beijing Forestry University, 2017, 39(12): 1-9. DOI: 10.13332/j.1000-1522.20170147

    黑龙江大兴安岭卫星热点预报森林火灾准确性研究

    Study on the accuracy of forest fire prediction by satellite hot spots in Daxing'an Mountains of Heilongjiang, northeastern China

    • 摘要: 卫星监测是现阶段我国主要森林火灾监测方法,其本质是测报地面的高温热源,利用粗分辨率的遥感数据进行林火监测时不能区分高温热源性质、精确定位火场,对于热点数据的地面核查反馈工作造成一定困难。提升热点数据处置的技术水平是森林防火研究的热点。本文基于2005—2015年黑龙江省大兴安岭林区卫星热点数据和同时期森林火灾历史资料,利用ARCGIS和统计分析,得出结论如下:1)卫星热点初判林火发生次数的准确率79.7%,不同卫星初判热源差异较大,NOAA-16、NOAA-18、NOAA-19和FY-1D的报准率均在80%左右,监测次数综合达到1 928次,占总数的2/3,是监测林火的主力卫星。2)卫星预报初判林火发生位置平均误差为5 787.9 m;不同卫星初判热源差异较大,NOAA-19和Terra预报热点的误差较小,但监测数量偏少;NOAA-15和NOAA-17的监测数量虽然较多,但其误差非常大,NOAA-15有7 064.7 m,NOAA-17达到万米以上。3)在卫星监测到的219次森林火灾和历史资料记录的165次火灾中,有147次森林火灾能够对应,卫星的多报、少报问题主要集中于呼玛县,在连续监测同一场森林火灾时,容易出现多报、少报的现象。建议在无法提高卫星性能的情况下,改进卫星图像的处理技术,完善卫星图像的判读标准,提高判读的准确性,同时完善地面核查反馈的方案,以增加核查效率,降低核查经济成本,同时基于不同卫星的性能差异,建议在进行林火监测时应以预报精确的风云系列极轨卫星为主,以性能稳定的NOAA系列卫星为辅。

       

      Abstract: Satellite monitoring is a major forest fire monitoring method at present in China, its essence is measuring and reporting the high-temperature heat source of ground. However, the coarse resolution remote sensing data can't distinguish the nature of the heat source, the fire locating is not precise, and it always make the excessive or underrated report, this can make difficult in the work of hot spot data verification. To enhance the technical level of hot spot data disposal is the research topic of forest fire protection industry. Through the data of Daxing'an Mountains satellite hot spot data and forest fire historical data from 2005 to 2015, making use of ARCGIS and statistical analysis, the conclusions were drawn as the followings: 1) Accuracy rate of satellite forest fire forecasting was 79.7%, first forecasting heat resource of varied satellites are different, the accuracy rate of NOAA-16, NOAA-18, NOAA-19 and FY-1D was all about 80%, monitoring frequency reached 1 928 times, accounted for 2/3 of the total, and they are the main satellite in forest fire monitoring. 2) The mean position error of the prediction of hot spot and the actual fire was 5 787.9 m, first forecasting heat resource of varied satellites was different, the error of NOAA-19 and Terra predicting hot spots was less, but the monitoring number was small. Although the monitoring number of NOAA-17 and NOAA-15 was more, yet the error was big, the error of NOAA-15 was 7 064.7 m, and that of NOAA-17 was more than 10 000 m. 3)Among 219 forest fires recorded from satellite and 165 fires in historical record, 147 forest fires can be recorded by satellite and historical record in the same time. The problems of multiple reports and few reports mainly concentrated in Huma County. When the satellites monitor the same forest fire, the phenomenon of overstating and missing is serious. To give advice, in the case of having no possibility to improve the performance of satellite, satellite image processing technology should be improved, also it is necessary to perfect the standards of satellite image interpretation and to improve the accuracy of interpretation. At the same time, perfecting the ground verification feedback scheme is also necessary to increase the efficiency of verification and reduce the verification cost. Based on the differences among different satellites, in forest fire monitoring, we should mainly use FY satellites which are very accurate in predicting, and the stable NOAA satellites can be used as a supplement.

       

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