基于VIIRS数据的火点检测及秸秆焚烧对霾污染过程影响研究

发布时间：2018-03-21 06:40

本文选题：VIIRS　切入点：火点算法　出处：《山东科技大学》2017年硕士论文　论文类型：学位论文

【摘要】：秸秆焚烧是大气中细颗粒物的一个主要来源,不仅能够恶化区域空气质量,降低大气的能见度;而且改变生态系统的循环,产生不利的健康效应。及时准确的监测秸秆焚烧的时间和地点,及时掌握农民进行秸秆焚烧的地域分布和动态变化,对秸秆禁烧的管控工作和空气质量的保障起到至关重要的作用。VIIRS传感器作为替代MODIS的下一代传感器,其波段设置和波谱响应在继承MODIS优势的基础上努力避免其不足,更为重要的是,其空间分辨率提高到375m,对于火点检测具有潜在优势。本研究基于热红外遥感原理,利用VIIRS 375m数据的空间信息和波谱信息,研究基于VIIRS 375m数据的火灾火点检测算法,结合算法结果,综合卫星数据、污染物地面监测站点数据、气溶胶地基观测数据以及气象数据,以2016年10月份京津冀地区一次持续5天(10月12～16日)的严重污染过程为例,分析山东、河南、山西等周边地区的秸秆焚烧对京津冀霾天气的影响。结论如下:(1)基于VIIRS 375m数据的火点检测算法,沿用MODIS上下文算法的思想,能够检测白天和夜间的生物质燃烧和其他热力异常现象。算法弥补了AVHRR、MODIS数据在空间分辨率方面的不足,提高了对更小火点的检测能力,同时提高了对大型火灾的动态监测能力。(2)本算法不仅排除了一部分河床的沙洲等可能与动态火灾混淆的虚假火点;还排除了浮云,沙漠等容易与候选火点混淆的虚假火点;此外,还排除了工业园区的金属屋顶、混凝土路面,水体的镜面反射等导致14通道峰值的虚假火点。(3) 2016年10月12～16日京津冀地区持续5天d的严重污染过程,归因于自然和人为因素共同作用的结果,即人为秸秆焚烧导致的本地污染源排放和传输、机动车尾气等本地污染物、京津冀地区的静稳大气和近地面丰富的大气水汽共同作用的结果。
[Abstract]:Straw incineration is a major source of fine particulate matter in the atmosphere. It can not only worsen regional air quality and reduce atmospheric visibility, but also change the circulation of ecosystems. Timely and accurate monitoring of the time and place of straw burning, timely understanding of farmers' regional distribution and dynamic changes of straw burning, VIIRS sensor is the next generation sensor instead of MODIS, and its band setting and spectral response are based on inheriting the advantages of MODIS. More importantly, its spatial resolution is raised to 375m, which has potential advantages for fire detection. Based on the principle of thermal infrared remote sensing, the spatial and spectral information of VIIRS 375m data are used in this study. The fire detection algorithm based on VIIRS 375m data is studied. Combined with the results of the algorithm, the satellite data, pollutant ground monitoring station data, aerosol ground-based observation data and meteorological data are integrated. Taking the serious pollution process in Beijing-Tianjin-Hebei area on October 2016 as an example, a five-day period (October 12 ~ 16th) was used to analyze Shandong and Henan provinces. The influence of straw burning in Shanxi and other surrounding areas on the haze weather in Beijing-Tianjin-Hebei. The conclusion is as follows: (1) Fire point detection algorithm based on VIIRS 375m data, using the idea of MODIS context algorithm, It can detect biomass combustion and other thermal anomalies during day and night. The algorithm makes up for the shortage of spatial resolution of AVHRRNMODIS data and improves the ability of detecting smaller fire points. At the same time, it improves the capability of dynamic monitoring for large-scale fires.) this algorithm not only eliminates the false fire spots which may be confused with dynamic fires, such as sandbanks of some riverbeds, but also excludes the false fire spots that are easily confused with candidate fire sites such as floating clouds and deserts. In addition, the metal roof, concrete pavement and mirror reflection of the water body in the industrial park are excluded from the false fire spot of the 14-channel peak value.) from October 2016 to 16th, the serious pollution process in the Beijing-Tianjin-Hebei area lasted 5 days. Attributed to the combined effects of natural and human factors, that is, emissions and transport from local sources of pollution caused by the burning of artificial straw, local pollutants such as motor vehicle exhaust, The result of the interaction between static and stable atmosphere and abundant atmospheric water vapor near the ground in Beijing, Tianjin and Hebei.
【学位授予单位】：山东科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：X513;X712

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