本文選題：VIIRS　切入點(diǎn)：火點(diǎn)算法　出處：《山東科技大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：秸稈焚燒是大氣中細(xì)顆粒物的一個(gè)主要來(lái)源,不僅能夠惡化區(qū)域空氣質(zhì)量,降低大氣的能見度;而且改變生態(tài)系統(tǒng)的循環(huán),產(chǎn)生不利的健康效應(yīng)。及時(shí)準(zhǔn)確的監(jiān)測(cè)秸稈焚燒的時(shí)間和地點(diǎn),及時(shí)掌握農(nóng)民進(jìn)行秸稈焚燒的地域分布和動(dòng)態(tài)變化,對(duì)秸稈禁燒的管控工作和空氣質(zhì)量的保障起到至關(guān)重要的作用。VIIRS傳感器作為替代MODIS的下一代傳感器,其波段設(shè)置和波譜響應(yīng)在繼承MODIS優(yōu)勢(shì)的基礎(chǔ)上努力避免其不足,更為重要的是,其空間分辨率提高到375m,對(duì)于火點(diǎn)檢測(cè)具有潛在優(yōu)勢(shì)。本研究基于熱紅外遙感原理,利用VIIRS 375m數(shù)據(jù)的空間信息和波譜信息,研究基于VIIRS 375m數(shù)據(jù)的火災(zāi)火點(diǎn)檢測(cè)算法,結(jié)合算法結(jié)果,綜合衛(wèi)星數(shù)據(jù)、污染物地面監(jiān)測(cè)站點(diǎn)數(shù)據(jù)、氣溶膠地基觀測(cè)數(shù)據(jù)以及氣象數(shù)據(jù),以2016年10月份京津冀地區(qū)一次持續(xù)5天(10月12～16日)的嚴(yán)重污染過程為例,分析山東、河南、山西等周邊地區(qū)的秸稈焚燒對(duì)京津冀霾天氣的影響。結(jié)論如下:(1)基于VIIRS 375m數(shù)據(jù)的火點(diǎn)檢測(cè)算法,沿用MODIS上下文算法的思想,能夠檢測(cè)白天和夜間的生物質(zhì)燃燒和其他熱力異�，F(xiàn)象。算法彌補(bǔ)了AVHRR、MODIS數(shù)據(jù)在空間分辨率方面的不足,提高了對(duì)更小火點(diǎn)的檢測(cè)能力,同時(shí)提高了對(duì)大型火災(zāi)的動(dòng)態(tài)監(jiān)測(cè)能力。(2)本算法不僅排除了一部分河床的沙洲等可能與動(dòng)態(tài)火災(zāi)混淆的虛假火點(diǎn);還排除了浮云,沙漠等容易與候選火點(diǎn)混淆的虛假火點(diǎn);此外,還排除了工業(yè)園區(qū)的金屬屋頂、混凝土路面,水體的鏡面反射等導(dǎo)致14通道峰值的虛假火點(diǎn)。(3) 2016年10月12～16日京津冀地區(qū)持續(xù)5天d的嚴(yán)重污染過程,歸因于自然和人為因素共同作用的結(jié)果,即人為秸稈焚燒導(dǎo)致的本地污染源排放和傳輸、機(jī)動(dòng)車尾氣等本地污染物、京津冀地區(qū)的靜穩(wěn)大氣和近地面豐富的大氣水汽共同作用的結(jié)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.
【學(xué)位授予單位】：山東科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：X513;X712

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 彭立群;張強(qiáng);賀克斌;;基于調(diào)查的中國(guó)秸稈露天焚燒污染物排放清單[J];環(huán)境科學(xué)研究;2016年08期

2 宋京京;吳序鵬;夏祥鰲;;華東農(nóng)田秸稈燃燒對(duì)常州大氣環(huán)境的影響[J];氣象與環(huán)境科學(xué);2016年02期

3 郭蕊;段浩;馬翠平;趙娜;曲曉黎;郭衛(wèi)紅;張金滿;;河北中南部連續(xù)12d重霾污染天氣過程特征及影響因素分析[J];氣象;2016年05期

4 周悅;岳巖裕;李蘭;劉敏;周婷;;秸稈焚燒導(dǎo)致湖北中東部一次嚴(yán)重霾天氣過程的分析[J];氣候與環(huán)境研究;2016年02期

5 李建峰;宋宇;李蒙蒙;黃昕;;江漢平原秸稈焚燒污染物排放的估算[J];北京大學(xué)學(xué)報(bào)(自然科學(xué)版);2015年04期

6 程念亮;李云婷;張大偉;陳添;徐文帥;孫峰;董欣;;2014年10月北京市4次典型空氣重污染過程成因分析[J];環(huán)境科學(xué)研究;2015年02期

7 陶金花;王子峰;徐謙;李令軍;范萌;陶明輝;蘇林;陳良富;;北京地區(qū)顆粒物質(zhì)量消光吸濕增長(zhǎng)模型研究[J];遙感學(xué)報(bào);2015年01期

8 嚴(yán)文蓮;劉端陽(yáng);孫燕;魏建蘇;濮梅娟;;秸稈焚燒導(dǎo)致的江蘇持續(xù)霧霾天氣過程分析[J];氣候與環(huán)境研究;2014年02期

9 張人禾;李強(qiáng);張若楠;;2013年1月中國(guó)東部持續(xù)性強(qiáng)霧霾天氣產(chǎn)生的氣象條件分析[J];中國(guó)科學(xué):地球科學(xué);2014年01期

10 劉慶陽(yáng);劉艷菊;楊崢;張婷婷;張美根;鐘震宇;;北京城郊冬季一次大氣重污染過程顆粒物的污染特征[J];環(huán)境科學(xué)學(xué)報(bào);2014年01期

相關(guān)博士學(xué)位論文 前1條

1 鄧叢蕊;中國(guó)大氣氣溶膠中生物質(zhì)燃燒的源追蹤及灰霾的形成機(jī)制[D];復(fù)旦大學(xué);2011年

相關(guān)碩士學(xué)位論文 前1條

1 張為兵;基于環(huán)境一號(hào)衛(wèi)星數(shù)據(jù)的小麥秸稈焚燒點(diǎn)提取方法研究[D];南京師范大學(xué);2013年

，

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