MODIS气溶胶光学厚度产品在西南地区林火检测中的应用

考虑到现有MODIS火灾检测算法易对低温火点产生漏判,通过研究MODIS C6-3 km、C5. 1-10 km AOD产品在西南地区不同区域森林火灾伴生烟羽扩散和分布的特性表征,对比火点中心32个方位、不同扩散范围下烟羽正、反方向AOD累积效应,以提高卫星遥感数据对火点的检测精度。结果表明:在西南中东部林区,MODIS C6-3 km AOD产品能较准确地表征该地区林火伴生烟羽的分布特征及扩散方向,且以火点为圆心,在3、6、9、15、24 km烟羽扩散半径内,当MODIS C6-3 km AOD累积AOD比值大于1. 55的特征半径存在时,该产品对烟羽检测有一定指示意义。在西南高山林区,基于暗像元法反演的MODIS C6-3 km AOD产品,由于算法中地表反射率的假定误差较大,且烟羽易识别为薄云,可能无法反演出有效数值,对林火伴生烟羽的检测能力较差,而深蓝算法反演的MODIS C5. 1-10 km AOD产品对伴生烟羽的检测具有一定优势。     

基于MODISL1B数据的川西高原森林火灾监测阈值研究

本文使用2009~2011年1~6月MODISL1B数据,经过云水掩膜,亮温反演,参照四川省护林防火办公室地面森林火灾观测资料,对四川省1、2季度火灾监测阈值进行了研究,提出了针对不同类型火灾监测的阈值范围,并对监测算法进行了适当修改。使用修改后的算法对2012年1~2月火灾进行了监测,精度达到87%,监测结果比MODIS14的火灾产品好。研究将监测火点与风场、土地利用数据叠加,并结合MODIS的7、2、1波段组合,提高了火点位置的准确度。     

大气气溶胶光学厚度信息在林火检测中的应用研究

由于现有MODIS火点检测算法对不同区域和不同季节的适应能力有限,因此需要关注复杂地表条件下对森林火灾伴生烟羽的识别问题,以提高明火点和低温焖烧火点的检测精度。本文基于烟羽扩散对大气气溶胶分布产生的影响,通过提取火灾区域的大气气溶胶光学厚度信息来描述区域内潜在火点的烟羽扩散特征,作为判识火点的辅助手段。利用MODIS资料,借助暗像元法通过6S模式反演了多个火点及周围区域的气溶胶光学厚度(AOD),并对明火点和低温火点在不同扩散范围和不同方位角条件下AOD的累积效应对烟羽的敏感性进行实验。结果表明,利用暗像元法反演出的AOD能明显地表征火灾伴生烟羽的分布特征,指示烟羽扩散方向及大致扩散范围。当以火点为中心,取32位方位角,扩散半径为10 km时,下风向与上风向的AOD累积效应差异最为显著,其累积值之比均10,对烟羽检测最为敏感。由此建立烟羽识别条件,为判识火点提供辅助依据,有效规避了MODIS火点检测算法对离散火点,特别是低温火点的漏判。     

利用MODIS大气廓线产品计算空气相对湿度的方法研究

森林火灾遍及全球,损失巨大。火险天气指数（FWI）是森林火灾预警和管理的有效工具。相对湿度（RH）是计算天气火险指数一个非常重要的参数。然而,由插值方法得到的RH在远离气象站点的地方往往存在很大的误差。因此,尝试利用MODIS遥感数据计算基于像元的高分辨率RH。MODIS的MOD07大气廓线产品,可以提供大气可降水量和地表气温数据。基于地面水汽压和大气可降水量的经验关系,利用MODIS数据计算了地表空气的相对湿度,平均绝对误差小于5％。结果表明,利用MODIS数据能简单而有效地计算地表空气的相对湿度,拓展了遥感技术在森林火险管理中的应用。     

EOS／MODIS卫星资料在贵州省林火监测中的应用

在森林火灾预防和扑救中,及时而准确地监测森林火灾和火环境的变化是各级防火人员最为关注的问题之一。对于大面积森林火灾,依靠地面人力和飞机监测,不但费用高,而且工作繁杂,特别是对于盲区的监测计算精度低。借助于卫星遥感和林火地理信息系统,进行计算机统计分析,可以克服这些不足,提供较为详细的森林火灾有关数据。该文介绍EOS／MODIS卫星遥感资料在贵州省森林火灾监测的应用,从理论上分析EOS／MODIS数据林火信息的识别和提取的原理及方法。     

极轨气象卫星森林火灾实时监测系统

介绍了新开发的极轨气象卫星林火实时监测系统的原理、功能及其数据处理流程.其特点是在卫星过境的同时就可处理出森林火灾信息,解决了目前同类气象卫星林火监测系统不能实时监测的问题.极轨气象卫星林火实时监测系统是由3台计算机组成的并行处理系统.该系统将火点判识的时序从模糊到确定分3步进行,并将数据接收、火点判断、火点定位、显示等的运行时序分配在3台计算机中同步运行.该系统于2005年在广州气象卫星地面站投入业务运行.与原有卫星遥感林火监测系统比较,该系统对森林火灾监测的时间可提早约30 min.     

极轨卫星云图森林火点识别方法

极轨卫星云图森林火点识别方法张玉香（山西省气象台０３０００６）引言我省森林资源贫乏，现有森林面积仅４２００万亩，覆盖率只有１７％，因此，保护好我省有限的森林资源，防止森林火灾，是关系到保护我省生态平衡的一件大事，而准确地监测森林火点和准确地判断火点位...     

EOS/MODIS遥感数据与应用前景

美国地球观测系统（EOS）的TERRA和AQUA卫星的中分辨率成像光谱仪（MODIS）具有36个波段和250－1000m地表分辨率，采取直接广播的形式下发数据，免费接收使用。MODIS遥感数据可广泛应用于地表覆盖变化、生物生产力和生态环境监测、气候预测和自然灾害监测（包括洪涝、干旱、森林草原火灾、雪灾、荒漠化）等领域。     

广西林火监测模型设计

[目的]森林火点的识别是利用气象卫星资料监测森林火灾的基础,通过研究广西林火发生特点,找出适用于广西的林火监测方法。[方法]应用亮温-植被指数法建立广西林火监测模型,实现广西林火监测。[结果]火点监测阈值不是一个绝对值,它可根据环境变化而设定对于检测火点最有效的值。[结论]在广西区内进行了试验,试验结果显示该方法适用于广西森林防火的需要,具备将森林火点从气象卫星影像中识别出来的能力。     

基于神经网络的气象卫星影像森林火点自动识别的试验研究

森林火点的识别是利用气象卫星资料监测森林火灾的基础。传统的目视解译火点识别法难以实现计算机的自动识别,神经网络技术为解决这一问题提供了新的工具。作者探讨了应用神经网络实现气象卫星影像森林火点自动识别的技术方法,并在湖北省地理范围内进行了试验。试验结果显示,经过训练的神经网络能够记忆火点的特征,具备将森林火点从气象卫星影像中识别出来的能力。与目视解译法相比,神经网络方法的精度接近目视解译法,最重要的是实现了森林火点的自动识别。     

MODIS数据在南方丘陵地区局地森林火灾面积评估中的应用研究

根据2004年的MODIS数据和森林火灾地面调查数据, 以福建省为例, 来探讨典型南方丘陵山区森林火灾发生后火灾面积大小评估的技术方法。在对火区250 m分辨率MODIS数据特征分析的基础上, 通过MODIS近红外通道反射率和归一化植被指数在火灾发生前后的散点图, 结合火区的假彩色合成影像, 利用ENVI软件的ROI处理功能建立火灾面积评估技术方法。对35起森林火灾样本进行评估, 过火面积总体估算误差为15 hm2, 结果表明, 在南方丘陵山区, 应用MODIS数据开展森林火灾面积评估, 能较好地满足业务需求。     

Sources of anthropogenic fire ignitions on the peat-swamp landscape in Kalimantan,Indonesia

Fire disturbance in many tropical forests, including peat swamps, has become more frequent and extensive in recent decades. These fires compromise a variety of ecosystem services, among which mitigating global climate change through carbon storage is particularly important for peat swamps. Indonesia holds the largest amount of tropical peat carbon globally, and mean annual CO₂ emissions from decomposition of deforested and drained peatlands and associated fires in Southeast Asia have been estimated at ∼2000 Mt y-1. A key component to understanding and therefore managing fire in the region is identifying the land use/land cover classes associated with fire ignitions. We assess the oft-asserted claim that escaped fires from oil palm concessions and smallholder farms near settlements are the primary sources of fire in a peat-swamp forest area in Central Kalimantan, Indonesia, equivalent to around a third of Kalimantan's total peat area. We use the MODIS Active Fire product from 2000 to 2010 to evaluate the fire origin and spread on the land use/land cover classes of legal, industrial oil palm concessions (the only type of legal concession in the study area), non-forest, and forest, as well as in relation to settlement proximity. We find that most fires (68–71%) originate in non-forest, compared to oil palm concessions (17%–19%), and relatively few (6–9%) are within 5 km of settlements. Moreover, most fires started within oil palm concessions and in close proximity to settlements stay within those boundaries (90% and 88%, respectively), and fires that do escape constitute only a small proportion of all fires on the landscape (2% and 1%, respectively). Similarly, a small proportion of fire detections in forest originate from oil palm concessions (2%) and within close proximity to settlements (2%). However, fire ignition density in oil palm (0.055 ignitions km⁻²) is comparable to that in non-forest (0.060 km-2 ignitions km-²), which is approximately ten times that in forest (0.006 ignitions km⁻²). Ignition density within 5 km of settlements is the highest at 0.125 ignitions km⁻². Furthermore, increased anthropogenic activity in close proximity to oil palm concessions and settlements produces a detectable pattern of fire activity. The number of ignitions decreases exponentially with distance from concessions; the number of ignitions initially increases with distance from settlements, and, around from 7.2 km, then decreases with distance from settlements. These results refute the claim that most fires originate in oil palm concessions, and that fires escaping from oil palm concessions and settlements constitute a major proportion of fires in this study region. However, there is a potential for these land use types to contribute substantially to the fire landscape if their area expands. Effective fire management in this area should therefore target not just oil palm concessions, but also non-forested, degraded areas where ignitions and fires escaping into forest are most likely to occur.     

Estimating emissions from forest fires in Thailand using MODIS active fire product and country specific data

Studies on air pollution and climate change have shown that forest fires constitute one of the major sources of atmospheric trace gases and particulate matter, especially during the dry season. However, these emissions remain difficult to quantify due to uncertainty on the extent of burned areas and deficient knowledge on the forest fire behaviours in each country. This study aims to estimate emissions from forest fires in Thailand by using the combination of the Moderate Resolution Imaging Spectroradiometer (MODIS) for active fire products and country-specific data based on prescribed burning experiments. The results indicate that 27817 fire hotspots (FHS) associated with forest fires were detected by the MODIS during 2005–2009. These FHS mainly occurred in the northern, western, and upper north-eastern parts of Thailand. Each year, the most significant fires were observed during January–May, with a peak in March. The majority of forest FHS were detected in the afternoon. According to the prescribed burning experiments, the average area of forest burned per fire event was found to fall within the range 1.09 to 12.47 ha, depending upon the terrain slope and weather conditions. The total burned area was computed at 159309 ha corresponding to the surface biomass fuel of 541515 tons dry matter. The forest fire emissions were computed at 855593 tons of CO₂, 56318 tons of CO, 3682 tons of CH₄, 108 tons of N₂O, 4928 tons of PM_2.5, 4603 tons of PM₁₀, 357 tons of BC and 2816 tons of OC.     

EOS/MODIS资料在湖北省林火监测中的应用

介绍了EOS卫星上携带的MODIS传感器的主要特点以及用MODIS资料进行林火监测的原理。根据近年来使用MODIS资料进行林火监测的应用情况,对自动判识火点所需设置的门槛值进行了分析和探索,找到了一种能快速、简便地设置ch21和ch21-ch31门槛值的方法,并通过实例证明该方法在林火监测中是可行的和有效的。     

湖南省森林火灾时空分布特征及其气象成因分析

利用湖南省2008-2017年10年森林火灾数据、卫星MODIS和VIIRS监测资料及常规气象资料,统计分析了湖南省森林火灾时空分布特征,分析结果表明：近10年湖南省森林火灾高发月份是2、3、4月, 3月最多,总次数为3800次,森林火灾在邵阳发生次数最多,郴州、长沙和永州次之。森林火灾受灾面积最大的是永州市、怀化市、邵阳市,达6800-7500公顷。重点分析了2018年2月14-19日湖南致灾严重的森林火灾过程与气象条件的关系,结果表明,森林火灾期间,气温偏高、相对湿度较小,降水量少,平均风速一般超过0.5m/s,火灾严重时段最大风速增大到6m/s左右,风向以偏东风和偏南风为主,湖南高低空受上下一致的西南风气流控制,天气形势较稳定。     

Analysis of lightning-induced forest fires in Austria

Besides human-caused fires, lightning is the major reason for forest fire ignition in Austria. In order to analyse the causes of ignition and to characterise lightning-induced forest fires, fire records were compared with the real appearance of lightning events by using the Austrian Lightning Detection and Information System for the period from 1993 to 2010. A probability was estimated for each forest fire being caused by lightning by using a decision tree and decision matrices based on flash characteristics (e.g. amplitude, time, location). It could be shown that 15 % of documented forest fires were lightning-caused. Nearly all lightning-caused fires were found during the summer months, whereas almost 40 % of all fires occurring from June to August were naturally caused. Most lightning-caused fires took place in the south and east of Austria. Lightning fires were more frequent at higher altitudes and primarily affected conifer forests. The median burned area was lower than that for anthropogenic forest fires.     

Multispectral remote sensing of biomass burning in West Africa

Remote sensing measurements provide a vauable means of determining the extent of burning areas and of estimating the overall distribution of pollutant sources (identified from experimental studies) in time and space. This distribution has to be taken into account in the boundary conditions of chemistry atmospheric models.Recent methods developed for the remote sensing of active fires in tropical or temperated forest zones, have been found to be completely inadequate for fire detection on West African savannas. In order to accurately estimate the active fire distribution in the function of different sorts of West African savannas (Sahelian, Sudanian and Guinean) and forests, a multispectral methodology has been developed based on NOAA/11-AVHRR satellite data, with the purpose of eliminating as much as possible the problems related to large surface heterogeneity, confusion and bias, produced by clouds, smoke, haze, background emissivities, etc.Unlike other methods, the results show that the multispectral method, in spite of its selectivity, provides realistic results, and does not under- or over-estimate the number of fires that can be sensed by the satellite. Consequently, this methodology is more appropriate than the simplest ones for a systematic sensing of this phenomenon.     

火灾遥感监测实例分析

选取了10个新疆火灾EOS／MODIS卫星遥感监测实例,在分析MODIS光谱数据的基础上,结合火场实况,进行了深入研究,结果表明：①由RGB 7．2．1通道合成影像可以发现火场。利用21～31通道差,可确定火场,但当中红外各通道不饱和时,则选择20～31通道差更为有效。截取MODIS光谱数据分析窗,做相应的判识则是最有效的手段。②火点判识参数（阀值）要根据气候和地理的不同来调整,灵活准确的调整参数是发现火点的关键。③将7通道、21通道数据点对点像元重合,可以判断火势当前位置和移动方向。④火灾遥感监测只能提供即时火场面积,通过截取光谱数据分析窗,计算火区像元数,即可估算即时火场面积。     

基于统计年鉴和MODIS的中国区域土地利用/覆盖变化特征研究

土地利用/覆盖变化(Land Use/Cover Change,LUCC)是影响区域气候变化不可忽略的因素,然而目前还没有十分可靠的土地利用/覆盖数据,因此其对气候变化影响的研究存在很大不确定性。基于此,利用中国统计年鉴(简称年鉴)和中分辨率成像光谱仪(MODerate-resolution Imaging Spectroradiometer,MODIS)遥感观测资料,以行政区为研究单元对3种典型土地利用/覆盖类型(森林、城市和农田)的变化进行了比较分析。结果表明:(1)2004~2011年,年鉴和MODIS森林覆盖率在中国各省(市、区)的分布和变化整体一致性较好,年鉴和MODIS数据都显示全国大部分省(市、区)份的森林覆盖率均有不同程度的增加,而仅MODIS数据中的北京、天津、吉林、黑龙江、上海、江苏森林覆盖率降低。MODIS数据能准确反映森林总体覆盖情况,由于类别精度不够,对单种森林类型及变化的描述存在较大误差。(2)年鉴表明中国东部城市建成区覆盖率及其增长远高于西部地区,黄淮海地区、东南部沿海地区城镇用地呈现加速扩张趋势,符合实际情况。但MODIS数据没有表征出中国区域近10年来的快速城市化进程,可能原因是城市面积较小,且地面地物分布复杂,受空间分辨率的限制,在离散的不集中的区域MODIS数据的土地覆盖类型分类精度较低,导致监测不到新城市的扩张。(3)MODIS农田面积和年鉴农作物播种面积、有效灌溉面积覆盖率的数值和空间分布均有较好的一致性,均是黄淮海地区覆盖率最大。但在2001~2011年,3种数据变化量的差异较大,尤其东部省(市、区)份,MODIS农田面积和年鉴有效灌溉面积增加,而年鉴农作物播种面积减少。(4)2004~2011年中国土地利用类型变化中年鉴城市建成区的变化速率最大(6.25%),其次为森林;耕地由于总量大,变化部分所占的比例较小,因而MOIDS农田及年鉴农作物播种面积和有效灌溉面积的变化速率均较小。     

Determining Effects of Area Burned and Fire Severity on Carbon Cycling and Emissions in Siberia

The Russian boreal forest contains about 25% of the global terrestrial biomass, and even a higher percentage of the carbon stored in litter and soils. Fire burns large areas annually, much of it in low-severity surface fires – but data on fire area and impacts or extent of varying fire severity are poor. Changes in land use, cover, and disturbance patterns such as those predicted by global climate change models, have the potential to greatly alter current fire regimes in boreal forests and to significantly impact global carbon budgets. The extent and global importance of fires in the boreal zone have often been greatly underestimated. For the 1998 fire season we estimate from remote sensing data that about 13.3 million ha burned in Siberia. This is about 5 times higher than estimates from the Russian Aerial Forest Protection Service (Avialesookhrana) for the same period. We estimate that fires in the Russian boreal forest in 1998 constituted some 14–20% of average annual global carbon emissions from forest fires. Average annual emissions from boreal zone forests may be equivalent to 23–39% of regional fossil fuel emissions in Canada and Russia, respectively. But the lack of accurate data and models introduces large potential errors into these estimates. Improved monitoring and understanding of the landscape extent and severity of fires and effects of fire on carbon storage, air chemistry, vegetation dynamics and structure, and forest health and productivity are essential to provide inputs into global and regional models of carbon cycling and atmospheric chemistry.