Simultaneous detection of burned areas of multiple fires in the tropics using multisensor remote-sensing data

Fires associated with recurrent El Niño events have caused severe damage to tropical peat swamp forests. Accurate quantitative information about the frequency and distribution of the burned areas is imperative to fire management but is lacking in the tropics. This article examines a novel method based on principal component analysis (PCA) of the normalized difference water index (NDWI) from multisensor data for simultaneously detecting areas burned due to multiple El Niño–related fires. The principal components of multitemporal NDWI (NDWI-PCs) were able to capture the areas burned in the 1998 and 2003 El Niño fires in NDWI-PC3 and 2, respectively. The proposed method facilitates the reduction of dimensionality in detecting the burned areas. From 22 image bands, the proposed method was able to accurately detect the burned areas of multiple fires with only three NDWI-PCs. The proposed method also shows superior performance to unsupervised classifications of the principal components of combined image bands, multitemporal NDWI, NDWI differencing and post-classification comparison methods. The results show that the 1998 El Niño fire was devastating especially to intact peat swamp forest. For degraded peat swamp forest, there was an increase in the burned area from 1998 to 2003. The proposed method offers the retrieval of accurate and reliable quantitative information on the frequency and spatial distribution of burned areas of multiple fires in the tropics. This method is also applicable to the detection of changes in general as well as the detection of vegetation changes.     

Spaceborne detection and characterization of fires during the bi-spectral infrared detection (BIRD) experimental small satellite mission (2001-2004)

Wildfires have a range of significant environmental effects with respect to both Earth's surface and atmosphere. Spaceborne remote sensing of active fires has been undertaken for more than two decades, but the bi-spectral Infrared Detection (BIRD) Experimental Small Satellite (2001-04) is the first mission dedicated to this task. This paper summarizes the experience gained during the BIRD mission, which has focused both on active fire detection and active fire characterization, in terms of quantifying effective fire temperature (T_F), effective fire area (A_F) and fire radiative power (FRP). A detailed error analysis for each parameter is undertaken, and the accuracy of FRP retrieval is shown to be significantly better than that of T_F or A_F. For key fire-affected forest, bush and savanna environments (Australia, Benin, Borneo, Brazil, Canada-US, Portugal and Siberia) BIRD data allows FRP estimation to within 30% in 75% of fires examined, and for the first time from space BIRD is able to allow estimation of fireline length, effective fireline depth and radiative fireline intensity for the more pronounced fire fronts. Some indication of the predominant combustion regime (smoldering or flaming), which has implications for the relative concentrations of emitted pollutant products, is possible through use of the T_F parameter. This experience demonstrates the advantages of the new infrared sensor technologies employed in BIRD, and offers suggestions for future fire monitoring sensors based on similar technologies.     

The impact of large-scale forest fires on atmospheric aerosol characteristics

Aerosol optical thickness and aerosol index variations, caused by large-scale forest fires in central Yakutia in 2002 were studied using remote-sensing data (Earth Observing System (EOS) Terra, Earth Probe). Total emissions of CO₂, CO, CH₄, etc., were calculated using a modelling approach and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra burned area data. A comparison of the total emissions from forest fires in central Yakutia with global fire and volcanic emissions are made. Furthermore, long-range transport events of aerosol particles during maximum activity of forest fires are examined. It was shown that forest fires have a significant impact on the lower atmosphere; in particular, aerosol plumes are noticeable at a distance of around 3000 km from the study area.     

Fire radiative energy for quantitative study of biomass burning: derivation from the BIRD experimental satellite and comparison to MODIS fire products

A major focus in global change research is to quantify the amount of gaseous and particulate pollutants emitted from terrestrial vegetation fires. Determination of the emitted radiant energy released during biomass combustion episodes (the so-called fire radiative energy or FRE) has been suggested as a new tool for determining variations in biomass combustion rates and the rate of production of atmospheric pollutants. We review the physical principals behind the remote determination of FRE and present an alternative method for its derivation via analysis of ‘fire pixel’ radiances in the middle infrared spectral region. We compare our method to the existing FRE retrieval approach used in the EOS Moderate Resolution Imaging Spectro-radiometer (MODIS) fire products, and to retrievals of FRE based on derived fire temperature and area made via the so-called Bi-spectral method. We test each FRE retrieval method using both simulated data and imagery from a new experimental space mission, the Bi-spectral InfraRed Detection (BIRD) small satellite, which has sensors specifically designed for the study of active fires. We analyse near simultaneous MODIS and BIRD data of the fires that burned around Sydney, Australia in January 2002. Despite the markedly different pixel size and spectral coverage of these sensors, where the spatial extent of the fire pixel groups detected by MODIS and BIRD are similar, the derived values of FRE for these fires agree to within ±15 %. However, in certain fires, the lower spatial resolution of MODIS appears to prevent many of the less intensely radiating fire pixels being detected as such, meaning MODIS underestimates FRE for these fires by up to 46% in comparison to BIRD. Though the FRE release of each of these low intensity fire pixels is relatively low, their comparatively large number makes their overall FRE significant. Thus, total FRE release of the Sydney fires on 5 January 2002 is estimated to be 6.5×10⁹ J s⁻¹ via BIRD but 4.0×10⁹ J s⁻¹ via MODIS. The ability of BIRD to resolve individual fire fronts further allows the first accurate calculation of ‘radiative’ fireline intensity from spaceborne measurements, providing values of 15-75 kJ s⁻¹ m⁻¹ for fire fronts that are up to 9 km in length. Finally, we analyse the effectiveness of the satellite-based FRE retrieval methods in estimating the FRE from the active flaming and smouldering components only (FRE_Active, believed to be proportional to the rate of biomass combustion), despite the sensor receiving additional radiance from the ‘cooling ground’. The MIR radiance method appears particularly strong in this regard, allowing FRE_Active to be estimated to within ±30% in the range 100-100,000 J s⁻¹ m⁻². These results provide further confidence in the ability of spaceborne missions to derive physically meaningful values of FRE that could be used to support biomass burning emissions inventories. Future comparisons between FRE derived via MODIS and those from higher spatial resolution BIRD or airborne imagery may allow the MODIS-derived FRE values to be ‘calibrated’ for any systematic underestimation. We therefore expect FRE to become an important tool for enhancing global studies of terrestrial vegetation fires with infrared remote sensing, particularly as the majority of large fires are now imaged four times per day via the MODIS instruments on the Terra and Aqua spacecraft.     

Space-borne high resolution fire remote sensing in Benin,West Africa

An experiment on high resolution remote sensing of fires was conducted in the Ouémé catchment area of Benin, West Africa using the Bi-spectral InfraRed Detection (BIRD) satellite. The high spatial resolution capability of the BIRD system allows the detection of fires with active burning areas less than a few hundred square metres in the sub-pixel domain, as well as the estimation of quantitative characteristics of these fires, such as the radiative fire energy release and (less accurately) the effective fire temperature and area.     

Analysis of forest fires in Northeast China from 2003 to 2011

Wildfires, a common disturbance in ecosystems, can be an immediate and dominant source of interannual carbon variability. In this study, we used an instantaneous Moderate Resolution Imaging Spectroradiometer (MODIS) global disturbance index algorithm to explore continuous spatiotemporal patterns of forest fires in Northeast China. The forest fires that were sensed remotely were then validated by field records. The findings suggest that the disturbance index is effective in locating forest fires in Northeast China, as evidenced by a close match with field fire records. We found that the incidence of forest fires was closely linked to extreme conditions of climate warming and drought, and more fires occurred in dry years than in wet years. Among different forest types, shrublands, mixed forest, and deciduous needleleaf forests were more prone to wildfires because of their fire regime characteristics. The study demonstrates that the algorithm was effective in detecting forest fires from 2003 to 2011 in Northeast China, providing fundamental data for forest inventory and large-scale ecological applications.     

基于无线传感器网络的森林生态系统观测试验平台构建

在长时间尺度上监测和评价森林生态过程的状态变量是当前森林生态系统观测研究的热点问题之一.针对森林生态系统观测站观测数据实时传输存储不畅、数据共享度低、数据碎片化严重、大数据分析平台建设薄弱、森林火灾实时预测预警缺乏等问题,下蜀林场综合观测试验平台结合遥感技术、涡度相关技术、样方调查技术和无线传感器网络技术实现了森林生态...     

EOS-MODIS 数据林火识别算法的验证和改进

EOS-MODIS 数据在森林火情监测中的应用研究日益受到世界各国的重视。为了获得适用于中国不同地区森林火情监测的成熟技术, 很有必要对现有MODIS 数据林火监测理论算法进行验证分析, 探讨其在中国不同地域和季节中使用时的通用性。为此, 利用中国境内9 起森林火灾事件对MODIS 数据火点识别的理论算法进行验证分析。结果显示9 起森林火灾有8 起被有效检测到, 1 起森林火情被遗漏。通过对9 起森林火点及其邻近像元的统计分析, 发现如下两个重要规则:利用火点亮温偏离统计均值3 倍标准差的关系来确定阈值, 可以避免火点的遗漏; 林火点在CH21和CH22 上的亮温值一般有CH21- CH22< 20 K, 而噪声点在两个波段上的差异却比较大。用以上规则改进的MODIS 林火热点识别算法可以检测出用来验证的全部9 起林火事件, 从而证明了改进算法的有效性和通用性。     

Detection of fire impact and vegetation recovery over tropical peat swamp forest by satellite data and ground-based NDVI instrument

Multitemporal Principal Component Analysis (MPCA) was used for processing Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper plus (ETM+) satellite images. MPCA was able to merge spectral data corresponding to TM-1996 (pre-fire in 1997), ETM-2000 (post-fire 1997 and pre-fire 2002) and ETM-2003 (post-fire in 2002), which was crucial for detecting the fire impact and vegetation recovery. Results indicate that the burnt areas of 1997 and 2002 were 89,086 ha (16.5%) and 31,859 ha (5.9%), respectively, within the study area of 540,000 ha. Satellite Pour 1’Observation de la Terre (SPOT)-VEGETATION 10-day Maximum Value Composite (MVC) data were also used and compared with Normalized Difference Vegetation Index (NDVI) from ground-based NDVI. Our research demonstrates the strong relationship between Landsat- TM/ETM+, SPOT-VEGETATION data and ground-based NDVI in identifying land-cover changes and vegetation recovery over the tropical peat swamp forest area in Central Kalimantan, Indonesia that is affected by forest fires that occurred in 1997 and 2002.     

Study of the impact of wildfire emissions,through MOPITT total CO column,at different spatial scales

The estimation of total carbon monoxide (CO) column has been identified as essential to improve our understanding of its role in the global climate system. The Earth Observing System (EOS) Science Steering Committee and the World Meteorological Organization (WMO) has suggested that a satellite-borne CO sensor, which would operate for extended periods, would be useful for that task. Measurements of Pollution in the Troposphere (MOPITT), on board the Terra spacecraft, is a correlation radiometer for estimating CO vertical profiles and total CO column in the lower atmosphere, through the thermal radiance received in the 4.7 μm spectral region. One of the main sources of CO in the atmosphere is the fires and global biomass-burning emissions that are produced when combustion is not complete, especially in the smouldering phase. This article presents a methodology based on a Fourier technique and spatial analysis in order to estimate the total CO column contribution of wildfires at three different spatial scales. First, in a seasonal study, a Mediterranean country (Spain) is selected, and the main regions affected by fire during four years in the summer season are analysed. Second, in order to estimate CO emissions at a local scale, a large fire (in Spain) and a cluster of fires (in North China) are selected. Third, for a global study at large scale and for comparing with CO and carbon dioxide (CO₂) data from Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), locations in North China, equatorial Africa, and Amazonia are selected. Results obtained show that MOPITT data are suitable to assess and to discriminate CO emissions at local spatial scales. Finally, a qualitative agreement between CO behaviour obtained by MOPITT and CO and CO₂ obtained by SCIAMACHY is found.     

Development and analysis of a 12-year daily 1-km forest fire dataset across North America from NOAA/AVHRR data

Fires in boreal and temperate forests play a significant role in the global carbon cycle. While forest fires in North America (NA) have been surveyed extensively by U.S. and Canadian forest services, most fire records are limited to seasonal statistics without information on temporal evolution and spatial expansion. Such dynamic information is crucial for modeling fire emissions. Using the daily Advanced Very High Resolution Radiometer (AVHRR) data archived from 1989 to 2000, an extensive and consistent fire product was developed across the entire NA forest regions on a daily basis at 1-km resolution. The product was generated following data calibration, geo-referencing, and the application of an active fire detection algorithm and a burned area mapping algorithm. The spatial-temporal variation of forest fire in NA is analyzed in terms of (1) annual and monthly patterns of fire occurrences in different eco-domains, (2) the influence of topographic factors (elevation zones, aspect classes, and slope classes), and (3) major forest types and eco-regions in NA. It was found that 1) among the 12 years analyzed, 1989 and 1995 were the most severe fire years in NA; 2) the majority of burning occurred during June-July and in low elevation zones (< 500 m) with gentle slopes (< 10°), except in the dry eco-domain where more fires occurred in higher elevation zones (> 2000 m); 3) most fires occurred in the polar eco-domain, sub-arctic eco-division, and in the taiga ( boreal forests), forest-tundras and open woodlands eco-provinces in the boreal forests of Canada. The tendency for multiple burns to occur increases with elevation and slope until about 2500 m elevation and 24° slope, and decreases therefore. In comparison with ground observations, the omission and commission errors are on the order of 20%.     

Detecting a moorland wildfire scar in the Peak District,UK, using synthetic aperture radar from ERS-2 and Envisat ASAR

Wildfires occur annually in UK moorland environments, especially in drought years. They can be severely damaging to the ecosystem when they burn deep into the peat, killing ground-nesting birds and releasing CO₂ into the atmosphere. Synthetic aperture radar (SAR) was evaluated for detecting the 18 April 2003 Bleaklow wildfire scar (7.4 km²). SAR’s ability to penetrate cloud is advantageous in this inherently overcast area. SAR can provide fire scar boundary information which is otherwise labour intensive to collect in the field using a global positioning system (GPS). This article evaluates the potential of SAR intensity and InSAR coherence to detect a large peat moorland wildfire scar in the Peak District of northern England. A time-series of pre-fire and post-fire ERS-2 and advanced synthetic aperture radar (ASAR) Single Look Complex (SLC) data were pre-processed using SARScape 4.2 to produce georeferenced greyscale images. SAR intensity and InSAR coherence values were analysed against Coordinate Information on the Environment (CORINE) land‐cover classes and precipitation data. SAR intensity detected burnt peat well after a precipitation event and for previous fire events within the CORINE peat bog class. For the 18 April 2003 fire event, intensity increased to 0.84 dB post-fire inside the fire scar for the peat bog class. InSAR coherence peaked post-fire for moors and heathland and natural grassland classes inside the fire scar, but peat bog exposed from previous fires was less responsive. Overall, SAR was found to be effective for detecting the Bleaklow moorland wildfire scar and monitoring wildfire scar persistence in a degraded peat landscape up to 71 days later. Heavy precipitation amplified the SAR fire scar signal, with precipitation after wildfires being typical in UK moorlands. Further work is required to disentangle the effects of fire size, topography, and less generalized land‐cover classes on SAR intensity and InSAR coherence for detecting fire scars in degraded peat moorlands.     

Satellite-based forest fire detection for fire control in boreal forests

Forest fires in large sparsely populated areas in the boreal forest zone are difficult to detect by ground based means. Satellites can be a viable source of information to augment air-borne reconnaissance. The Advanced Very High Resolution Radiometer (AVHRR) sensor aboard the National Oceanic and Atmospheric Administration (NOAA) satellites has been used to detect and map fires in the past mainly in the tropics and mainly for environmental monitoring purposes. This article describes real-time forest fire detection where the aim is to inform local fire authorities on the fire. The fire detection is based on the 3.7 mu m channel of the NOAA AVHRR sensor. In the fire detection algorithm, imaging geometry is taken into account in addition to the data from the near-infrared and thermal infrared channels. In an experiment in summer 1995, 16 fires were detected in Finland. One was a forest fire, 11 were prescribed burnings and 4 false alarms. Three of the false alarms were due to steel factories. We conclude that satellite-based fire detection for fire control is feasible in the boreal forest zone if the continuous supply of frequent middle-infrared data can be guaranteed in the future.     

Monitoring forest fires over the Indian region using Defense Meteorological Satellite Program-Operational Linescan System nighttime satellite data

Monitoring and management of forest fires is very important in countries like India where 55% of the total forest cover is prone to fires annually. The present study aims at effective monitoring of forest fires over the Indian region using Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) nighttime satellite data and to evaluate the active fire detection capabilities of the sensor. Nightly DMSP-OLS fire products were generated from February to May 2005 (peak fire season) and analyzed to study the occurrence and behavior of fires over different forest physiognomies in Indian region. Fire products generated from DMSP-OLS were validated with ground observations of fire records from state forest departments to evaluate the accuracy of fire products. Further, inter-comparison of the DMSP-OLS derived fire products with contemporary fire products from Moderate resolution Imaging Spectroradiometer (MODIS) (both daytime and nighttime products) in addition to fires and burnt areas derived from Indian Remote sensing Satellite (IRS-P6) Advanced Wide Field Sensor (AWiFS) data has been done to analyze spatial agreement of fire locations given by the above sensors.Results from the DMSP-OLS fire products (derived from February to May 2005) over Indian region showed high forest fires in southern dry deciduous forests during February-March; central Indian dry and mixed deciduous forests during March-April; northeastern tropical forests during February-April and northern pine forests during May. Spatial pattern in fires showed a typical seasonal shift in fire activity from the southern dry deciduous forests to the northern pine forests and temperate forests as the fire season progressed. Statistical evaluation of DMSP-OLS fire products with ground observations showed an over all accuracy of 98%. Comparison of DMSP-OLS derived fires with consecutive MODIS and AWiFS derived fires for individual days indicated that 69% of the fires continued from current day (DMSP-OLS pass around ∼ 7 pm to ∼ 10 pm local time) to the next day (MODIS and AWiFS pass ∼ 10:30 am local time). Comparison of DMSP-OLS derived fires with burnt areas estimated from AWiFS showed that 98% of DMSP-OLS derived fires on the current day fell within the burnt area of AWiFS on subsequent day. Since the worst forest fires are those that extend from the current to the consecutive days, DMSP-OLS derived fires provide a valuable augmentation to the fires derived from other sensors operating in daytime.     

Forest Fires Mapping and Monitoring of current and past forest fire activity from Meteosat Second Generation Data

An operational visualization tool for forest fire events monitoring (named forest fires online/offline mapping and monitoring application, and shorthanded as FOMA) is presented. It can be used in two different modes: the near real-time mode, for the online display of actual possible and probable fires, or in retrospective mode, allowing the visualization of past forest fire occurrences. The application is based on the data obtained by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Active Fire Monitoring (FIR) product, obtained from the Meteosat Second Generation (MSG) –2 satellite. The results of this tool, running in the online mode, are automatically uploaded to a web page, providing information about active and potential fires in near-real time. For further investigations, the retrospective mode allows access to processed information, in the Keyhole Markup Language (KML) format, regarding the history of occurrences of forest fires. The EUMETCast reception system is described, and the scientific basis of the FIR product is referenced. The operational implementation of the visualization tool is presented, and some results are shown, considering forest fire occurrences in Portugal, confirmed by the Portuguese Forestry Service.     

Comparison of burnt area estimates derived from satellite products and national statistics in Europe

Burnt area maps based on satellite observations are frequently used in calculations related to fire regime, such as those of carbon dioxide emissions. Nevertheless, burnt area estimates between products vary widely, and validation against independent data is scarce, especially for Europe. Here we compare two active fire maps (the ATSR World Fire Atlas and the Moderate Resolution Imaging Spectroradiometer (MODIS) Active Fire Product) and two fire scars maps (the L3JRC and the MODIS Burned Area Product) to independent national statistics taken from 22 European countries between 1997 and 2008. We also tested the coincidence between satellite products derived by calculation of the fraction of active fires that were confirmed by a subsequent drop in reflectance. As a large proportion of fire pixels (between 40% and 66%, depending on the product) is located on urban land or crop fields, filtering out fires located on these land uses greatly improves the agreement between satellite-based burnt area estimates and national statistics and it also improves the coincidence between satellite products. The MODIS Active Fire Product appears to be most suitable for use as a proxy for burnt area patterns, showing a high correlation to national statistics (R² = 0.9), relatively low spatial and temporal heterogeneity and only a slight underestimation of the total burnt area (19 000 ha year^–1). Unfiltered products show cases of substantial wildfire overestimation in all products, mainly attributable to anthropogenic activity, in the case of active fire products, and drought-induced vegetation dieback, in that of fire scar maps. Thus, filtering out fires on anthropogenic land uses seems to be essential when analysing patterns of forest fires from satellite observations. However, if agricultural fires are to be included, a combination of MODIS Active Fire and MODIS Burned Area products is recommended. We obtained that such combination shows low temporal and spatial heterogeneity and the highest coincidence between satellite products (25%), although the correlation to national statistics is not very high (R² = 0.67) and clearly underestimates the total burnt area (187 000 ha year^–1).     

Assessing two large area burnt area products across Australian Southern Forests

Burnt area is a critical parameter for estimating emissions of greenhouse gases associated with biomass burning. Several burnt area products (BAPs) derived from Earth Observation satellites/sensors have been released; these are based on different spatial resolutions and derived using different methodologies so that accuracies can vary amongst them. This study validates a global (MODIS) and a national (AVHRR) BAP across Australian southern forests using two reference datasets: state fire histories (SFHs) from 2000 to 2013 and a forest cover map derived through high resolution air photo interpretation (API). The spatial and temporal agreement between fires in the BAPs and reference SFH were analysed based on 2610 sample points representative of Australian southern forest types (successful detection was evaluated according to fire type: planned burn vs. wildfire, size of fire, and land tenure). Results show that both BAPs were most successful when identifying large wildfires (>5000 ha). Overall accuracy for AVHRR and MODIS was 73.9% and 62.5%, respectively. When compared to the API derived forest cover map as reference dataset, both products achieved higher overall accuracies (94.1% for AVHRR and 87.1% for MODIS); an expected result given that the fires detected in this dataset are known to be observable using Earth observation data. But regardless of reference dataset, the AVHRR BAP which is tailored to Australian conditions achieved better results than the MODIS global BAP. Also, the AVHRR archive in Australia goes back to 1988, which is an important consideration for calculating wildfire history for greenhouse gas accounting.     

林火巡护与扑救车载定位系统设计

针对林火发生的特点,结合我国林区现状,研究并设计了用于林火地面巡护与早期扑救的车载卫星定位系统和远程管理软件系统,结合卫星定位系统和移动互联网技术,实时精确地采集和回传灾害现场的关键信息,生成地图地形标记,为防火指挥部门提供详细准确的火灾现场数据。实验表明,该系统可以实时可靠地回传现场坐标、海拔、温度等信息,地图位置标注准确。     

A forest fire risk assessment using NOAA AVHRR images in the Valencia area,eastern Spain

The risk of widespread forest fire has been assessed from information supplied by the AVHRR sensor onboard NOAA satellites, for the area of the Autonomous Community of Valencia in eastern Spain, where several major forest fires occurred in the summer of 1994. The burnt surface data were obtained through unsupervised classification of the spectral information of the forest areas, first, from a date previous to the forest fire; and second, from a date following the fire. The methodology for the forest fire risk evaluation is based on the temporal evolution of the NDVI weekly maximum value. Actual forest fires appear to be statistically correlated with the deduced high risk forest fire areas.