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1.
Purvee P. Joshi S. K. Singh B. P. Rathore I. M. Bahuguna Raj Kumar 《Journal of the Indian Society of Remote Sensing》2018,46(12):2107-2111
In the summer of 2016, fire broke out in the forests of Uttarakhand state. The effect of forest fire was thought to have severe impact on nearby glaciated region in terms of faster melting. It is understood that contamination and heat enhance the snowmelt, which reduces the reflectance in different part of EM spectrum. In order to assess the effect, AWiFS and IMAGER data from Resourcesat-1 and INSAT-3D, respectively, for the months of April and May of the years 2012, 2013, 2014 and 2016 were used to compare the reflectance of snow. It was observed that pre- and post-fire data of 2016 show drop in reflectance in comparison with earlier years. The change in reflectance for locations near to forest fire was significantly high in comparison with previous year images, whereas far-away locations did not show much change. This drastic drop may be attributed to deposition of black carbon on nearby locations in snow-covered area. AWS data of nearby Joshimath observatory were also analysed to avoid any anomalous change in temperature for the same duration. 相似文献
2.
本文根据林区背景的温度差异,取火场的平均温度,并在假定可以满足识别目标的信噪比的情况下,计算了机载与卫星(NOAA)遥感系统的监测能力。计算结果与实地试验基本符合。因此,利用卫星、机载和地面三个高度层次的遥感资料的相互印证与补充,并加以对照,可对森林火灾进行早期监测。 相似文献
3.
本研究以1987年5月30日接收的法国SPOT卫星标准假彩色合成影像为主要信息源,对大兴安岭阿木尔林业局火灾造成的林地损失进行了研究。文中着重介绍了面积量算方法、原理和误差;选取适量地面样地,用抽样统计和角规辅助目测方法计算蓄积损失并与二类调查结果进行比较;在影像上按火烧等级的判读结果、现地景观与烧死率─火灾的定量描述,及三者之间的一致性。结果表明,应用SPOT卫星资料,按本研究所介绍的方法进行火灾损失估计,可快速、经济地获得所需结果,并可满足精度要求。 相似文献
4.
森林火灾既严重影响森林生态系统的稳定,还威胁到人类生命财产安全。传统监测森林火灾方法,覆盖范围小,难以及时监测小面积火灾。遥感卫星能大范围精确监测火情,提高了监测方法的时效性,但使用单一卫星数据源很容易受到云雨等客观环境因素影响,降低监测的时效性。本文以四川木里藏族自治县"330森林火灾"区域为对象,开展多源卫星遥感数据对小范围火灾联合监测的研究。首先,充分挖掘高分四号高时空分辨率和中红外火烧敏感波段优势,联合烟幕、温度和植被指数时序变化确定火烧时间与位置;然后,使用Sentinel-2数据监测不同火烧区域光谱信息;接着,使用Sentinel-2数据提取dNBR(differenced Normalized Burn Ratio),提出了基于最大类间方差算法(OTSU)分步骤确定不同程度火烧迹地与面积的方法;最后,建立Sentinel-1A极化比值PR (Polarization Ratio)和NDVI之间关系,利用微波雷达突破云雨限制。结果表明:(1)高分四号联合IRS(InfraRed Scanner)和PMS(Panchromatic Multispectral Sensor)能够实时监测小范围火灾;(2)根据火点位置,确定火灾蔓延期间NDVI下降(由0.7降低至0.25),确定起火时间(3月30日);(3)火灾区域与未受灾区,以及不同类型火烧迹地之间的光谱在490—2200 nm范围存在差异;(4)基于OTSU算法自动确定阈值,确定林地损失面积41.56公顷(dNBR=0.35),精度达94.67%,提取林地过火未损失面积66.56公顷(dNBR=0.10),精度达90.94%,林地损失区域基本符合实际调查结果;(5)火灾前后极化比值由6.6 dB升高至10.8 dB,NDVI与PR经线性回归,R2=0.58,验证R2=0.50。联合多源卫星监测森林火灾,能提高森林火灾监测的时效性,避免了云雨等复杂环境的影响。研究成果能为小火点的及时识别和灾害评估提供参考,其应用可为林火应急响应提供技术支撑。 相似文献
5.
R. K. Somashekar P. Ravikumar C. N. Mohan Kumar K. L. Prakash B. C. Nagaraja 《Journal of the Indian Society of Remote Sensing》2009,37(1):37-50
The Bandipur National Park situated in the Western Ghats of Karnataka State, is one of the biodiversity hotspots of the world.
During recent years, this park has witnessed repeated fires, affecting considerable areas under vegetation. The temporal satellite
data from 1997 to 2006 have been analyzed to map the burnt areas using Remote Sensing (RS) and Geographic Information System
(GIS) techniques. The vegetation cover is moist deciduous, dry deciduous, scrub forests and teak plantation. Information on
extent of the burnt areas and the type of vegetation affected were derived forest range-wise. The fire prone regions have
been identified by integrating vegetation type/density, road and settlement network and past history of forest fire occurrence,
by assigning subjective weightage according to their fire-inducing capability or their sensitivity to fire. Comparison between
each temporal dataset in terms of the extent of burnt area was also carried out to interpret fire incidence pattern. Three
categories of fire risk regions such as Low, Moderate and High fire intensity zones were identified and it was found that
almost 40% of the study area falls under low risk zone. An evaluation of the existing fire management systems and the implication
of fire prevention programmes has been discussed, besides an assessment of causal factors for fire incidence in the park. 相似文献
6.
中国目前已形成了地面巡护、近地面监测、航空巡护和卫星监测等4级立体林火监测层次,但森林火灾仍是造成中国森林资源损失、森林生态环境安全和人身伤害的主要林业灾害。为对林火预警监测技术研究提供技术借鉴参考,本文从可燃物参数估测、烟区识别、着火点检测、森林大火燃烧动态监测、森林火烧迹地制图、森林火灾受害程度评价、森林燃烧生物量估算和火后植被恢复监测等8个方面,对中国近二十多年来开展的林火卫星遥感预警监测应用技术的研究进展、存在的技术问题和发展趋势进行了分析,并对构建服务于生态文明建设的天—空—地一体化的林火预警监测技术体系建设进行了展望。 相似文献
7.
S. Movaghati F. Samadzadegan A. Azizi 《Journal of the Indian Society of Remote Sensing》2013,41(1):21-33
Detecting fires, which are at their early stages is the first component of effective fire fighting. To date, several algorithms have been proposed to detect fire spots using remote sensing data. Nevertheless, in order to be able to accurately detect small and cool fires, which are very important at the regional scale, most of these algorithms need to be adjusted and improved. In this paper, an agent-based algorithm is presented for regional forest fire detection using bi-temporal MODIS data. The algorithm is designed to be so self-adaptive and consistent that it could be applied to the different pairs of consecutive images taken by the same satellite platform and at the same daytime. The results clearly show that compared with the MODIS contextual algorithm (version 4), the proposed method is more sensitive to small and cool forest fires in Iran. 相似文献
8.
N. Sifakis D. Paronis I. Keramitsoglou 《International Journal of Applied Earth Observation and Geoinformation》2004,5(4):305
This paper describes an operational application of AVHRR satellite imagery in combination with the satellite-based land cover database CORINE Land Cover (CLC) for the comprehensive observation and follow-up of 10000 fire outbreaks and of their consequences in Greece during summer 2000. In the first stage, we acquired and processed satellite images on a daily basis with the aim of smoke-plume tracking and fire-core detection at the national level. Imagery was acquired eight times per day and derived from all AVHRR spectral channels. In the second stage, we assessed the consequences of fire on vegetation by producing a burnt-area map on the basis of multi-annual normalised vegetation indices using AVHRR data in combination with CLC. In the third stage we used again CLC to assess the land cover of burnt areas in the entire country. The results compared successfully to available inventories for that year. Burnt area was estimated with an accuracy ranging from 88% to 95%, depending on the predominant land cover type. These results, along with the low cost and high temporal resolution of AVHRR satellite imagery, suggest that the combination of low-resolution satellite data with harmonised CLC data can be applied operationally for forest fire and post-fire assessments at the national and at a pan-European level. 相似文献
9.
利用动态阈值的森林草原火灾火点检测算法 总被引：2，自引：0，他引：2
针对传统固定阈值的森林和草原火灾火点遥感检测算法因时空环境变化而导致的火点漏检和误检问题,提出了一种综合季节、地理位置和土地覆盖类型等影响因素的时空动态阈值火点检测算法。实验结果表明,时空动态阈值火点检测算法能有效改善火点检测结果,具有时空自适应性。 相似文献
10.
A forest fire started on August 8th, 2016 in several places on Madeira Island causing damage and casualties. As of August 10th the local media had reported the death of three people, over 200 people injured, over 950 habitants evacuated, and 50 houses damaged. This study presents the preliminary results of the assessment of several spectral indices to evaluate the burn severity of Madeira fires during August 2016. These spectral indices were calculated using the new European satellite Sentinel-2A launched in June 2015. The study confirmed the advantages of several spectral indices such as Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVIreXn) using red-edge spectral bands to assess the post-fire conditions. Results showed high correlation between NDVI, GNDVI, NBR and NDVIre1n spectral indices and the analysis performed by Copernicus Emergency Management Service (EMSR175), considered as the reference truth. Regarding the red-edge spectral indices, the NDVIre1n (using band B5, 705 nm) presented better results compared with B6 (740 nm) and B7 (783 nm) bands. These preliminary results allow us to assume that Sentinel-2 will be a valuable tool for post-fire monitoring. In the future, the two twin Sentinel-2 satellites will offer global coverage of the Madeira Archipelago every five days, therefore allowing the simultaneous study of the evolution of the burnt area and reforestation information with high spatial (up to 10 m) and temporal resolution (5 days). 相似文献
11.
R. K. Somashekar B. C. Nagaraja Kavya Urs 《Journal of the Indian Society of Remote Sensing》2008,36(1):99-104
The Western Ghats constitute one of the three biodiversity hot spots in India, which is under constant threat from various
quarters. Among the several anthropogenic causes, fire is one of the important anthropogenic factor, which plays a pivotal
role in vegetation succession and ecosystem processes. It is very important to understand the ecological changes due to fire
and other anthropogenic factors for conservation and management of biodiversity. Because of its synoptic, multi-spectral and
multi-temporal nature remote sensing data can be a good source for forest fire monitoring. In the present study, an effort
has been made to monitor the burnt areas using March 2000 and 2004 IRS LISS — III data. The study revealed that an area of
2.15 km2 and 4.46 km2 was affected by fire in 2000 and 2004 respectively. Repeated drought, followed by mass flowering and dying of bamboo accelerated
the spread of fire from ground to canopy in areas with high bamboo density. 相似文献
12.
结合高分遥感和多源数据的高原湖泊流域土地利用分析 总被引：1，自引：0，他引：1
高分一号卫星是为提升我国高分辨率数据自给率自主发射的卫星,在土地利用监测方面具有重要的应用价值。将GF-1卫星影像与多源数据影像进行对比能够挖掘各数据源在土地利用动态监测方面的差异性。本文以云南省杞麓湖流域为研究区,选取最新的Sentinel-2、GF-1和Landsat 8卫星遥感影像进行土地利用分类,以第二次全国土地利用调查数据为基期数据,结合野外实地调研和土地利用转移矩阵开展土地利用现状和演变分析,得出以下结论：①杞麓湖流域的水域、建设用地、耕地和林地自中心向外呈现出圈层分布的特征,与第二次全国土地调查结果相比,水域、耕地、林地3种类型的自然景观面积减少,而建设用地和其他用地受人类活动的影响,面积大幅增加,变化主要集中在杞麓湖周边的纳古镇和河西镇。②Sentinel-2卫星影像与GF-1卫星影像均具有较高的空间分辨率,二者对土地利用变化评估的结果相近,均优于Landsat 8卫星影像,其中GF-1卫星影像具有较高的应用价值。 相似文献
13.
Sandeep Tambe M. L. Arrawatia Narpati Sharma 《Journal of the Indian Society of Remote Sensing》2011,39(4):555-564
Sikkim is a small, mountainous, Indian state (7,096 km2) located in the eastern Himalayan region. Though a global biodiversity hotspot, it has been relatively less studied. A detailed
forest type, density and change dynamics study was undertaken, using SATELLITE remote sensing data and intensive field verification.
The landscape was found to be dominated by alpine and nival ecosystems, with a large portion above the tree line, considerable
snow cover, and a sizeable area under forest cover (72%, 5,094 km2). A total of 18 landscape components including 14 vegetation classes were delineated, with the major ones being oak forest,
alpine meadow, alpine scrub, conifer forest and alder-cardamom agro-forestry. Of the 3,154 km2 of forests below the tree line, 40% were found to be dense (>40% tree canopy cover). A sizeable portion of the non dense
forests below the tree line was contributed by the degradation of oak forests, which was confirmed by change detection analysis.
However on a positive front over the past decade, ban on grazing and felling of trees in forests has been implemented. In
order to expand the extent of dense forests, further efforts are needed for the restoration of oak forests such as fire protection,
providing alternatives to firewood use, promotion of alder-cardamom agro-forestry in the private lands and protection of the
small-sized, fragmented forest patches in the subtropical belt. 相似文献
14.
森林植被碳储量的空间分布格局及其动态变化是陆地生态系统碳收支核算的基础。作为森林地上生物量的重要指示因子,森林高度的精确估算是提高森林植被碳储量估算精度的关键。现有研究已证明,由专业星载摄影测量系统获取的立体观测数据可用于森林高度提取,但光学遥感数据最大的问题是受云雨等天气因素的影响严重。区域森林地上生物量产品的生产需要充分挖掘潜在数据源。国产高分二号卫星(GF-2)虽然不是为获取立体观测数据而设计的专业星载摄影测量系统,但其获取的图像空间分辨率可达0.8 m,且具备±35°的的侧摆能力,在重复观测区域可构成异轨立体观测。本文以分别获取于2015年6月20日和2016年7月19的GF-2数据作为立体像对,其标称轨道侧摆角分别为0.00118°和20.4984°,以激光雷达数据获取的林下地形(DEM)和森林高度(CHM)为参考,对利用GF-2立体观测数据进行森林高度提取进行了研究。通过对立体处理得到的摄影测量点云的栅格化得到DSM,以激光雷达数据提供的DEM作为林下地形,得到了GF-2的CHM。结果表明GF-2提取的CHM与激光雷达CHM空间分布格局较为一致,两者之间存在明显的相关性,像素对像素的线性相关性(R2)达到0.51,均方根误差(RMSE)为3.6 m。研究结果表明,在林下地形已知的情况下,GF-2立体观测数据可用于森林高度估算。 相似文献
15.
基于遥感数据的森林火灾监测研究概述 总被引：1，自引：0，他引：1
研究和总结了遥感数据在森林火灾监测中的应用,研究对象主要是NOAA和MODIS,内容包括遥感监测火灾的原理、基于2种数据的森林火灾监测算法以及目前的研究现状。最终得出结论:MODIS数据在林火监测的准确率和定位精度等方面较NOAA卫星有较大的提高,动态监测具有较好的应用前景。 相似文献
16.
LIANG Yitong HU Jianglin LIU Liangming XIE Ping 《地球空间信息科学学报》2001,4(3):68-72
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17.
Remote sensing techniques are specially suitable to detect and to map areas affected by forest fires. In this work, Landsat 5 Thematic Mapper (TM) data has been used to study a number of forest fires that occurred in the province of Valencia (Spain) and to monitor the vegetation regeneration over burnt areas. A reference area (non‐burnt forest) was established to assess the change produced by fire. The radiance in the thermal band (10.4–12.5 μm) and the normalized difference in reflectance between near 1R (0.76–0.90 μm) and middle IR (2.08–2.35 μm) were the most suitable parameters to map burnt areas. This index can also be used for monitoring vegetation regeneration in burnt areas. About a month after the fire, the burns show temperatures of 5–6 °C higher than those found in the reference area, and the vegetation index shows negative values whereas the reference area values remain positive. The differences between the burns and the reference area for the vegetation index decrease with time as vegetation regenerates. 相似文献
18.
Biomass burning from vegetation fires is an important source of greenhouse gas emissions. In this study, we quantify biomass burning emissions from grasslands from the highly sensitive Kaziranga National Park, Assam, Northeast India. Most of the fires in the park are ‘controlled burning fires’ set by the park officials for management purposes. We evaluated the short-term impacts of fires and the resulting air pollution through integrating biomass burnt information from satellite remote sensing datasets. IRS-P6 Advanced Wide Field Sensor (AWiFS) data during March and April corresponding to dry season were evaluated to delineate the burnt areas. These burnt area estimates were then integrated with biomass data and emission factors for quantifying the greenhouse gas emissions. Results suggested that of the total study area of 37,822 ha, nearly 3163.282 ha has been burnt during March, 2005. Within one month, the burnt area increased to 7443.92 ha by April, i.e., from 8.36% to 19.68%. In total, biomass burning from the grasslands contributed to 29.65 Tg CO2, 1.19 Tg CO, 0.071 Tg NOx, 0.042 Tg CH4, 0.0625 Tg total non-methane hydrocarbons, 0.152 Tg of particulate matter, and 0.062 Tg of organic carbon and 0.008 Tg of black carbon during April. The importance of ‘fire’ as a management tool for maintaining the wildlife habitat has been highlighted in addition to some of the adverse affects of air pollution resulting from such management practices. The results from this study will be useful to forest officials as well as policy makers to undertake some sustainable forest management practices to maintain an ideal habitat for Kaziranga's wildlife. 相似文献
19.
Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models 总被引：1，自引：0，他引：1
This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km2, respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km2, respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km2. Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha?1 year?1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha?1 year?1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future. 相似文献
20.
George P. Petropoulos Charalambos Kontoes Iphigenia Keramitsoglou 《International Journal of Applied Earth Observation and Geoinformation》2011
Information on burnt area is of critical importance in many applications as for example in assessing the disturbance of natural ecosystems due to a fire or in proving important information to policy makers on the land cover changes for establishing restoration policies of fire-affected regions. Such information is commonly obtained through remote sensing image thematic classification and a wide range of classifiers have been suggested for this purpose. The objective of the present study has been to investigate the use of Support Vector Machines (SVMs) classifier combined with multispectral Landsat TM image for obtaining burnt area mapping. As a case study a typical Mediterranean landscape in Greece was used, in which occurred one of the most devastating fires during the summer of 2007. Accuracy assessment was based on the classification overall statistical accuracy results and also on comparisons of the derived burnt area estimates versus validated estimates from the Risk-EOS Burnt Scar Mapping service. Results from the implementation of the SVM using diverse kernel functions showed an average overall classification accuracy of 95.87% and a mean kappa coefficient of 0.948, with the burnt area class always clearly separable from all the other classes used in the classification scheme. Total burnt area estimate computed from the SVM was also in close agreement with that from Risk-EOS (mean difference of less than 1%). Analysis also indicated that, at least for the studied here fire, the inclusion of the two middle infrared spectral bands TM5 and TM7 of TM sensor as well as the selection of the kernel function in SVM implementation have a negligible effect in both the overall classification performance and in the delineation of total burnt area. Overall, results exemplified the appropriateness of the spatial and spectral resolution of the Landsat TM imagery combined with the SVM in obtaining rapid and cost-effective post-fire analysis. This is of considerable scientific and practical value, given the present open access to the archived and new observations from this satellite radiometer globally. 相似文献