Detection of Australian southeast forest fire using HJ satellite
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摘要: 以2009年2月发生在澳大利亚东南部的森林山火为研究对象,利用HJ-1B遥感影像识别森林山火,分析HJ-1B在林火灾害事故中的监测能力,通过对HJ-1B IRS B07设计参数及数据特点进行分析,提出适用于HJ-1B卫星林火监测的归一化火点指数(Ku)算法.研究表明:Ku值大于0.40为潜在可能的火点像元,云耀斑和地表虚假高温点是影响林火监测的主要噪声.由于HJ-1B没有获取到研究区域未着火前的影像数据,利用MODIS(Moderate-resolution Imaging Spectroradiometer)空间分辨率为250 m的通道1和通道2计算植被指数,其结果能较好的应用于HJ-1B林火监测算法中.通过对比分析HJ-1B林火监测结果和MODIS林火产品MOD14认为,HJ-1B能更好的监测出澳大利亚东南部森林火灾,反映出火灾的局部空间分布和细节特征.Abstract: By detecting forest fire happened in Australian southeast from remote sensing imagery to demonstrate the application ability of HJ-1B satellite in disaster. After analyzing the character of HJ-1B IRS B07 system parameters and data trait, a normalized forest fire index, Ku, was constructed. Pixels are potential fore fire points where Ku are greater than 0.40. Cloud dazzling points and surface high-temperature points are the main noises disturbing the fire point detection. MODIS 250m spatial resolution band 1 and band 2 were used to get normalized difference vegetation index(NDVI) for the lack of HJ-1B data earlier than the fire happened date and its results are suitable for the forest fire detection. The compare of detection results by HJ-1B and moderate-resolution imaging spectroradiometer(MODIS) fire product, MOD14, shows that HJ-1B is better than MOD14 on presenting fire spatial structure for the reason of its higher spatial resolution, 300m.
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[1] Dozier J.A method for satellite identification of surface temperature fields of sub-pixel resolution[J].Remote Sensing of Environment,1981,11:221-229 [2] Louis G,Jacqueline D.Application of the Dozier retrieval to wild fire characterization-A sensitivity analysis[J].Remote Sensing of Environment,2001,77:34-49 [3] Yoram J,Chris J.MODIS fire products .Algorithm Technical Background Document,EOS ID#2741,1998 [4] Boles S H,Verbyla D L.Comparison of three AVHRR-based fire detection algorithms for interior Alaska[J].Remote Sensing of Environment,2000,72(1):1-16 [5] 覃先林,易浩若.基于MODIS数据的林火识别方法研究[J].火灾科学,2004,13(2):83-89 Qin Xianlin,Yi Haoruo.A method to identify forest fire based on MODIS data[J].Fire Safety Science,2004,13(2):83-89(in Chinese) [6] Stroppiannad,Pinnock S,Gregoire J.The global fire production:daily fire occurrence from april 1992 to december 1993 Derived form NOAA AVHRR data [J].International Journal of Remote Sensing,2000,21:1279-1288 [7] Justicea C,Gigliob S,Owensa J.The MODIS fire products[J].Remote Sensing of Environment,2002,8(3):244-262 [8] Giglio L,Descloitres J,Justice C O,et al.An enhanced contextual fire detection algorithm for MODIS [J].Remote Sensing Environment,2003,87(2):273-282 -
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