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| 俄罗斯远东林区林火过程数值分类研究 | |
| 引用本文： | 陈文波,刘闯,Tomoko DOKO,王正兴.俄罗斯远东林区林火过程数值分类研究[J].资源科学,2007,29(5):190-194. |
| 作者姓名： | 陈文波 刘闯 Tomoko DOKO 王正兴 |
| 作者单位： | 1. International Institute for Geo-Information Science and Earth Observation(ITC), The Netherlands,7500 AA;中国科学院地理科学与资源研究所,北京,100101 2. 中国科学院地理科学与资源研究所,北京,100101;北京师范大学资源学院世界资源研究所,北京,100875 3. International Institute for Geo-Information Science and Earth Observation(ITC), The Netherlands,7500 AA;Keio University, Graduate School of Media and Governance, 5322 Endoh Fujisawa Kanagawa 252-8520 Japan 4. 中国科学院地理科学与资源研究所,北京,100101 |
| 基金项目： | 科技部国际科技合作计划 |
| 摘 要： | MODIS数据在当今的森林火灾监测中得到了广泛的应用,其用途大多是用来监测林火和研究林火对大气环境所产生的影响等等。而森林火灾在其燃烧的过程中是有着不同的类别,如暗火、明火、过火、火烧迹地等,不同的林火类别在其亮温上的表现是不同的。但是仅凭借亮温是不能够准确的识别林火燃烧过程的类别,还需要有植被信息来加以判读。本文对林火燃烧的过程分了五类,即明火、暗火、过火、火烧迹地和非燃地区,选取了俄罗斯远东地区的林区,利用MODIS数据的CH21和CH31热红外波段,对林火在燃烧过程中亮温数值的变化进行研究,并与植被指数和多时相数据相结合进行综合分析,最后采用监督分类和决策树分类方法进行解译分类,以便更好的辨别森林火灾在燃烧过程中的不同阶段,使其能够快速、有效的对森林火灾进行监测和控制。 |
| 关 键 词： | 森林火灾 亮温 植被指数 |
| 文章编号： | 1007-7588（2007）05-0190-05 |
| 修稿时间： | 2007-04-25 |
Quantitative Classification of Forest Fire in Far East Forest Area in Russia |
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| CHEN Wen-bo,LIU Chuang,Tomoko DOKO and WANG Zheng-xing.Quantitative Classification of Forest Fire in Far East Forest Area in Russia[J].Resources Science,2007,29(5):190-194. | |
| Authors: | CHEN Wen-bo LIU Chuang Tomoko DOKO and WANG Zheng-xing |
| Institution: | 1. International Institute for Geo-lnformation Science and Earth Observation, The Netherlands, 7500 AA ; 2. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beifing 100101, China ; 3. World Resources Research, College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China 4. Keio University, Graduate School of Media and Governance, 5322 Endoh Fujisawa Kanagawa 252-8520 Japan |
| Abstract: | MODIS is broadly used to detect forest fire because of its spatial resolution and its large coverage,and it has more bands than AVHRR and frequency.In order to support the fire rescue and quick response in forest fire,the analysis of forest fire process and identification of the fire status become more important.This paper focuses on a quantitative method to classify forest fire process.We take Far East Russia as an example to describe how the method could be applied for identifying the forest fire status and real time response.Firstly,five types of forest fire in its burning process were identified as follows: 1) The active fire was identified as the fire in visible flames;2) Hidden fire was recognized as the fire with high temperature but invisible flames.In general,hidden fire is considered to be a status before the active fire in forest burning process;3) The over fire followed the active fire,normally it keeps high temperature without visible flames,but it is different from the hidden fire in vegetation;4) The burnt surface was identified as the area which does not have high temperature and has little vegetation;5) The fifth type is unfired land.Secondly,two indicators were selected in order to identify types of forest fire process,which are brightness temperature and vegetation.After pre-processing of MODIS including bowtie deduction,the brightness temperature were calculated in each pixel based on the brightness temperature algorithm using MODIS CH21 and CH31,and the vegetation index were calculated in each pixel with the algorithm of NDVI using MODIS CH1 and CH2.Thirdly,brightness temperature and vegetation index which satisfied with certain conditions were selected to identify each type of fire process.Finally,the supervised classification and decision-tree classification methods were adopted.We classified the forest fire process in Far East Russia.In order to conduct the accurate assessment of classification system,this paper adopted time series analysis on April(22 2003),May 8 2003,and June 7 2003.This method is innovative since this is the first study to attempt to classify the fire status,which can be used for near-real time identification of the fire. Also,the method has an advantage in visualization of the forest fire process status in an effective way.From the case study of Far East Russia,brightness temperature and vegetation index from MODIS data were revealed to be suitable indicators for classification of forest fire process.Moreover,the supervised classification and a decision-tree classification method can provide the easy and simple tools to identify each of forest fire process types.The time series analysis could be a great help to understand the forest fire process. |
| Keywords: | MODIS |
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