欢迎访问林草资源研究
科学研究

内蒙古毕拉河林场森林火灾受害程度遥感评价

  • 刘树超 ,
  • 陈小中 ,
  • 覃先林 ,
  • 孙桂芬 ,
  • 李晓彤
展开
  • 1.中国林业科学研究院资源信息研究所,北京 100091
    2.四川省林业信息中心,成都 610081
刘树超(1992-),男,山东泰安人,在读硕士,主要从事光学遥感影像处理和森林火灾监测方法研究。Email:liushuchao1992@163.com

收稿日期: 2017-11-30

  修回日期: 2017-12-05

  网络出版日期: 2020-09-27

基金资助

国防科工局重大专项项目(21-Y30B05-9001-13/15);“基于数据挖掘的森林扰动信息卫星遥感监测和评价技术”;民用航天预研项目“基于多源空间数据的森林火灾综合监测技术与应用示范”

Remote Sensing Assessment of Forest Fire Damage Degree in Bilahe Forest Farm,Inner Mongolia

  • Shuchao LIU ,
  • Xiaozhong CHEN ,
  • Xianlin QIN ,
  • Guifen SUN ,
  • Xiaotong LI
Expand
  • 1. Research Institute of Forest Resources Information Technique,Chinese Academy of Forestry,Beijing 100091,China
    2. Forestry Information Center of Sichuan Province,Chengdu 610081,China

Received date: 2017-11-30

  Revised date: 2017-12-05

  Online published: 2020-09-27

摘要

为评价内蒙古毕拉河林场2017年5月2日发生的森林火灾损失情况,利用火灾发生前后的Landsat8卫星影像,计算得到两者间的差值归一化燃烧指数(dNBR),通过目视解译和数学统计相结合的方法构建森林火灾受害程度分级评价指标,对该火烧迹地受灾程度进行定量评价,并利用实地测量GPS数据和GF-2卫星数据验证受害程度的分级精度为86.39%。研究结果表明:内蒙古毕拉河林场火烧迹地的中度受害区域面积最大,为4 685.09hm2,占火烧迹地总面积的40.35%;轻度受害面积次之,为4 213.1hm2,占火烧迹地总面积的36.28%;重度受害面积为1 031.03hm2,占总面积的8.88%;未受害区域的面积最小为906.57hm2,占火烧迹地总面积的7.81%;火烧迹地内的受灾森林主要分布在中度受害区域和轻度受害区域,受灾草地主要分布在轻度受害区域。

本文引用格式

刘树超 , 陈小中 , 覃先林 , 孙桂芬 , 李晓彤 . 内蒙古毕拉河林场森林火灾受害程度遥感评价[J]. 林草资源研究, 2018 , 0(1) : 90 -95 . DOI: 10.13466/j.cnki.lyzygl.2018.01.013

Abstract

In order to evaluate the forest fire loss occurred on May 2,2017 in Bilahe Forest Form in Inner Mongolia,the Landsat8 satellite images which were pictured pro and post the fire were selected as the study data,the difference Normalized Burn Ratio(dNBR) was calculated by means of the two images.Through the combination of visual interpretation and mathematical statistics,the fire severity evaluation index was constructed.The damage of forest fire in Bilahe forest was quantitatively evaluated.By using the field survey GPS data and GF-2 satellite data to verify the damage degree of the forest fire,the grading accuracy was 86.39%.The results show that the moderate damage area is the largest in Bilahe Forest Farm in Inner Mongonlia,which is 4 685.09 hm2,accounting for 40.35% of the total burned area,followed by low damage area of 4 213.1hm2,accounting for 36.28% of the total burned area,high damage area is 1 031.03hm2,accounting for 8.88% of the total burned area,and the unburned damage area is 906.57hm2,accounting for 7.81% of the total burned area.The affected forest of the typical vegetation is mainly distributed in the moderate damage and low damage area.The affected grassland is mainly distributed in the low damage area.

参考文献

[1] 贾振虎. 中条山林区一场森林火灾的损失评估[J]. 陕西林业科技, 2017(1):35-37.
[2] Odion D C, Hanson C T. Fire severity in conifer forests of the Sierra Nevada,California[J]. Ecosystems, 2006,9(7):1177-1189.
[3] 常禹, 陈宏伟, 胡远满, 等. 林火烈度评价及其空间异质性研究进展[J]. 自然灾害学报, 2012,21(2):28-34.
[4] Key C H, Benson N C. Landscape assessment:sampling and analysis methods[C]// USDA Forest Service,Rocky Mountain Research Station General Technical Report.Ogden,Utah:United States Department of Agriculture, 2006.
[5] Maria Jose Lopez Garcia, V . Caselles . Mapping burns and natural reforestation using thematic mapper data[J]. Geocarto International, 1991,6(1):31-37.
[6] Wimberly M C, Reilly M J. Assessment of fire severity and species diversity in the Southern Appalachians using Landsat TM and ETM + imagery[J]. Remote Sensing of Environment, 2007,108:189-197.
[7] 朱曦. 基于环境减灾小卫星数据的森林火灾灾情监测方法研究[D]. 北京:中国林业科学研究院, 2013.
[8] 张春桂, 黄朝法, 潘卫华, 等. 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[J]. 应用气象学报, 2007,18(1):119-123.
[9] 张凌峰. 内蒙古毕拉河林业局森林资源现状及分布特点[J]. 内蒙古林业调查设计, 2013,36(1):52-54.
[10] 王婷婷, 李山山, 李安, 等. 基于Landsat8卫星影像的北京地区土地覆盖分类[J]. 中国图像图形学报, 2015,20(9):1275-1284.
[11] David P.Roy, Luigi Boschetti, Simon N. Trigg . Remote sensing of fire severity:assessing the performance of the normalized burn ratio[J]. IEEE Geoscience and Remote Sensing Letters, 2006,3(1):112-116
[12] 覃先林. 林火卫星遥感监测[M]. 北京: 中国林业出版社, 2016.
[13] Hoy E E, French N H F, Turetsky M R, et al. Evaluating the potential of Landsat TM/ETM + imagery for assessing fire severity in alaskan Black Spruce Forests[J]. International Journal of Wildland Fire, 2008,17:500-514.
[14] Soverel N O, Perrakis D D B, Coops N C. Estimating burn severity from Landsat dNBR and RdNBR Indices across Western Canada[J]. Remote Sensing of Environment, 2010,114(9):1896-1909.
[15] Allen J L, Sorbel B. Assessing the differenced normalized burn ratio’s ability to map burn severity in the boreal forest and tundra ecosystems of Alaska’s National Parks[J]. International Journal of Wildland Fire, 2008,17(4):463-475.
[16] Veraverbeke S, Lhermitte S, Verstraeten W W, et al. Evalution of pre/post-fire differenced spectral indices for assessing burn severity in a mediterranean environment with Landsat thematic mapper[J]. International Journal of Remote Sensing, 2011,32:3521-3537.
[17] 杨达, 吴志伟, 梁宇, 等. 林火烈度的量化指标构建[J]. 林业资源管理, 2014(6):140-145.
[18] 杨伟. 基于遥感的黑龙江流域火烧迹地及其植被恢复研究[D]. 北京:中国科学院大学, 2013.
文章导航

/