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FOREST RESOURCES WANAGEMENT ›› 2018›› Issue (1): 90-95.doi: 10.13466/j.cnki.lyzygl.2018.01.013

• Scientific Research • Previous Articles     Next Articles

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

LIU Shuchao1(), CHEN Xiaozhong2, QIN Xianlin1(), SUN Guifen1, LI Xiaotong1   

  1. 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:2017-11-30 Revised:2017-12-05 Online:2018-02-28 Published:2020-09-27
  • Contact: QIN Xianlin E-mail:liushuchao1992@163.com;noaags@ifrit.ac.cn

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.

Key words: forest fire, difference Normalized Burn Ratio, remote sensing, evaluation index, loss assessment

CLC Number: