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Forest fire monitoring using airborne optical full spectrum remote sensing data

  • role： First author第一作者
  • Affiliation：

    Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing 100091, China

    Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China

  • Email：pangy@ifrit.ac.cn
  • Introduction：庞勇， 1976年生 ，男，研究员，研究方向为林业遥感机理模型、激光雷达信号处理及林业应用、森林碳汇计量、森林变化监测。E-mail: pangy@ifrit.ac.cn
PANG Yong12,  
  • Affiliation：

    Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing 100091, China

    Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China

JIA Wen12,  
  • Affiliation：

    Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing 100091, China

    Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China

QIN Xianlin12,  
  • Affiliation：

    Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing 100091, China

    Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China

SI Lin12,  
  • Affiliation：

    Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing 100091, China

    Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China

LIANG Xiaojun12,  
  • Affiliation：

    Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing 100091, China

    Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China

LIN Xin12,  
  • Affiliation：

    Institute of Forest Resource Information Technique, Chinese Academy of Forestry, Beijing 100091, China

    Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China

LI Zengyuan12

Resümee

Forest fire is one of the major forest disturbances, which directly affects forest ecosystem structure, carbon cycle, even global climate change. In recent years, the technical progresses of aerial platforms and onboard sensors have effectively improved the capability of airborne remote sensing to detect and monitor forest fires. As a result, many forest fire applications have been carried out with airborne data, including the forest fuel assessment, evaluation of forest fire potential and prevention, forest fire monitoring and situation evaluation during firefighting, post-fire damage assessment, ecosystem management and restoration.This paper introduces an integrated airborne remote sensing system, i.e., Chinese Academy of Forestry's LiDAR, Thermal, CCD and Hyperspectral (CAF-LiTCHy) airborne observation system. The CAF-LiTCHy airborne observation system is equipped with Light Detection and Ranging (LiDAR) scanner, thermal infrared camera, CCD camera and hyperspectral scanner and can obtain the corresponding data, simultaneously. The parameters of these sensors and the data processing scheme were described to show the advanced and scientific nature of CAF-LiTCHy airborne observation system. Moreover, the detailed “image - spectral - temperature - height” information of forest benefits the aforementioned applications. Here, the Xichang ‘3.30 Forest Fire’ in Sichuan Province was selected as a case study to test the capability of CAF-LiTCHy airborne observation system in post-fire survey and disaster assessment.The burn severity levels can be interpreted from the high spatial resolution CCD image directly. Meanwhile, the LiDAR-derived Canopy Height Model (CHM) shows the different burn severities of the canopy in spatial and vertical structural level. The vegetation indices calculated from hyperspectral image indicate that the pigment content and water content of canopy decrease simultaneously. The thermal information shows a higher temperature in high burn severity areas than other areas due to lots of charcoals from fire. Finally, with the combination of the CCD, CHM, spectral and thermal temperature information, the distribution of burn severity levels of the study area was mapped. The CAF-LiTCHy airborne observation system can obtain forest fire information and offer fire-related parameters effectively. The design of CAF-LiTCHy airborne observation system is advanced and scientific, and the acquired data are in high resolution, multiple dimensions and good geo-location consistency. The efficiency and stability for airborne data collection provide rapid response for fire events. Furthermore, the CAF-LiTCHy airborne observation system has the potential to provide support for fire prevention, fire risk forecast and early warning, firefighting decision-making, post-fire damage assessment and ecological restoration.

Schlüsselwort

remote sensing;airborne observation system;optical full spectrum remote sensing;CAF-LiTCHy;Xichang ‘3.30 Forest Fire’;burn severity;thermal image

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