• DocumentCode
    410950
  • Title

    Early warning for grassland fire danger in north China using remote sensing

  • Author

    Zhou, Weiqi ; Zhou, Yi ; Wang, Shixin ; Zhao, Qing

  • Author_Institution
    Inst. of Remote Sensing Applications, Chinese Acad. of Sci., Beijing, China
  • Volume
    4
  • fYear
    2003
  • fDate
    21-25 July 2003
  • Firstpage
    2505
  • Abstract
    Grassland fires do a lot of economic and environmental damages and even raise forest fires, which causes more losses. Grasslands in north China mainly distribute in arid and semi-arid areas, fires happened frequently there. Grassland fires can be largely eliminated by early warning technology. This paper presents a multifactor Grassland Fire Danger Index (GFDI) of north China, which provides early warning for grassland fire occurrence and behavior. The GFDI was developed using remotely sensed images and weather station data. Seven basic indicators, relative humidity, temperature, wind velocity, precipitation, degree of grassland curing, fuel weight and grassland continuity were selected to calculate the GFDI. According to its value, GFDI was classified to 5 levels: low, moderate, high, very high and extreme.
  • Keywords
    fires; geographic information systems; meteorology; vegetation mapping; atmospheric temperature; degree of grassland curing; economic damage; environmental damage; fuel weight; geographic information systems; grassland continuity; grassland fire danger index; north China; precipitation; relative humidity; remote sensing images; warning technology; weather station data; wind velocity; Economic forecasting; Fires; Fuels; Geographic Information Systems; Humidity; Remote sensing; Surfaces; Temperature; Weather forecasting; Wind speed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International
  • Print_ISBN
    0-7803-7929-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.2003.1294490
  • Filename
    1294490