• DocumentCode
    966363
  • Title

    Using MODIS land surface temperature to evaluate forest fire risk of northeast China

  • Author

    Guangmeng, Guo ; Mei, Zhou

  • Author_Institution
    Inst. of Geogr. Sci. & Natural Resource, Chinese Acad. of Sci., Beijing, China
  • Volume
    1
  • Issue
    2
  • fYear
    2004
  • fDate
    4/1/2004 12:00:00 AM
  • Firstpage
    98
  • Lastpage
    100
  • Abstract
    A neural network method was developed with the Moderate-resolution Imaging Spectroradiometer (MODIS) land surface temperature product as training and validation datasets, and it was used to retrieve land surface temperatures (LSTs) from direct-broadcast MODIS data in Northeast China in April and May 2003 before fire events. The result shows that LST increases as the day gets closer to the fire day, and this trend can be observed about three days before the fire day. This is similar to the result of fire potential index, so the LST can also be used to evaluate forest fire risk.
  • Keywords
    forestry; program verification; training; AD 2003 4 to 5; Northeast China; fire day; forest fire risk; land surface temperature; moderate-resolution imaging spectroradiometry; validation; Fires; Information retrieval; Land surface; Land surface temperature; MODIS; Neural networks; Ocean temperature; Remote monitoring; Sea surface; Surface morphology;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2004.826550
  • Filename
    1291390