Forest fuel moisture content estimation from MODIS data

Mei Zhou; Guangmeng Guo; Gary Z. Wang; Junhui Zhao

doi:10.1117/12.618947

1 September 2005 Forest fuel moisture content estimation from MODIS data

Mei Zhou, Guangmeng Guo, Gary Z. Wang, Junhui Zhao

Proceedings Volume 5884, Remote Sensing and Modeling of Ecosystems for Sustainability II; 588406 (2005) https://doi.org/10.1117/12.618947
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

Abstract

Fuel moisture content (FMC) is an important parameter in determining fire risk and fire behavior. Direct measurement of FMC in the field is very costly and time consuming. Therefore, remote sensing becomes the effective method to retrieve FMC at large scale. Short wave infrared (SWIR) band reflectance has been found negatively related to leaf water content and most of the researches are conducted at leaf level. Here SWIR and NIR (Near Infrared) bands of Moderate Resolution Imaging Spectroradiometer (MODIS) are used to retrieve FMC at canopy level in Northeast China forest. The result shows that the combination of MODIS band 7 and 2 presented the best results for FMC estimates. It is also found that forest fires prone to spread along the dryer area.

Citation Download Citation

Mei Zhou, Guangmeng Guo, Gary Z. Wang, and Junhui Zhao "Forest fuel moisture content estimation from MODIS data", Proc. SPIE 5884, Remote Sensing and Modeling of Ecosystems for Sustainability II, 588406 (1 September 2005); https://doi.org/10.1117/12.618947

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