Application of QuickBird imagery in fuel load estimation in the Daxinganling region, China
Sen Jin A C and Shyh-Chin Chen B
+ Author Affiliations
- Author Affiliations
A College of Forestry, Northeast Forestry University, Harbin, Heilongjiang Province, 150040, PR China.
B Pacific Southwest Research Station, USDA Forest Service, Riverside, CA 92507, USA.
C Corresponding author. Email: jins-cf@nefu.edu.cn
International Journal of Wildland Fire 21(5) 583-590 https://doi.org/10.1071/WF11018
Submitted: 31 January 2011 Accepted: 14 November 2011 Published: 25 May 2012
Abstract
A high spatial resolution QuickBird satellite image and a low spatial but high spectral resolution Landsat Thermatic Mapper image were used to linearly regress fuel loads of 70 plots with size 30 × 30 m over the Daxinganling region of north-east China. The results were compared with loads from field surveys and from regression estimations by surveyed stand characteristics. The results show that fuel loads were related to stand characteristics, such as stand mean diameter at breast height and stand height. As the QuickBird image using the shadow fraction method represented the stand characteristics well, fuel loads were well estimated from the QuickBird image. QuickBird estimations outperformed those from the lower spatial resolution Thermatic Mapper image. For many fuel classes, the QuickBird estimations were as good as those regressed from surveyed stand characteristics, and thus similar to the surveyed fine and total dead fuel loads. However, coarse fuel loads were not estimated as well using both satellite images owing to their intrinsic low association with stand characteristics. Despite this limitation in estimating coarse fuels, very-high-resolution images such as QuickBird are still valuable in estimating fine fuels, which are critically important in the practice of fire management.
Additional keywords: remote sensing, shadow fraction.
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