Modeling spatially explicit fire impact on gross primary production in interior Alaska using satellite images coupled with eddy covariance

TitleModeling spatially explicit fire impact on gross primary production in interior Alaska using satellite images coupled with eddy covariance
Publication TypeJournal Article
Year of Publication2013
AuthorsHuang S.L, Liu H.P, Dahal D., Jin S.M, Welp LR, Liu J.X, Liu S.G
JournalRemote Sensing of Environment
Date Published2013/08
Type of ArticleArticle
ISBN Number0034-4257
Accession NumberWOS:000320419100015
KeywordsAlaska; canadian boreal forest; carbon balance; climate; data; ecosystem productivity; Eddy covariance; evergreen; Fire; Gross primary production; Image reconstruction; light use efficiency; needleleaf forest; net primary productivity; photosynthetically active radiation; postfire; potential evapotranspiration; production; Remote sensing; Vegetation

In interior Alaska, wildfires change gross primary production (GPP) after the initial disturbance. The impact of fires on GPP is spatially heterogeneous, which is difficult to evaluate by limited point-based comparisons or is insufficient to assess by satellite vegetation index. The direct prefire and postfire comparison is widely used, but the recovery identification may become biased due to interannual climate variability. The objective of this study is to propose a method to quantify the spatially explicit GPP change caused by fires and succession. We collected three Landsat images acquired on 13 July 2004,5 August 2004, and 6 September 2004 to examine the GPP recovery of burned area from 1987 to 2004. A prefire Landsat image acquired in 1986 was used to reconstruct satellite images assuming that the fires of 1987-2004 had not occurred. We used a light-use efficiency model to estimate the GPP. This model was driven by maximum light-use efficiency (E-max) and fraction of photosynthetically active radiation absorbed by vegetation (F-PAR). We applied this model to two scenarios (i.e., an actual postfire scenario and an assuming-no-fire scenario), where the changes in E-max and F-PAR were taken into account. The changes in E-max were represented by the change in land cover of evergreen needleleaf forest, deciduous broadleaf forest, and shrub/grass mixed, whose E-max was determined from three fire chronosequence flux towers as 1.1556, 13336, and 0.5098 gC/MJ PAR. The changes in F-PAR were inferred from NDVI change between the actual postfire NDVI and the reconstructed NDVI. After GPP quantification for July, August, and September 2004, we calculated the difference between the two scenarios in absolute and percent GPP changes. Our results showed rapid recovery of GPP post-fire with a 24% recovery immediately after burning and 43% one year later. For the fire scars with an age range of 2-17 years, the recovery rate ranged from 54% to 95%. In addition to the averaging, our approach further revealed the spatial heterogeneity of fire impact on GPP, allowing one to examine the spatially explicit GPP change caused by fires. Published by Elsevier Inc.

Short TitleRemote Sens. Environ.
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