Abstract

Forest fire as a common disturbance has an important role in the terrestrial ecosystem carbon cycling. However, the causes and impacts of longtime burned areas on carbon cycling need further exploration. In this study, we exploit Thematic Mapper (TM) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to develop a quick and efficient method for large-scale forest fire dynamic monitoring in China. Band 2, band 4, band 6, and band 7 of MOD09A1 were selected as the most sensitive bands for calculating the Normalized Difference Fire Index (NDFI) to effectively estimate fire burned area. The Convergent Cross Mapping (CCM) algorithm was used to analyze the causes of the forest fire. A trend analysis was used to explore the impacts of forest fire on Gross Primary Productivity (GPP). The results show that the burned area has an increased tendency from 2009 to 2018. Forest fire is greatly influenced by natural factors compared with human factors in China. But only 30% of the forest fire causes GPP loss. The loss is mainly concentrated in the northeast forest region. The results of this study have important theoretical significance for vegetation restoration of the burned area.

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