Monitoring of post-fire forest recovery under different restoration modes based on time series Landsat data

Abstract Forest fire is a common disturbance factor, especially in boreal forests. The detection of forest disturbance and monitoring of post-fire forest recovery are crucial to both ecological research and forest management. The Greater Hinggan Mountain area of China is rich in forest resources, but also has a high incidence of forest fires. After the most serious forest fire in the history of P. R. China, three restoration modes were adopted for local forest recovery, namely artificial regeneration, natural regeneration and artificial promotion. In this study, based on time series Landsat data, we proposed to detect the disturbance and monitor the post-fire forest recovery under the three restoration modes. Disturbance Index (DI) was proven to be an effective approach for the detection and monitoring. The results indicated that the forest under natural regeneration achieved a totally different recovery process with those under the other two modes. In combination with the field survey data analysis, the availability of different remote sensing indices and applicability of the three restoration modes were evaluated and compared. It could provide significant suggestions for local post-fire forest management.

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