Upscaling remote estimation on relative abundance of chengal trees in tropical rainforest using modified canopy fractional cover (mCFC) approach

Abstract

Forest degradation and deforestation is crucial to be monitored. Thus, aggressive sustainable forest management is needed. Tree species composition estimations at large spatial scale is crucial to achieve sustainable forest management and monitor forest degradation and deforestation occurrences. Thus, monitoring by using remotely sensed data would be helpful to cover large spatial extend of tropical rainforest. However, due to coarse spatial resolution the estimation of tree species composition nearly impossible due to mixing pixel problem. Nonetheless, utilizing modified Canopy Fractional Cover (mCFC) would help to overcome mixing pixels in coarse spatial resolution satellite data. Accuracy of the results suggest that mCFC is suitable to be utilized for estimating relative abundance of Chengal at large extend area.