Visualisation of acoustic entropy index for rainforest health monitoring system

The estimation of forest health can be considered as one of the main challenges in modern biology. Some animal species, including taxa often used in biodiversity studies, produce active sounds during their social interactions or in other contexts such as mating, feeding and etc. Acoustic entropy index (H) of alpha diversity composed of two sub-indices which is the temporal entropy index (Ht) and spectral entropy index (Hf). This index shows that the animal activities are different during the sunrise and sunset. Background noise during night time is higher compared to daytime because of the non-stop sound of crickets. The high species richness will lead to a healthy forests. The composion of the species and the interaction between them can be one of the indicator for health of the forest. Most of the bird species in the forest are active during daytime. The diversity of animal in certain area also depends on the source of food such as fruits, nuts or small animal species such as insects and worms. Thus, in this work we investigate the health state of tow type of rainforest, incorporating their temporal and spatial information.