Multi-scale temporal characters mining for bird activities based on historical avian radar system datasets

Avian radar systems are effective for wide-area bird detection and tracking, but application significances need further exploration. Existing radar data mining methods provide long-term functionalities, but they are problematic for bird activity modelling especially in temporal domain. This paper complements this insufficiency by introducing a temporal bird activity extraction and interpretation method. The bird behaviour is quantified as the activity degree which integrates intensity and uncertainty characters with an entropy weighing algorithm. The method is applicable in multiple temporal scales. Historical radar dataset from a system deployed in an airport is adopted for verification. Temporal characters demonstrate good consistency with understandings from local observers and ornithologists. Daily commuting and roosting characters of local birds are well reflected, evening bat activities are also extracted. Night migration activities are demonstrated clearly. Results indicate the proposed method is effective in temporal bird activity modelling and interpretation. Its integration with bird strike risk models might be more useful for airport safety management with wildlife interference.