A Recognizing Method of Penguin Population Using UAV Images Based on Object Otiented Classification

  Objectives  Penguins are representative organisms in Antarctica. Monitoring the population and distribution of penguins is significant to study on environmental changes in Antarctica. In the past studies, due to the limitation of medium-high resolution images, the accuracy of penguin recognition is difficult to be further improved, and the existing time series analysis of penguin distribution and population is based on indirect identification method.

  Methods  The penguin island in East Antarctica was selected as the study area where the chinese antarctic scientific research team used remote sensing unmanned aerial vehicle to make aerial observations in 2017-01, 2018-01 and 2019-12, and obtained centimeter-level resolution images. Based on object-oriented classification, the shadow pixels of penguins in 3 images were extracted, the penguin habitats were marked, and the penguin population was calculated.

  Results and Conclusions  The overall accuracy is 91%, and the results show the dynamic changes of penguin population of which the distribution of penguin habitat was relatively fixed, but the number of penguins fluctuated with 1 068 pairs, 1 003 pairs and 1 081 pairs in 3 images respectively.