Identification of eight bird species of Bogotá wetlands using pattern recognition and component analysis

Abstract

This paper seeks to identify eight native birds from Bogotá wetlands by recognizing the characteristics of their songs. Sounds are subjected to digital processing for sampling, normalizing, filtering, and scaling the frequency spectrum to extract the characteristics. The survey shall determine if an input file belongs to the pattern identified. According to the variables used different characterizations exist, whose performance is evaluated in terms of True and False Positives for a training group and test group. The characterization uses a combination of variables extracted by pattern recognition and Principal Component Analysis. This proposal received 90% performance in identifying and 6% of wrong recognition, being the lowest false positive rate compared to that obtained by using the methods separately. This study provides patterns of 8 species from Bogota´ wetlands. The results provide a tool for automatic identification of bird sounds, contributing to the study and conservation of vulnerable ecosystems. This helps to assess the status of endangered populations and supports strategic ecosystems monitoring