Research communities show interest in in-situ measurements using digital
photography. We measured the body parts of Painted Storks, through a
non-invasive method, with their digital images taken under field
conditions at two different biogeographic regions of India to test the
Ecogeographic rules and sexual dimorphism. Our results show a
significant difference in the morphological measurements between the
sexes. The Nested ANOVA of the principal component scores indicated an
apparent sexual dimorphism with a substantial variation in the leg
morphology of the Painted Storks. Further, we have classified and
predicted the Painted Storks' sexes and the region from the independent
morphological variables through Machine Learning algorithms. Without the
non-invasive method, it would be almost impossible to collect
morphological measurements at a large scale from live Painted Storks
under field conditions. Besides, the non-invasive sex identification of
birds under field conditions assumes importance from animal welfare and
conservation perspective.