This paper focusses on various convolutional neural network architectures for the aerial cactus identification task. Our main effort is a thorough experimentation and evaluation of performance of different networks to identify columnar cactus in aerial imagery using deep learning. The dataset consisting of 21,500 images, was retrieved via a competition hosted by Kaggle and is a part of the VIGIA project.