Rodriguez, Jorge and Zhang, Ce and Lizarazo, Ivan and Prieto, Flavio (2021) Automatic Detection and Mapping of Espeletia Plants from UAV Imagery. In: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. 2021 IEEE International Geoscience and Remote Sensing Symposium . IEEE, pp. 2831-2834. ISBN 9781665447621
Full text not available from this repository.Abstract
This paper proposes an automatic method for detection and mapping of Espeletia plants from aerial images acquired by UAV drone. The proposed approach integrated a computer vision for automatic extraction of training zones and tested on three well-established machine learning algorithms to detect regions belonging to Espeletia plants. The main components of the method are: (i) data capture and preprocessing; (ii) automatic extraction of training zones; and (iii) classification procedure using machine learning algorithms. Experimental results show that the method can achieve accurate detection and mapping of Espeletia plants, with up to 98.3% accuracy.