Desarrollo de un método para la clasificación automatizada de imágenes Landsat 8 mediante Redes Neuronales Artificiales

Abstract

This research develop a method for the automated classification of Landsat 8 images from the integration of Artificial Neural Networks and the identification of pixels of pure classes. The exercise carried out in this research from the SEPAL platform, allowed to obtain a mosaic L8 of the study area, duly pre-processed and calibrated, automatically in minutes. This result represents a significant advance in terms of pre-processing capacity that currently exists for the management of satellite data compared to the state of the area a decade ago. This relevant advance has been possible due to the use of artificial neural networks and cross-correlation factors of the píxels of the Landsat 8 satellite platform images. Their use and differentiation of areas in remote sensing of wooded, agricultural and water areas are discussed.