Neural Networks for Interpretation of Remotely Sensed Data
Recent advances in sensor and computer technology are revolutionizing the way remotely sensed data is
collected, managed, and interpreted. The main purpose of this special issue is to provide a cross-section of the state-of-the-art in the area and to offer a thoughtful perspective on the potentials and the emerging challenges of applying ANNs to the analysis and interpretation of the new generation of remotely sensed data sets. The special issue will equally cover methodological innovations (e.g., development of new ANN architectures or modifications of existing ones, including advanced training strategies) and new applications of ANNs in EO and planetary exploration.
Edited by: Javier Plaza, Fabio Del Frate and Erzsebet Merenyi