Since 1940, since Ulam and von Neumann conceived the CA (Cellular Automata) until now, they have been applied to the study of general phenomenological aspects of the world as a way of understanding the behavior of complex systems. The basic idea has been not to try to describe a complex system from 'above,' but simulating this system by interaction of cells following easy rules. In this paper we propose to use the Cellular Automata paradigm for Remote Sensing applications on multi-spectral, multi-temporal and spatial data analysis. In a first approach, we are designing two new applications which are being implemented in the Space Applications Institute (SAI) in the Global Vegetation Monitoring (GVM) unit in order to process daily NOAA-AVHRR data for detecting burnt surfaces and also land use/cover changes at global scale. The results obtained (burn scar maps and land use/cover changes maps) at global scale from daily NOAA-AVHRR images GAC -- 8 km are presented.

Date Published: 14 December 1999
PDF: 9 pages
Proc. SPIE 3871, Image and Signal Processing for Remote Sensing V, (14 December 1999); doi: 10.1117/12.373267

Published in SPIE Proceedings Vol. 3871:
Image and Signal Processing for Remote Sensing V
Sebastiano Bruno Serpico, Editor(s)