Soft computing is a new emerging discipline rooted in a group of technologies, such as knowledge-based systems, neural networks, fuzzy set theory, probabilistic and evidential approaches, genetic algorithms, that have the common characteristic of mimicking the remarkable human ability in making decisions in an environment of uncertainty and imprecision. Encouraged by the growing interest in soft computing and by the scientific effort already developed within the remote sensing community, the International Workshop on Soft Computing in Remote Sensing Data Analysis held in Milan on December 4-5, 1995, brought together researchers and scientists engaged in related themes. Papers presented at the Workshop are grouped in this volume into four sections. The first section contains plenary lectures, the others open with two invited papers and deal with remote sensing classification by neural networks and fuzzy sets, symbolic approaches in geographic information processing, and remote sensing image analysis respectively.
Seidam - an intelligent data fusion system with case-based reasoning, D.G. Goodenough et al; soft classification and spatial-spectral mixing, R.A. Schowengerdt; information management, image analysis and image compression research in support of NASA's mission to planet Earth, J.C. Tilton et al; fuzzy logic and neural techniques integration - a review, P. Blonda and A. Bennardo; classification of remotely sensed images by the neural-network approach - an experimental comparison, S.B. Serpico et al; numeric and symbolic data fusion - a soft computing approach for remote sensing images analysis, J. Desachy; classification algorithms - where next?, G.G. Wilkinson; analysis large satellite data sets for global change studies - the case of vegetation monitoring, D. Ehrlich and J.P. Malingreau; information fusion in remote sensing image interpretation, A. Pinz et al; and other papers. (Part contents).