  We propose a strategy for land use classification which exploits Multiple
Kernel Learning (MKL) to automatically determine a suitable combination of a
set of features without requiring any heuristic knowledge about the
classification task. We present a novel procedure that allows MKL to achieve
good performance in the case of small training sets. Experimental results on
publicly available datasets demonstrate the feasibility of the proposed
approach.
