A novel iterative approach based on a modular neural architecture [1] is presented for the classification of SAR images of sea ice. Additionally to the local image information the algorithm uses spatial context information derived from the first iteration of the algorithm and refines it in the subsequent iterations. The modular structure of the neural network is used with the aim to capture structural features of the SAR images of sea ice in the Marginal Ice Zone.