  This technical report summarizes the analysis and approach on the
image-to-image translation task in the Multimodal Learning for Earth and
Environment Challenge (MultiEarth 2022). In terms of strategy optimization,
cloud classification is utilized to filter optical images with dense cloud
coverage to aid the supervised learning alike approach. The commonly used
pix2pix framework with a few optimizations is applied to build the model. A
weighted combination of mean squared error and mean absolute error is
incorporated in the loss function. As for evaluation, peak to signal ratio and
structural similarity were both considered in our preliminary analysis. Lastly,
our method achieved the second place with a final error score of 0.0412. The
results indicate great potential towards SAR-to-optical translation in remote
sensing tasks, specifically for the support of long-term environmental
monitoring and protection.
