Is standardization needed before using scikit-learn SVM?
scikit learn does not standardize data, but it does offer utilities for you to standardize your input data yourself:
http://scikit-learn.org/stable/modules/preprocessing.html

the rule of thumb is to standardize if your data aren't related.  That is, if channel X is not a function of channel Y, you should standardize

Qualitatively, think about it this way, SVM 'creates a hyperplane' to separate data into categories; if the data are skewed too far in one axis, that will make it harder to draw a plane to separate them