Type I SS is a sort of "sequential" SS.    I.e. for the model
    Y = X1 X2
 
- The Type I SS for X1   is the same as the total SS for the model Y=X1
 
- But the type I SS for X2  is the total SS for Y=X1 X2 minus the total SS for Y=X1, i.e. the partial SS for X2, given X1
 
 
Consider the case if the variables X1 and X2 were almost perfectly correlated (e.g. X2 is almost always equals k*X1).  Then the Type I SS for X2 in the above would be almost zero, because it would add almost no improvement to X1 in estimating Y.   And if the original model were Y=X2 X1, then it would be X1 with type I SS almost zero.
 
The type III SS for any variable is the equivalent of its type I SS IF THAT VARIABLE WERE THE LAST ONE ENTERED INTO THE MODEL.  I.e. it is the partial SS for a predictor after controlling for all the other predictors.
 
This mean that if X1 and X2 were perfectly uncorrelated, then their type I SS values would equal their type III SS values, regardless of their order in the model.