I am new to R but I would like to fit a Generalized Boosted Regression Modeling (gbm) package to my data. The challenge is that my response data is categorical (I want to model land cover change). What family distribution should I use for my categorical data as the available options such as "bernoulli" , "poison" seem not to be applicable. Can anyone help?

If it is binary, then use "bernoulli". If there are more than two categories, use "multinomial". Keep in mind that, for that latter, I've had gbm hang indefinitely for some data sets. Alternatively, use C50 or xgboost which are IMO better.