trouble understanding roc curve

I'm not sure if I can consider three different land cover maps "classifiers" but I have several pairs of TPRs and FPRs for these 3 land cover maps which look like this.

For A(corine):

 cities        TPR           FPR

Bristol     0.6894999    0.08716076
Brussel     0.8065292    0.18621056
Amsterdam   0.8234692    0.07085285
Berlin      0.6944172    0.05507682
Manchester  0.6360882    0.11037915
...........


For B(globcover):

 cities      TPR         FPR

Bristol    0.3830600 0.02031096
Brussel    0.7203415 0.09221805
Amsterdam  0.5984948 0.03149400
Berlin     0.3902973 0.01440764
Manchester 0.7105581 0.02429963
..........


For C(grump):

 cities      TPR         FPR

Bristol    0.3830600 0.02031096
Brussel    0.7203415 0.09221805
Amsterdam  0.5984948 0.03149400
Berlin     0.3902973 0.01440764
Manchester 0.7105581 0.02429963
..........


with these datas, I plotted FPR vs TPR with a random classifier without having any threshold. And the plot looks like this:

Can it still be considered an ROC Curve or am I missing something or have I not understood what an roc curve is?

Any help is much appreciated.

Thanks!

• It looks like for any given city and classifier you can get different values of (TPR, FPR) by varying the classifier threshold. That is, each combination of classifier and city should have its own ROC curve. – James Sep 11 '15 at 17:00
• yes, so i was wondering if the above plot is correct. @James – tropicalbath Sep 16 '15 at 18:22