R: Automatization of transition detections

I need some help with my dataset, where I have to detect transition through time. I think I can built something with if_else statements but it could be very long and complicated. I am sure there's a shortcut.

My dataset looks like:

df <- tibble ("FID" = c(1,2,3,4,5),
                   "CCSC87"= c(NA, NA,"Boscos d'aciculifolis", NA, "Boscos de caducifolis"),
                   "CCSC92"= c(NA,"Boscos d'aciculifolis","Matollars",NA,"Bosquines i prats"),
                   "CCSC97"= c(NA,"Zones cremades", "Matollars","Boscos d'aciculifolis","Bosquines i prats"),
                   "CCSC02"= c(NA,"Matollars", "Matollars", "Matollars", "Bosquines i prats"),
                   "CCSC07"= c("Boscos d'escleròfil·les","Boscos d'aciculifolis",  NA,"Matollars",NA),
                   "CCSC12"= c("Matollars",NA,NA,"Boscos d'escleròfil·les",NA),
                   "CCSC17"= c("Bosquines i prats",NA,NA,NA,NA),
                   "CCSC20"= c("Boscos d'escleròfil·les", NA, NA,NA,NA))
> df
# A tibble: 5 x 9
    FID CCSC87           CCSC92           CCSC97           CCSC02       CCSC07           CCSC12           CCSC17       CCSC20          
  <dbl> <chr>            <chr>            <chr>            <chr>        <chr>            <chr>            <chr>        <chr>           
1     1 NA               NA               NA               NA           Boscos d'escler… Matollars        Bosquines i… Boscos d'escler…
2     2 NA               Boscos d'acicul… Zones cremades   Matollars    Boscos d'acicul… NA               NA           NA              
3     3 Boscos d'acicul… Matollars        Matollars        Matollars    NA               NA               NA           NA              
4     4 NA               NA               Boscos d'acicul… Matollars    Matollars        Boscos d'escler… NA           NA              
5     5 Boscos de caduc… Bosquines i pra… Bosquines i pra… Bosquines i… NA               NA               NA           NA    

As you can see I have different columns, which are Land Cover classifications, from 1987, 1992, 1997, 2002, 2007, 2012, 2017 and 2020.

For each plot (FID=1,2...) I have data from 4 columns of Land Cover, and the other columns al filled with NA's.

To simplify, my data could also be visualized like:

df <- tibble ("FID" = c(1,2,3,4,5),
                     "CCSC87"= c(NA, NA,"A", NA, "C"),
                     "CCSC92"= c(NA,"A","E",NA,"F"),
                     "CCSC97"= c(NA,"D", "E","A","F"),
                     "CCSC02"= c(NA,"E", "E", "E", "F"),
                     "CCSC07"= c("B","A",  NA,"E",NA),
                     "CCSC12"= c("E",NA,NA,"B",NA),
                     "CCSC17"= c("F",NA,NA,NA,NA),
                     "CCSC20"= c("B", NA, NA,NA,NA))
> df
# A tibble: 5 x 9
    FID CCSC87 CCSC92 CCSC97 CCSC02 CCSC07 CCSC12 CCSC17 CCSC20
  <dbl> <chr>  <chr>  <chr>  <chr>  <chr>  <chr>  <chr>  <chr> 
1     1 NA     NA     NA     NA     B      E      F      B     
2     2 NA     A      D      E      A      NA     NA     NA    
3     3 A      E      E      E      NA     NA     NA     NA    
4     4 NA     NA     A      E      E      B      NA     NA    
5     5 C      F      F      F      NA     NA     NA     NA  

What I need is to compute an extra column that tells me if the Land Cover has changed from the first year I have data to the last year. For example, in FID=1, I would like to check if CCSC07 and CCSC20 are different and if they are what is the transition.

My output should look like:

> df_done
# A tibble: 5 x 10
    FID CCSC87 CCSC92 CCSC97 CCSC02 CCSC07 CCSC12 CCSC17 CCSC20 Transition
  <dbl> <chr>  <chr>  <chr>  <chr>  <chr>  <chr>  <chr>  <chr>  <chr>     
1     1 NA     NA     NA     NA     B      E      F      B      B         
2     2 NA     A      D      E      A      NA     NA     NA     A         
3     3 A      E      E      E      NA     NA     NA     NA     AtoE      
4     4 NA     NA     A      E      E      B      NA     NA     AtoB      
5     5 C      F      F      F      NA     NA     NA     NA     CtoF