Afforestation Layer

The afforestation layer denotes the land-use changes from non-forest to the forest and creates the afforestation layer. The input_traza and output_gcbm parameters define the folder where the land-use change data is (Trazabilidad file) and the output data folder respectively.

The layer_traza parameter defines the land use data (Trazabilidad) with the Trazabilidad layer having four fields (T1, T2, T3, T4) with land use data for 4 distinct years. Initially, the LUC shapefile is read and a filter is used to identify polygons that went from non-forest to forest between T1 and T2.

After assigning the year and name of the disturbance, we assign a random year between T1 and T2 for the disturbance. We calculate the post-disturbance forest type for Bosque Mixto forest type, Matrorral Arborescente forest type including the ones without forest type which will have the regional average growth, according to the REDD+ Technical annexe.

afor_t2$Tipofor_pa <- as.character(afor_t2$T_F_06)

afor_t2$Tipofor_pa <- ifelse(afor_t2$T2 == "0403", "Bosque Mixto", as.character(afor_t2$Tipofor_pa))

afor_t2$Tipofor_pa <- ifelse(afor_t2$T2 == "0304", "Matorral Arborescente", as.character(afor_t2$Tipofor_pa))

afor_t2$Tipofor_pa <- ifelse(is.na(afor_t2$Tipofor_pa), "Promedio Regional", as.character(afor_t2$Tipofor_pa))

In a similar manner, we calculate the post-disturbance forest structure:

afor_t2$Estruc_pa <- as.character(recode(afor_t2$ID_EST_06,
                                    "01" = "Adulto",
                                    "02" = "Renoval",
                                    "03" = "Adulto Renoval",
                                    "04" = "Achaparrado"
                                      ))

afor_t2$Estruc_pa <- ifelse(afor_t2$T2 == "0403", "Bosque Mixto", as.character(afor_t2$Estruc_pa))

afor_t2$Estruc_pa <- ifelse(afor_t2$T2 == "0304", "Matorral Arborescente", as.character(afor_t2$Estruc_pa))

afor_t2$Estruc_pa <- ifelse(is.na(afor_t2$Estruc_pa), "Promedio Regional", as.character(afor_t2$Estruc_pa))

afor_t2<-afor_t2[,c("year","Perturb","Tipofor_pa","Estruc_pa")]

We will further repeat the same process with T3 and T4. Once completed, all the afforestation layers are bind together in a single file. We add the origin classier type to distinguish the afforestation forest and finally write the shapefile.