-
Notifications
You must be signed in to change notification settings - Fork 0
/
code1.R
27 lines (21 loc) · 1.08 KB
/
code1.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
# Load required libraries
library(raster)
library(dplyr)
library(tidyr)
# Load the two NLCD rasters for different years
raster1 <- raster("C:\\Users\\levis\\OneDrive - Baylor University\\2024\\Spring_Classes\\BioSeminar\\bio5100_lulcc\\rasters\\SA_2016.tif")
raster2 <- raster("C:\\Users\\levis\\OneDrive - Baylor University\\2024\\Spring_Classes\\BioSeminar\\bio5100_lulcc\\rasters\\SA_2019.tif")
# Extract the values of the rasters as factors
values1 <- as.factor(getValues(raster1))
values2 <- as.factor(getValues(raster2))
# Create a data frame with transitions
transition_df <- data.frame(from_class = values1, to_class = values2)
# Remove NA values (if any)
transition_df <- na.omit(transition_df)
# Count the transitions using dplyr
transition_counts <- transition_df %>%
group_by(from_class, to_class) %>%
summarise(count = n()) %>%
arrange(from_class, to_class)
# Export the transition counts to a CSV file
write.csv(transition_counts, file = "C:\\Users\\levis\\OneDrive - Baylor University\\2024\\Spring_Classes\\BioSeminar\\bio5100_lulcc\\transition_counts.csv", row.names = FALSE)