Ftyjtk

I have Landsat data for 31 years in 6 NetCDF files.

Each files has about 4 million rows of data.

Each file has an as yet unknown number of timesteps in each

Except for the first file that I am using to write my script, which has 60 timesteps, and will be used to process all the files.

I have never used R before this wee exercise.

My task is to create one set of land only data for a statistician to work on.

How can I loop through the timesteps calculating ndwi?

I have this code working:
But it requires a lot of find/replace, copy/paste to work through the 60 timesteps and then there are 5 more files to process.

###############################################################

# Calculate ndwi for for the each timestep

###############################################################

#convert the timestep_1 for green to numeric value

green_nir_df02$t_1 <- as.numeric(as.character(green_nir_df02$t_1))

head (na.omit(green_nir_df02$t_1, 20))



#convert the timestep_1 for nir to numeric value

green_nir_df02$t_1.1 <- as.numeric(as.character(green_nir_df02$t_1.1))

head (na.omit(green_nir_df02$t_1.1, 20))



# calculate green minus nir for timestep_1

grnMinusNir_t_1 <- green_nir_df02$t_1 - green_nir_df02$t_1.1

head(grnMinusNir_t_1, 20)



# calculate green plus nir for timestep_1

grnPlusNir_t_1 <- green_nir_df02$t_1 + green_nir_df02$t_1.1

head(grnPlusNir_t_1, 20)



# calculate ndwi from greenMinusNir divided by greenPlusNir for timestep_1

ndwi_t_1 <- grnMinusNir_t_1 / grnPlusNir_t_1

head(ndwi_t_1, 20)



# write ndwi to the green_nir_df02 dataframe for timestep_1

green_nir_df02$ndwi_t_1 <- ndwi_t_1



####################################################

#convert the timestep_2 for green to numeric value

green_nir_df02$t_2 <- as.numeric(as.character(green_nir_df02$t_2))

head (na.omit(green_nir_df02$t_2, 20))



#convert the timestep_2 for nir to numeric value

green_nir_df02$t_2.1 <- as.numeric(as.character(green_nir_df02$t_2.1))

head (na.omit(green_nir_df02$t_2.1, 20))



# calculate green minus nir for timestep_2

grnMinusNir_t_2 <- green_nir_df02$t_2 - green_nir_df02$t_2.1

head(grnMinusNir_t_2, 20)



# calculate green plus nir for timestep_2

grnPlusNir_t_2 <- green_nir_df02$t_2 + green_nir_df02$t_2.1

head(grnPlusNir_t_2, 20)



# calculate ndwi from greenMinusNir divided by greenPlusNir for timestep_2

ndwi_t_2 <- grnMinusNir_t_2 / grnPlusNir_t_2

head(ndwi_t_2, 20)



# write ndwi to the green_nir_df02 dataframe for timestep_2

green_nir_df02$ndwi_t_2 <- ndwi_t_2

... etc to t_60

###############################################################

# END: Calculate ndwi for for the each timestep

###############################################################

and the next file starts at t_61 and so on

I have tried using this loop, which is not working because I can't point to the value in the column of t_1 in the dataframe rather than the value in the array of column names.

# initialize the "for" loop to calculate ndwi columns

seq <- 1:nt

i <- 0

green_t <- array(1:nt)

nir_t <- array(1:nt)

ndwi_t <- array(1:nt)

greenMinusNir <- array(1:nt)

greenPlusNir <- array(1:nt)

ndwi <- array(1:nt)

# set the value of the count

# count = nt from previous file #nt = num timesteps#THIS IS THE VALUE TO USE

count <- 0 ################################## EDIT THIS VALUE BEFORE RUNNING

# START: Loop for each timestep

# Step 1: create variable names for green, nir, ndwi

# Step 2: convert t_[i] and t_[i].1 to numeric

# Step 3: calculate green minus nir

# Step 4: calculate green plus nir

# Step 5: calculate ndwi = g-nir/g+nir

# Step 6: write ndwi to the green_nir_df02 dataframe

for(i in seq){

    # Step 1: create variable names for green, nir, ndwi

    green_t[i] <- paste("green_nir_df02$t_",count+i,sep="")

    nir_t[i] <- paste("green_nir_df02$t_",count+i,".1",sep="")

    ndwi_t[i] <- paste("green_nir_df02$ndwi_t_",count+i,sep="")

}

# initialize the "for" loop to calculate ndwi columns

seq <- 1:nt

i <- 0

for(i in seq){

    # Step 2: convert green (i.e., t_[i]) and nir (i.e., t_[i].1) to numeric

    green <- as.numeric(as.character(green_t[i]))

    ##    

    #ERROR when i=1 > green <-as.numeric(as.character("green_nir_df02$t_1"))

    ## 

    nir_t <- as.numeric(as.character(nir_t))



    # Step 3: calculate green minus nir

    greenMinusNir[i] <- green_t - nir_t



    # Step 4: calculate green plus nir

    greenPlusNir[i] <- green_t[i] + nir_t[i]



    # Step 5: calculate ndwi = g-nir/g+nir

    ndwi[i] <- greenMinusNir[i] / greenPlusNir[i]



    # Step 6: write ndwi to the green_nir_df02 dataframe ndwi timestep

    ndwi_t[i] <- ndwi[i]

    # i <- i+1

}

Sample data

            lon_lat t_1 t_2 t_60 t_1.1 t_2.1  t_60.1  ndwi_t_1   ndwi_t_2

1 -1609787.5_-2275087.5 180 216 247 80 197 192 0.3846154 0.04600484

2 -1609762.5_-2275087.5 102 252 281 80 197 227 0.1208791 0.12249443

3 -1609737.5_-2275087.5 102 216 281 80 156 227 0.1208791 0.16129032

4 -1609712.5_-2275087.5 141 216 281 80 156 227 0.2760181 0.16129032

5 -1609687.5_-2275087.5 180 181 281 80 156 227 0.3846154 0.07418398

6 -1609662.5_-2275087.5 180 216 281 80 197 227 0.3846154 0.04600484