Nothing
R/ndvi.R
In ASIP: Automated Satellite Image Processing
#' Normalized Difference Vegetation Index
#'
#' Normalized Difference Vegetation Index (NDVI). It is the most widely used satellite image derived index emphasizing on vegetation mapping.
#' This function can also be used to obtain the ground emissivity as well.
#' @param ext2crop,crop,directory Same as mentioned in \code{\link[ASIP]{arvi}}.
#' @param op_directory Specify the output directory (within double quotes). By default the input satellite image directory will be selected as the output directory.
#' @param emissivity Assign value "y" to get the emissivity of the surface as a seperate raster file.
#' @return File named ndvi_'date of satellite image acqisition'.tif in the input folder
#' @note 1. NDVI= (r_nir - r_red)/(r_nir + r_red)
#'
#' where, "r_" denotes TOA reflectance band.
#'
#' 2. Emissivity is calculated according to \href{http://www.tandfonline.com/doi/abs/10.1080/01431169308904400}{Van De Griend and Owe (1993)}.
#'
#' 3. Emissivity values will be absent on pixels with negative NDVI values. This can affect the land surface temperature results (not at-sensor brightness temperature) as well.
#' So, please review the study region and the requirements before using this function.
#'
#' 4. Other important notes are mentioned in \code{\link[ASIP]{custom.eqn}}.
#' @export
#' @references 1. \href{http://www.sciencedirect.com/science/article/pii/0034425787900381}{Huetet A R and Jackson R D (1987) Suitability of spectral indices for evaluating vegetation characteristics on arid rangelands, Remote sensing of environment, 23(2), pp:213-232. doi: 10.1016/0034-4257(87)90038-1.}
#'
#' 2. \href{http://www.tandfonline.com/doi/abs/10.1080/01431169308904400}{Van De Griend AA, Owe M (1993) On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. Int J Remote Sens 14:1119–1131. doi: 10.1080/01431169308904400}
#' @importFrom raster raster writeRaster extent mask crop
#' @importFrom utils tail
#' @examples
#' library (raster)
#' library (rgdal)
#' # Finding the path of the sample satellite image directory.
#' # User may define paths directly like "/home/ur_folder" or "C:/ur_folder"
#' path <- system.file ("TM_sample", package = "ASIP")
#' shapefil <- paste0 (path, "/test.shp")
#' ndvi (directory = path, crop = "y", ext2crop = shapefil)
# ndvi function
ndvi <- function(directory = getwd(), crop = "n", ext2crop = "none", op_directory = directory, emissivity = "n")
{
# If the directory is not set
bands <- length(list.files(directory,pattern = "*TIF"))
if (bands == 0)
stop("Define your satellite image folder path properly")
# Finding out which satellite sensor data & name of satellite image data
files <- list.files(directory)
for (i in 1:length(files))
{
file <- files[i]
broke_name <- strsplit(file, "_B1.TI")
broke_name <- broke_name[[1]]
if (utils::tail(broke_name,1) == "F")
{
sat_fold <- broke_name[1]
satellite <- substr(sat_fold,1,2)
break()
}
}
# Defining the crop extent
if (crop != "n" && crop != "y" && crop !="u" && crop != "f")
stop ("Define argument 'crop' properly. Use either n, y, f or u in double quotes. Type ?arvi in console to read more about the function")
if (crop != "n" && ext2crop == "none")
{
if (crop != "u")
stop ("Define argument 'ext2crop' properly if croppping is required, otherwise choose argument 'crop' as n in double quotes")
}
if (crop == "y" || crop == "f")
{
if (typeof (ext2crop) == "character")
{
shape <- raster::shapefile (ext2crop)
ext <- raster::extent (shape)
}
if (typeof (ext2crop) == "S4")
{
ext <- raster::extent (ext2crop)
shape <- ext2crop
}
}
# Defining folders properly
if (stringr::str_sub(op_directory) == "/")
{
op_directory <- stringr::str_sub(op_directory, start = 1L, end = -2L)
}
if (stringr::str_sub(directory) == "/")
{
directory <- stringr::str_sub(directory, start = 1L, end = -2L)
}
meta_data <- readLines(paste0(directory,"/",sat_fold,"_MTL.txt"))
count_i <- length(meta_data)
if (count_i==0){print("ERROR: MTL file not found")}
######### Landsat 8 starting###############
if (satellite=="LC")
{
if (crop == "u")
{
b5 <- raster (paste0 (directory, "/", sat_fold, "_B5.TIF"))
b4 <- raster (paste0 (directory, "/", sat_fold, "_B4.TIF"))
b3 <- raster (paste0 (directory, "/", sat_fold, "_B3.TIF"))
stak <- raster::stack(c(b5,b4,b3))
plotRGB(stak, scale = 65536)
print("Please define your extent from the map in plot preview for further processing")
print("You can click on the top left of custom subset region followed by the bottom right")
ext <- drawExtent()
}
# Extracting values from meta data
for (i in 1:count_i)
{
line <- meta_data[i]
line_splited <- strsplit(line," ")
words <- line_splited[[1]]
counts <- length(words)
for (j in 1:counts)
{
if (words[j]=="REFLECTANCE_ADD_BAND_5"){ nir_refl_add <- as.double(words[j+2])}
if (words[j]=="REFLECTANCE_MULT_BAND_5"){ nir_refl_mult <- as.double(words[j+2])}
if (words[j]=="REFLECTANCE_ADD_BAND_4"){ red_refl_add <- as.double(words[j+2])}
if (words[j]=="REFLECTANCE_MULT_BAND_4"){ red_refl_mult <- as.double(words[j+2])}
if (words[j]=="DATE_ACQUIRED"){ data_aq <- as.character(words[j+2])}
if (words[j]=="SUN_ELEVATION"){ sun_ele <- as.double(words[j+2])}
}
}
nir <- as.integer(raster(paste0(directory,"/",sat_fold,"_B5.TIF")))
if (crop == "y" || crop == "f" || crop == "u")
{
nir <- crop(nir, ext)
if (crop=="f")
{
nir <- mask(nir,shape)
}
}
toa_nir <- ((nir * nir_refl_mult) + nir_refl_add)/sin(sun_ele*(pi/180))
red <- as.integer(raster(paste0(directory,"/",sat_fold,"_B4.TIF")))
if (crop == "y" || crop == "f" || crop == "u")
{
red <- crop(red, ext)
if (crop=="f")
{
red <- mask(red,shape)
}
}
toa_red <- ((red * red_refl_mult) + red_refl_add)/sin(sun_ele*(pi/180))
}
########### Landsat-8 ending ##############
########### Landsat-7 starting ##############
if (satellite=="LE")
{
if (crop == "u")
{
b4 <- raster (paste0 (directory, "/", sat_fold, "_B4.TIF"))
b3 <- raster (paste0 (directory, "/", sat_fold, "_B3.TIF"))
b2 <- raster (paste0 (directory, "/", sat_fold, "_B2.TIF"))
stak <- stack(c (b4, b3, b2))
plotRGB(stak)
print("Please define your extent from the map in plot preview for further processing")
print("You can click on the top left of custom subset region followed by the bottom right")
ext <- drawExtent()
}
qcal_max <- 255
d <- 0
for (i in 1:count_i)
{
line <- meta_data[i]
line_splited <- strsplit(line," ")
words <- line_splited[[1]]
counts <- length(words)
for (j in 1:counts)
{
if (words[j]=="QUANTIZE_CAL_MIN_BAND_1"){ qcal_min <- as.double(words[j+2])}
if (words[j]=="EARTH_SUN_DISTANCE"){ d <- as.double(words[j+2])}
if (words[j]=="DATE_ACQUIRED"){ data_aq <- as.character(words[j+2])}
if (words[j]=="SUN_ELEVATION"){ sun_ele <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MAXIMUM_BAND_3"){ lmax3 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MAXIMUM_BAND_4"){ lmax4 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MINIMUM_BAND_3"){ lmin3 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MINIMUM_BAND_4"){ lmin4 <- as.double(words[j+2])}
}
}
if (d==0)
{
dat_tex <- as.Date(data_aq)
jul_ful <- julian(dat_tex)
yr_rmv_num <- jul_ful%/%365.25
jul_day <- jul_ful-(yr_rmv_num*365.25)+1.5
jul_flot <- jul_day%%365.25
jul_final <- as.integer(jul_flot)
d <- 1 + (0.0167 * sin ((pi/180) *2 *pi *(jul_final- 93.5) / 365))
}
red <- raster(paste0(directory,"/",sat_fold,"_B3.TIF"))
if (crop == "y" || crop == "f" || crop == "u")
{
red <- crop(red,ext)
if (crop=="f")
{
red <- mask(red,shape)
}
}
rad_b3 <- ((lmax3-lmin3)/(qcal_max-qcal_min)) * (red-qcal_min) + lmin3
toa_red <- pi * rad_b3 * d^2 / 1547 * sin(sun_ele*(pi/180))
nir <- raster(paste0(directory,"/",sat_fold,"_B4.TIF"))
if (crop == "y" || crop == "f" || crop == "u")
{
nir <- crop(nir,ext)
if (crop=="f")
{
nir <- mask(nir,shape)
}
}
rad_b4 <- ((lmax4-lmin4)/(qcal_max-qcal_min)) * (nir-qcal_min) + lmin4
toa_nir <- pi * rad_b4 * d^2 / 1044 * sin(sun_ele*(pi/180))
}
############## Landsat ETM ending ##################
############## Landsat TM starting ##################
if (satellite=="LT")
{
if (crop == "u")
{
b4 <- raster (paste0 (directory, "/", sat_fold, "_B4.TIF"))
b3 <- raster (paste0 (directory, "/", sat_fold, "_B3.TIF"))
b2 <- raster (paste0 (directory, "/", sat_fold, "_B2.TIF"))
stak <- stack(c (b4, b3, b2))
plotRGB(stak)
print("Please define your extent from the map in plot preview for further processing")
print("You can click on the top left of custom subset region followed by the bottom right")
ext <- drawExtent()
}
qcal_max <- 255
d <- 0
for (i in 1:count_i)
{
line <- meta_data[i]
line_splited <- strsplit(line," ")
words <- line_splited[[1]]
counts <- length(words)
for (j in 1:counts)
{
if (words[j]=="QUANTIZE_CAL_MIN_BAND_1"){ qcal_min <- as.double(words[j+2])}
if (words[j]=="DATE_ACQUIRED"){ data_aq <- as.character(words[j+2])}
if (words[j]=="SUN_ELEVATION"){ sun_ele <- as.double(words[j+2])}
if (words[j]=="EARTH_SUN_DISTANCE"){ d <- as.double(words[j+2])}
if (words[j]=="SPACECRAFT_ID"){ tm_id <- as.character(words[j+2])}
if (words[j]=="RADIANCE_MAXIMUM_BAND_3"){ lmax3 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MAXIMUM_BAND_4"){ lmax4 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MINIMUM_BAND_3"){ lmin3 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MINIMUM_BAND_4"){ lmin4 <- as.double(words[j+2])}
}
}
if (tm_id=="\"LANDSAT_5\"")
{
esun3 <- 1551
esun4 <- 1036
}
if (tm_id!="\"LANDSAT_5\"")
{
esun3 <- 1554
esun4 <- 1033
}
if (d==0)
{
dat_tex <- as.Date(data_aq)
jul_ful <- julian(dat_tex)
yr_rmv_num <- jul_ful%/%365.25
jul_day <- jul_ful-(yr_rmv_num*365.25)+1.5
jul_flot <- jul_day%%365.25
jul_final <- as.integer(jul_flot)
d <- 1 + (0.0167 * sin ((pi/180) *2 *pi *(jul_final- 93.5) / 365))
}
red <- raster(paste0(directory,"/",sat_fold,"_B3.TIF"))
if (crop == "y" || crop == "f" || crop == "u")
{
red <- crop(red,ext)
if (crop=="f")
{
red <- mask(red,shape)
}
}
rad_b3 <- ((lmax3-lmin3)/(qcal_max-qcal_min)) * (red-qcal_min) + lmin3
toa_red <- pi * rad_b3 * d^2 / esun3 * sin(sun_ele*(pi/180))
nir <- raster(paste0(directory,"/",sat_fold,"_B4.TIF"))
if (crop == "y" || crop == "f" || crop == "u")
{
nir <- crop(nir,ext)
if (crop=="f")
{
nir <- mask(nir,shape)
}
}
rad_b4 <- ((lmax4-lmin4)/(qcal_max-qcal_min)) * (nir-qcal_min) + lmin4
toa_nir <- pi * rad_b4 * d^2 / esun4 * sin(sun_ele*(pi/180))
}
######## Landsat TM ending ############
ndvi <- (toa_nir-toa_red)/(toa_nir+toa_red)
#writeRaster(ndvi,paste0(op_directory,"/","ndvi_",data_aq), format= "GTiff", overwrite= TRUE)
op_bands <- list()
op_bands [[1]] <- ndvi
# Emissivity
op_names <- list()
op_names [[1]] <- "First variable ndvi band"
if (emissivity != "n")
{
emis <- 1.0094 + (0.047 * log (ndvi))
op_bands [[2]] <- emis
op_names [[2]] <- "Second variable is emissivity band"
#writeRaster(emis,paste0(op_directory,"/","emissivity_",data_aq), format= "GTiff", overwrite= TRUE)
cat ("\nEmissivity on pixels with negative NDVI values can't be computed. Thereby, those pixels will not have any values in the emissivity product")
cat ("\nEmissivity is produced as a variable named 'emis'")
}
op <- list()
op [[2]] <- op_bands
op [[1]] <- op_names
return(op)
cat ("\nProgram completed, output is produced as 'ndvi'")
}
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#' Normalized Difference Vegetation Index
#'
#' Normalized Difference Vegetation Index (NDVI). It is the most widely used satellite image derived index emphasizing on vegetation mapping.
#' This function can also be used to obtain the ground emissivity as well.
#' @param ext2crop,crop,directory Same as mentioned in \code{\link[ASIP]{arvi}}.
#' @param op_directory Specify the output directory (within double quotes). By default the input satellite image directory will be selected as the output directory.
#' @param emissivity Assign value "y" to get the emissivity of the surface as a seperate raster file.
#' @return File named ndvi_'date of satellite image acqisition'.tif in the input folder
#' @note 1. NDVI= (r_nir - r_red)/(r_nir + r_red)
#'
#' where, "r_" denotes TOA reflectance band.
#'
#' 2. Emissivity is calculated according to \href{http://www.tandfonline.com/doi/abs/10.1080/01431169308904400}{Van De Griend and Owe (1993)}.
#'
#' 3. Emissivity values will be absent on pixels with negative NDVI values. This can affect the land surface temperature results (not at-sensor brightness temperature) as well.
#' So, please review the study region and the requirements before using this function.
#'
#' 4. Other important notes are mentioned in \code{\link[ASIP]{custom.eqn}}.
#' @export
#' @references 1. \href{http://www.sciencedirect.com/science/article/pii/0034425787900381}{Huetet A R and Jackson R D (1987) Suitability of spectral indices for evaluating vegetation characteristics on arid rangelands, Remote sensing of environment, 23(2), pp:213-232. doi: 10.1016/0034-4257(87)90038-1.}
#'
#' 2. \href{http://www.tandfonline.com/doi/abs/10.1080/01431169308904400}{Van De Griend AA, Owe M (1993) On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. Int J Remote Sens 14:1119–1131. doi: 10.1080/01431169308904400}
#' @importFrom raster raster writeRaster extent mask crop
#' @importFrom utils tail
#' @examples
#' library (raster)
#' library (rgdal)
#' # Finding the path of the sample satellite image directory.
#' # User may define paths directly like "/home/ur_folder" or "C:/ur_folder"
#' path <- system.file ("TM_sample", package = "ASIP")
#' shapefil <- paste0 (path, "/test.shp")
#' ndvi (directory = path, crop = "y", ext2crop = shapefil)
# ndvi function
ndvi <- function(directory = getwd(), crop = "n", ext2crop = "none", op_directory = directory, emissivity = "n")
{
# If the directory is not set
bands <- length(list.files(directory,pattern = "*TIF"))
if (bands == 0)
stop("Define your satellite image folder path properly")
# Finding out which satellite sensor data & name of satellite image data
files <- list.files(directory)
for (i in 1:length(files))
{
file <- files[i]
broke_name <- strsplit(file, "_B1.TI")
broke_name <- broke_name[[1]]
if (utils::tail(broke_name,1) == "F")
{
sat_fold <- broke_name[1]
satellite <- substr(sat_fold,1,2)
break()
}
}
# Defining the crop extent
if (crop != "n" && crop != "y" && crop !="u" && crop != "f")
stop ("Define argument 'crop' properly. Use either n, y, f or u in double quotes. Type ?arvi in console to read more about the function")
if (crop != "n" && ext2crop == "none")
{
if (crop != "u")
stop ("Define argument 'ext2crop' properly if croppping is required, otherwise choose argument 'crop' as n in double quotes")
}
if (crop == "y" || crop == "f")
{
if (typeof (ext2crop) == "character")
{
shape <- raster::shapefile (ext2crop)
ext <- raster::extent (shape)
}
if (typeof (ext2crop) == "S4")
{
ext <- raster::extent (ext2crop)
shape <- ext2crop
}
}
# Defining folders properly
if (stringr::str_sub(op_directory) == "/")
{
op_directory <- stringr::str_sub(op_directory, start = 1L, end = -2L)
}
if (stringr::str_sub(directory) == "/")
{
directory <- stringr::str_sub(directory, start = 1L, end = -2L)
}
meta_data <- readLines(paste0(directory,"/",sat_fold,"_MTL.txt"))
count_i <- length(meta_data)
if (count_i==0){print("ERROR: MTL file not found")}
######### Landsat 8 starting###############
if (satellite=="LC")
{
if (crop == "u")
{
b5 <- raster (paste0 (directory, "/", sat_fold, "_B5.TIF"))
b4 <- raster (paste0 (directory, "/", sat_fold, "_B4.TIF"))
b3 <- raster (paste0 (directory, "/", sat_fold, "_B3.TIF"))
stak <- raster::stack(c(b5,b4,b3))
plotRGB(stak, scale = 65536)
print("Please define your extent from the map in plot preview for further processing")
print("You can click on the top left of custom subset region followed by the bottom right")
ext <- drawExtent()
}
# Extracting values from meta data
for (i in 1:count_i)
{
line <- meta_data[i]
line_splited <- strsplit(line," ")
words <- line_splited[[1]]
counts <- length(words)
for (j in 1:counts)
{
if (words[j]=="REFLECTANCE_ADD_BAND_5"){ nir_refl_add <- as.double(words[j+2])}
if (words[j]=="REFLECTANCE_MULT_BAND_5"){ nir_refl_mult <- as.double(words[j+2])}
if (words[j]=="REFLECTANCE_ADD_BAND_4"){ red_refl_add <- as.double(words[j+2])}
if (words[j]=="REFLECTANCE_MULT_BAND_4"){ red_refl_mult <- as.double(words[j+2])}
if (words[j]=="DATE_ACQUIRED"){ data_aq <- as.character(words[j+2])}
if (words[j]=="SUN_ELEVATION"){ sun_ele <- as.double(words[j+2])}
}
}
nir <- as.integer(raster(paste0(directory,"/",sat_fold,"_B5.TIF")))
if (crop == "y" || crop == "f" || crop == "u")
{
nir <- crop(nir, ext)
if (crop=="f")
{
nir <- mask(nir,shape)
}
}
toa_nir <- ((nir * nir_refl_mult) + nir_refl_add)/sin(sun_ele*(pi/180))
red <- as.integer(raster(paste0(directory,"/",sat_fold,"_B4.TIF")))
if (crop == "y" || crop == "f" || crop == "u")
{
red <- crop(red, ext)
if (crop=="f")
{
red <- mask(red,shape)
}
}
toa_red <- ((red * red_refl_mult) + red_refl_add)/sin(sun_ele*(pi/180))
}
########### Landsat-8 ending ##############
########### Landsat-7 starting ##############
if (satellite=="LE")
{
if (crop == "u")
{
b4 <- raster (paste0 (directory, "/", sat_fold, "_B4.TIF"))
b3 <- raster (paste0 (directory, "/", sat_fold, "_B3.TIF"))
b2 <- raster (paste0 (directory, "/", sat_fold, "_B2.TIF"))
stak <- stack(c (b4, b3, b2))
plotRGB(stak)
print("Please define your extent from the map in plot preview for further processing")
print("You can click on the top left of custom subset region followed by the bottom right")
ext <- drawExtent()
}
qcal_max <- 255
d <- 0
for (i in 1:count_i)
{
line <- meta_data[i]
line_splited <- strsplit(line," ")
words <- line_splited[[1]]
counts <- length(words)
for (j in 1:counts)
{
if (words[j]=="QUANTIZE_CAL_MIN_BAND_1"){ qcal_min <- as.double(words[j+2])}
if (words[j]=="EARTH_SUN_DISTANCE"){ d <- as.double(words[j+2])}
if (words[j]=="DATE_ACQUIRED"){ data_aq <- as.character(words[j+2])}
if (words[j]=="SUN_ELEVATION"){ sun_ele <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MAXIMUM_BAND_3"){ lmax3 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MAXIMUM_BAND_4"){ lmax4 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MINIMUM_BAND_3"){ lmin3 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MINIMUM_BAND_4"){ lmin4 <- as.double(words[j+2])}
}
}
if (d==0)
{
dat_tex <- as.Date(data_aq)
jul_ful <- julian(dat_tex)
yr_rmv_num <- jul_ful%/%365.25
jul_day <- jul_ful-(yr_rmv_num*365.25)+1.5
jul_flot <- jul_day%%365.25
jul_final <- as.integer(jul_flot)
d <- 1 + (0.0167 * sin ((pi/180) *2 *pi *(jul_final- 93.5) / 365))
}
red <- raster(paste0(directory,"/",sat_fold,"_B3.TIF"))
if (crop == "y" || crop == "f" || crop == "u")
{
red <- crop(red,ext)
if (crop=="f")
{
red <- mask(red,shape)
}
}
rad_b3 <- ((lmax3-lmin3)/(qcal_max-qcal_min)) * (red-qcal_min) + lmin3
toa_red <- pi * rad_b3 * d^2 / 1547 * sin(sun_ele*(pi/180))
nir <- raster(paste0(directory,"/",sat_fold,"_B4.TIF"))
if (crop == "y" || crop == "f" || crop == "u")
{
nir <- crop(nir,ext)
if (crop=="f")
{
nir <- mask(nir,shape)
}
}
rad_b4 <- ((lmax4-lmin4)/(qcal_max-qcal_min)) * (nir-qcal_min) + lmin4
toa_nir <- pi * rad_b4 * d^2 / 1044 * sin(sun_ele*(pi/180))
}
############## Landsat ETM ending ##################
############## Landsat TM starting ##################
if (satellite=="LT")
{
if (crop == "u")
{
b4 <- raster (paste0 (directory, "/", sat_fold, "_B4.TIF"))
b3 <- raster (paste0 (directory, "/", sat_fold, "_B3.TIF"))
b2 <- raster (paste0 (directory, "/", sat_fold, "_B2.TIF"))
stak <- stack(c (b4, b3, b2))
plotRGB(stak)
print("Please define your extent from the map in plot preview for further processing")
print("You can click on the top left of custom subset region followed by the bottom right")
ext <- drawExtent()
}
qcal_max <- 255
d <- 0
for (i in 1:count_i)
{
line <- meta_data[i]
line_splited <- strsplit(line," ")
words <- line_splited[[1]]
counts <- length(words)
for (j in 1:counts)
{
if (words[j]=="QUANTIZE_CAL_MIN_BAND_1"){ qcal_min <- as.double(words[j+2])}
if (words[j]=="DATE_ACQUIRED"){ data_aq <- as.character(words[j+2])}
if (words[j]=="SUN_ELEVATION"){ sun_ele <- as.double(words[j+2])}
if (words[j]=="EARTH_SUN_DISTANCE"){ d <- as.double(words[j+2])}
if (words[j]=="SPACECRAFT_ID"){ tm_id <- as.character(words[j+2])}
if (words[j]=="RADIANCE_MAXIMUM_BAND_3"){ lmax3 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MAXIMUM_BAND_4"){ lmax4 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MINIMUM_BAND_3"){ lmin3 <- as.double(words[j+2])}
if (words[j]=="RADIANCE_MINIMUM_BAND_4"){ lmin4 <- as.double(words[j+2])}
}
}
if (tm_id=="\"LANDSAT_5\"")
{
esun3 <- 1551
esun4 <- 1036
}
if (tm_id!="\"LANDSAT_5\"")
{
esun3 <- 1554
esun4 <- 1033
}
if (d==0)
{
dat_tex <- as.Date(data_aq)
jul_ful <- julian(dat_tex)
yr_rmv_num <- jul_ful%/%365.25
jul_day <- jul_ful-(yr_rmv_num*365.25)+1.5
jul_flot <- jul_day%%365.25
jul_final <- as.integer(jul_flot)
d <- 1 + (0.0167 * sin ((pi/180) *2 *pi *(jul_final- 93.5) / 365))
}
red <- raster(paste0(directory,"/",sat_fold,"_B3.TIF"))
if (crop == "y" || crop == "f" || crop == "u")
{
red <- crop(red,ext)
if (crop=="f")
{
red <- mask(red,shape)
}
}
rad_b3 <- ((lmax3-lmin3)/(qcal_max-qcal_min)) * (red-qcal_min) + lmin3
toa_red <- pi * rad_b3 * d^2 / esun3 * sin(sun_ele*(pi/180))
nir <- raster(paste0(directory,"/",sat_fold,"_B4.TIF"))
if (crop == "y" || crop == "f" || crop == "u")
{
nir <- crop(nir,ext)
if (crop=="f")
{
nir <- mask(nir,shape)
}
}
rad_b4 <- ((lmax4-lmin4)/(qcal_max-qcal_min)) * (nir-qcal_min) + lmin4
toa_nir <- pi * rad_b4 * d^2 / esun4 * sin(sun_ele*(pi/180))
}
######## Landsat TM ending ############
ndvi <- (toa_nir-toa_red)/(toa_nir+toa_red)
#writeRaster(ndvi,paste0(op_directory,"/","ndvi_",data_aq), format= "GTiff", overwrite= TRUE)
op_bands <- list()
op_bands [[1]] <- ndvi
# Emissivity
op_names <- list()
op_names [[1]] <- "First variable ndvi band"
if (emissivity != "n")
{
emis <- 1.0094 + (0.047 * log (ndvi))
op_bands [[2]] <- emis
op_names [[2]] <- "Second variable is emissivity band"
#writeRaster(emis,paste0(op_directory,"/","emissivity_",data_aq), format= "GTiff", overwrite= TRUE)
cat ("\nEmissivity on pixels with negative NDVI values can't be computed. Thereby, those pixels will not have any values in the emissivity product")
cat ("\nEmissivity is produced as a variable named 'emis'")
}
op <- list()
op [[2]] <- op_bands
op [[1]] <- op_names
return(op)
cat ("\nProgram completed, output is produced as 'ndvi'")
}
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